Surveillance, Epidemiology, and End Results (SEER) and SEER-Medicare Databases: Use in Clinical Research for Improving Colorectal Cancer Outcomes

Environmental Levels of Volatile Organic Compounds, Race, and Socioeconomic Markers Correlate with Areas of High Colorectal Cancer Incidence

BACKGROUND

Ambient levels of volatile organic compounds (VOCs) released from nearby industrial plants have shown positive associations with increased colorectal cancer (CRC) rates. The objective of this study is to analyze the distribution of CRC in the context of socioeconomic status and its correlation with community environmental data.

METHODS

A retrospective study analyzed CRC patients from 2021 to 2023. The census tracts of the patients' residential addresses were obtained, and CRC rates were calculated for each census tract. Socioeconomic data was gathered on these communities. Environmental VOC measurements were obtained from the National Scale Air Toxics Assessment. All datapoints were compared to statewide levels.

RESULTS

Three census tracts in the county had higher CRC cases comparatively. These areas exhibited higher incidence rates and localized clusters of CRC cases, higher distribution of Black or African Americans, lower household incomes, lower home values, and lower educational attainment. VOC measurements in these census tracts had higher levels compared to county and state averages: specifically, 10.68% higher than county and 48.07% higher than state benzene levels (0.52 µg/m3 clusters vs 0.47µg/m3 county vs 0.35 µg/m3 state), 10.84% and 129.15% higher toluene (1.65 µg/m3 vs 1.49 vs 0.72 µg/m3), and 15.64% and 141.87% higher butadiene (0.048 µg/m3 vs 0.041 µg/m3 vs 0.020 µg/m3).

CONCLUSION

This study illustrates a positive correlation between higher ambient exposure to VOCs with increased CRC incidence. These findings underscore the potential interplay of environmental factors, socioeconomic determinants, and environmental injustice when considering strategies to address health disparities and CRC incidence.

The role of CXC chemokines and receptors in breast cancer

CXC chemokines are a class of cytokines possessing chemotactic properties. Studies indicate that CXC chemokines exhibit dysregulation in miscellaneous cancer categories and are significantly associated with the advancement of tumors. Breast cancer is a commonly diagnosed and fatal cancer among the female population. Breast cancer pathogenesis and progression involve various mechanisms, including invasion, metastasis, angiogenesis, and inflammation. Chemokines and their receptors are involved in all of these processes. The CXC chemokine receptors (CXCRs) and their related ligands have attracted considerable attention due to their multifaceted functions in facilitating and controlling tumor proliferation. CXCRs are expressed by both cancer cells and immune cells, and they play a crucial role in regulating the tumor microenvironment and the immune response. This review aims to assess the potential of CXCRs and CXC chemokines as therapeutic targets or biomarkers for personalized therapy. Additionally, it provides an overview of the current understanding of the expression, function, and prognostic relevance of CXCRs in breast cancer. Furthermore, the challenges and potential prospects pertaining to CXCR investigation in breast cancer are deliberated.

Differences in risk factors for mortality between T2N1M0 and T3N0M0 lobular breast cancer patients: a comparative study

Objective

This study aimed to explore the differences in risk factors for mortality between T2N1M0 and T3N0M0 lobular breast cancer, and investigate the factors associated with non-lobular breast cancer mortality.

Methods

Data from 2,693 T2N1M0 and 1,384 T3N0M0 lobular breast cancer patients from the SEER database (2008-2018) were analyzed. The lobular breast cancer-specific and non-lobular breast cancer mortality were compared using the Kaplan-Meier curve and Log-rank test. The Cox proportional hazards regression analysis was used to determine the risk factors associated with non-lobular breast cancer mortality.

Results

The total survival time showed a significant difference between the T2N1M0 and T3N0M0 groups (p = 0.0011). Statistically significant difference were found in lung-related disease mortality (p = 0.0023), with the survival rate of T2N1M0 higher than that of T3N0M0. Age, surgery, radiotherapy, and chemotherapy were independent factors associated with mortality in lung-related disease patients with both subtypes, and compared with T2N1M0, radiotherapy in T3N0M0 increased the risk of lung-related disease mortality (HR = 2.076, 95% CI: 1.4318-3.011).

Conclusion

The T3N0M0 group had a higher mortality rate from lung-related diseases compared to the T2N1M0 group, and radiotherapy may increase the risk of lung-related disease death in T3N0M0 patients. These findings provide valuable information for treatment strategies for T2N1M0 and T3N0M0 subtypes of patients and assist physicians and patients make better treatment choices.

Socioeconomic disparities in survival of patients with non-muscle invasive urothelial carcinoma

PURPOSE

Limited data are available on the impact of socioeconomic disparities on the survival of patients with non-muscle invasive urothelial carcinoma (NMIBC).

METHODS

We analyzed the Surveillance, Epidemiology, and End Results database to review the effects of sex, race, location, and socioeconomic factors on the survival of patients with NMIBC. We calculated 5-year overall survival (OS) and cancer-specific survival (CSS) using the log-rank test. The impact of socioeconomic factors on OS and CSS was analyzed using the Cox proportional hazards model adjusted for clinical characteristics. Hazard ratios (HR) and survival rates were reported with 95% confidence intervals (CI).

RESULTS

Analysis of 3831 patients showed that older age was associated with worse OS (HR 1.08 [1.08-1.09]) and CSS (HR 1.05 [1.04-1.06]). Women and men had similar OS (HR 0.91 [0.82-1.01]) and CSS (HR 1.12 [0.95-1.32]). Black patients had worse OS (HR 1.33 [1.08-1.62] and CSS [HR 1.54 [1.13-2.05]) than their White counterparts. Patients with an annual household income below $40,000 had worse outcomes compared to those with income above $70,000 for both OS (HR 1.79 [1.37-2.33]) and CSS (HR 1.924 [1.26-2.89]).

CONCLUSIONS

There were no gender differences in survival outcomes of NMIBC. Older age, Black, American Indian/Alaskan Native, and patients with a household income below $40,000 appear to have worse survival. However, the area of residence did not seem to affect patient survival.

Accuracy of Faecal Matrix-Metalloproteinase-9 (MMP-9) for Colorectal Cancer Detection in Makassar, Indonesia

BACKGROUND

Colorectal cancer (CRC) is one of the most frequent malignancies. Insufficient comprehensive screening by health authorities raises colorectal cancer risk in developing countries. While colonoscopy is the gold standard for CRC diagnosis, it has limitations. Faecal immunochemical test (FIT) and guaiac faecal occult blood test (gFOBT) are famous for colorectal cancer screening tests. FIT is more sensitive and specific than gFOBT. However, both FIT and gFOBT have limited accuracy in diagnosing advanced adenoma and proximal colon cancer. Matrix-metalloproteinase-9 (MMP-9) remodels the extracellular matrix and is associated with CRC progression. Its levels can be detected in faecal samples. Studies specifically evaluating the accuracy of faecal MMP-9 as a diagnostic test are limited. Therefore, this study aims to evaluate the accuracy of faecal MMP-9 for detecting colorectal cancer in our centre.

METHODS

Ninety patients provided faecal samples for MMP-9 analysis. Faecal MMP-9 levels were measured by ELISA. Diagnostic accuracy was evaluated using the diagnostic test method.

RESULT

Patients were divided into four groups: control: 10; hyperplastic and adenoma polyp: 9; colitis and proctitis: 37; and colorectal carcinoma: 34. Faecal MMP-9 levels significantly increased in colorectal carcinoma compared to the other group (P<0.001). ROC analysis indicated that the accuracy of faecal MMP-9 in differentiating CRC patients against controls was good, with the area under curve (AUC) 0.85 (sensitivity 82.35% and specificity 80%). The accuracy of faecal MMP-9 for detecting proximal colon cancer was excellent, with an AUC of 0.96 (sensitivity 80% and specificity 80%). The AUC for adenoma detection was 0.83, with a sensitivity of 77.78% and specificity of 80%.

CONCLUSION

Faecal MMP-9 demonstrated significant accuracy in differentiating colorectal cancer from normal subjects, exhibiting satisfactory sensitivity and specificity. Compared to FIT, Faecal MMP-9 demonstrated superior detection of proximal colon cancer and adenoma.

Differences in the epidemiology and survival of patients with colorectal cancer between China and the United States: a large cross-sectional study

Studying the epidemiological and management characteristics of colorectal cancer (CRC) between China and the US has important implications. The present cross-sectional study included patients from SEER and Southwest China Colorectal (SCC) databases. Incidence, treatment and survival information were compared between two countries. 86859 patients in the SEER database and 5838 patients in the SCC database were included. The estimated incidence of CRC in the US was greater than that in China from 2006 to 2019. The most common tumor sites of CRC patients in China were the RSC (66.5%), RCC (20.2%) and LCC (13.3%), while those in the US were the RCC (44.4%), RSC (29.8%) and LCC (25.8%). Chinese CRC patients were more likely to be male (58.9% vs 52.4%, p < 0.001), have a greater stage II CRC rate (49.8% vs 27.8%, p < 0.001), younger age at diagnosis (median 64 vs 66 years, p < 0.001). Radical surgery rates were lower in Chinese RCC (92.3% vs 93.9%, p < 0.001) and LCC (88.9% vs 92.0%, p < 0.001) patients. The adjuvant therapy rates were lower in Chinese CRC patients. The 5-year overall survival rates were 71.8% and 78.2% for Chinese and US CRC patients, respectively (p < 0.001). China is undergoing an increasing incidence of CRC. The treatment and mortality of CRC differ in China and US populations. China had a lower adjuvant therapy rate and a lower 5-year OS rate compared with the US.

Metformin Inhibits NLRP3 Inflammasome Expression and Regulates Inflammatory Microenvironment to Delay the Progression of Colorectal Cancer

BACKGROUND

Colorectal cancer is a common malignant tumor, with about one million people diagnosed with it worldwide each year. Recent studies have found that metformin can inhibit the production of inflammatory factors and regulate the polarization of immune cells. However, whether metformin can regulate the inflammatory microenvironment and delay the progression of colorectal cancer by inhibiting the inflammatory response has not been deeply studied yet.

OBJECTIVES

This study aimed to explore the molecular mechanism by which metformin inhibits the expression of NLRP3 inflammasome, regulates the inflammatory microenvironment, and delays the progression of colorectal cancer through in vitro cell experiments.

METHODS

In this research, NLRP3 was knocked down in human colorectal cancer cells, and metformin was added to them. Cell proliferation ability was detected by CCK8, and cell migration and invasion abilities were assessed by Transwell assay. The apoptosis rate was determined by flow cytometry. In addition, the expression of NLRP3 inflammatory vesicles and inflammatory factors in each group of cells was studied by qRT-PCR and Western blotting. Finally, clinical colorectal cancer samples were analyzed by immunohistochemistry.

RESULTS

The results of the study showed that NLRP3 expression was significantly increased in colorectal cancer cell lines and human colorectal cancer tissues. Knockdown of NLRP3 significantly inhibited tumor cell proliferation, migration, and invasion. In addition, the proliferation, migration and invasion of tumor cells were also significantly reduced by the addition of metformin intervention. Furthermore, qRT-PCR and WB results demonstrated that the expression of IL-1β, IL-6, TNF- α, TGF-β, and IL-10 was down-regulated in LS1034 tumor cells after NLRP3 knockdown. In addition, metformin intervention also resulted in different degrees of downregulation of NLRP3 and inflammatory factor expression (p π0.05). Notably, the reduction in inflammatory factors was more pronounced after the combination of NLRP3 knockdown and metformin intervention.

CONCLUSION

Metformin can inhibit the expression of NLRP3 inflammasome, thereby suppressing the expression of inflammation-related factors, reducing the damage of the inflammatory microenvironment to normal cells, and delaying the progression of colorectal cancer.

Comparing SEER and NCDB: a case study using colorectal cancer

Nationwide datasets are frequently used to examine cancer trends and outcomes in the U.S. Understanding the strengths and limitations of the commonly used Surveillance, Epidemiology, and End Results (SEER) Program and the National Cancer Database (NCDB) is important when designing studies and interpreting results. We used colorectal cancer (CRC) as a case study to compare information available. We identified 575,128 (SEER) and 1,578,046 (NCDB) adults diagnosed with CRC between 2004 and 2021. The distribution of age, tumor location, stage, and treatment did not meaningfully differ between SEER and NCDB. SEER represents racially and ethnically diverse populations, including a higher proportion of Hispanic (11.7% vs 5.8%) and Asian/Pacific Islander (8.6% vs 3.3%) persons. SEER includes more information on area-level characteristics, such as county-level measures of poverty, unemployment, and migration and census tract-level measures of socioeconomic status. Age-adjusted incidence, mortality rates, and cause-specific survival are only available in SEER, facilitating detailed analyses of racial, ethnic, and socioeconomic differences in cancer incidence and mortality. NCDB provides information on tumor characteristics and treatment not available in SEER, including microsatellite instability, KRAS mutation, palliative treatment, unplanned readmissions, and 30-day mortality after surgery, facilitating analyses of treatment effectiveness and outcomes. Five-year overall survival was similar in SEER (55.6%) vs NCDB (57.5%).

Prognostic nomogram models for elderly patients with differentiated thyroid carcinoma: A population-based study

This study aimed to develop and validate a prognostic model for elderly patients with differentiated thyroid carcinoma (DTC) based on various demographic and clinical parameters in order to accurately predict patient outcomes. Patients who were diagnosed with DTC and were over 55 years old between 2010 and 2019 were identified from the Surveillance, Epidemiology, and End Results database. The patients were then randomly divided into a training set and a validation set in a 7:3 ratio, and patients from our center were included as an external validation group. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify independent prognostic factors, which were then utilized to develop nomograms for predicting the prognosis. The discriminative ability of the nomograms was evaluated using the concordance index, and the calibration was assessed using calibration plots. The clinical usefulness and benefits of the predictive models were determined through decision curve analysis. The findings of the stepwise Cox regression analysis revealed that several variables, including age, marital status, sex, multifocality, T stage, N stage, and M stage, were significantly associated with overall survival in elderly patients with DTC. Additionally, age, tumor size, multifocality, T stage, N stage, and M stage were identified as the primary determinants of cancer specific survival in elderly patients with DTC. Using these predictors, nomograms were constructed to estimate the probability of overall survival and cancer specific survival. The nomograms demonstrated a high level of predictive accuracy, as evidenced by the concordance index, and the calibration plots indicated that the predicted outcomes were consistent with the actual outcomes. Furthermore, the decision curve analysis demonstrated that the nomograms provided substantial clinical net benefit, indicating their utility in clinical practice.

Secondary databases in gynecologic cancer research

Observational and cohort studies using large databases have made important contributions to gynecologic oncology. Knowledge of the advantages and potential limitations of commonly used databases benefits both readers and reviewers. In this review, researchers familiar with National Cancer Database (NCDB), Surveillance, Epidemiology, and End Results Program (SEER), SEER-Medicare, MarketScan, Healthcare Cost and Utilization Project (HCUP), National Surgical Quality Improvement Program (NSQIP), and Premier, describe each database, its included data, access, management, storage, highlights, and limitations. A better understanding of these commonly used datasets can help readers, reviewers, and researchers to more effectively interpret and apply study results, evaluate new research studies, and develop compelling and practice-changing research.

Prognostic value of a modified pathological staging system for gastric cancer based on the number of retrieved lymph nodes and metastatic lymph node ratio

Aim

The prognosis for gastric cancer (GC) remains grim, underscoring the importance of accurate staging and treatment. Given the potential benefits of using lymph node ratio (LNR) for improved prognostication and treatment planning, it is critical to incorporate examined lymph nodes (ELN) count in an integrated GC staging system.

Methods

Patients data from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015 was utilized as training set. The Mantel-Cox survival test was used to calculate chi-square values for 40 LNR segments with a 0.025 interval, defining a novel LNR-based N (rN) classification based on the cutoff points. A revised AJCC (rAJCC) staging system was established by replacing the 8th AJCC N staging with a rN classification. The relationship between the ELN count and prognosis or positive lymph node detection was conducted by using multivariable models. The series of the odds ratios and hazard ratios were fitted with a locally weighted scatterplot smoothing (LOWESS) smoother, and the structural break points were determined by Chow test to clarify an optimal minimum ELN count. The integrated GC staging system incorporated both rAJCC system and the ideal ELN count. Discriminatory ability and prognostic homogeneity of the rAJCC and integrated staging system was compared with AJCC staging system in the SEER validation set (2016-2017), the Cancer Genome Atlas Program (TCGA) database, and the Third Affiliated Hospital of Sun Yat-sen University database.

Results

The current study found that LNR and ELN count are both significantly associated with the prognosis of GC patients (HR = 0.98, p < 0.001 and HR = 2.51, p < 0.001). Four peaks of the chi-square value were identified as LNR cut-off points at 0.025, 0.175, 0.45 and 0.6 to define a novel rN stage. In comparison to the 8th AJCC staging system, the rAJCC staging system demonstrated significant prognostic advantages and discriminatory ability in the training set (5-Y OS AUC: 71.7 vs. 73.0; AIC: 57,290.7 vs. 57,054.9). The superiority of the rAJCC staging system was confirmed in all validation sets. Using a LOWESS smoother and Chow test, a threshold ELN count of 30 was determined to maximum improvement in the prognosis of node-negative patients without downgrading due to potential metastasis, while also maximizing the detection efficiency of at least one involved lymph node. The integrated staging system, combining the refined rAJCC classification with an optimized ELN count threshold, has demonstrated superior discriminatory performance compared to the standalone rAJCC or the traditional AJCC system.

Conclusion

The development of a novel GC staging system, which integrated the LNR-based N classification and the minimum ELN count, has exhibited superior prognostic accuracy, holding promise as a valuable asset in the clinical management of GC. However, it is crucial to recognize the limitations from the retrospective database, which should be addressed in subsequent analyses.

Low neighborhood socioeconomic status is associated with poor outcomes in young adults with colorectal cancer

BACKGROUND

The incidence of early-onset colorectal cancer has increased markedly over the past decade. Although established for older adults, there are limited data on socioeconomic and racial disparities in screening, treatment, and outcomes in this distinct group.

METHODS

Adults with primary colorectal cancer diagnosed at age <50 were identified from the Surveillance, Epidemiology, and End Results database. The exposure of interest was neighborhood socioeconomic status based on the Yost Index, a census-tract level composite score of neighborhood economic health. Univariate analysis was performed with χ2 analyses. Logistic regression models were created to evaluate the association of neighborhood socioeconomic status (Yost Index quintile) with metastasis at presentation and surgical intervention. Kaplan-Meier and Cox proportional hazards models were created.

RESULTS

In total, 45,660 early-onset colorectal cancer patients were identified; 16.8% (7,679) were in the lowest quintile of neighborhood socioeconomic status. Patients with the lowest neighborhood socioeconomic status were 1.13 times (95% confidence interval 1.06-1.21) more likely to present with metastases and had lower survival (hazard ratio 1.45, 95% confidence interval 1.37-1.53) compared to those with the highest neighborhood socioeconomic status. Non-Hispanic Black patients were more likely to present with metastatic disease (odds ratio 1.11, 95% confidence interval 1.05-1.19), less likely to undergo surgery for localized or regional disease (odds ratio 0.48, 95% confidence interval 0.43-0.53), and had lower survival (hazard ratio 1.21, 95% confidence interval 1.15-1.27) than non-Hispanic White patients.

CONCLUSION

Socioeconomic and racial disparities in early-onset colorectal cancer span diagnosis, treatment, and survival. As the disease burden of early-age onset colorectal cancer increases, interventions to boost early diagnosis and access to surgery are necessary to improve survival among minorities and patients with low neighborhood socioeconomic status.

Machine learning for predicting liver and/or lung metastasis in colorectal cancer: A retrospective study based on the SEER database

OBJECTIVE

This study aims to establish a machine learning (ML) model for predicting the risk of liver and/or lung metastasis in colorectal cancer (CRC).

METHODS

Using the National Institutes of Health (NIH)'s Surveillance, Epidemiology, and End Results (SEER) database, a total of 51265 patients with pathological diagnosis of colorectal cancer from 2010 to 2015 were extracted for model development. On this basis, We have established 7 machine learning algorithm models. Evaluate the model based on accuracy, and AUC of receiver operating characteristics (ROC) and explain the relationship between clinical pathological features and target variables based on the best model. We validated the model among 196 colorectal cancer patients in Beijing Electric Power Hospital of Capital Medical University of China to evaluate its performance and universality. Finally, we have developed a network-based calculator using the best model to predict the risk of liver and/or lung metastasis in colorectal cancer patients.

RESULTS

51265 patients were enrolled in the study, of which 7864 (15.3 %) had distant liver and/or lung metastasis. RF had the best predictive ability, In the internal test set, with an accuracy of 0.895, AUC of 0.956, and AUPR of 0.896. In addition, the RF model was evaluated in the external validation set with an accuracy of 0.913, AUC of 0.912, and AUPR of 0.611.

CONCLUSION

In this study, we constructed an RF algorithm mode to predict the risk of colorectal liver and/or lung metastasis, to assist doctors in making clinical decisions.

The development and validation of automated machine learning models for predicting lymph node metastasis in Siewert type II T1 adenocarcinoma of the esophagogastric junction

Background

Lymph node metastasis (LNM) is considered an essential prognosis factor for adenocarcinoma of the esophagogastric junction (AEG), which also affects the treatment strategies of AEG. We aimed to evaluate automated machine learning (AutoML) algorithms for predicting LNM in Siewert type II T1 AEG.

Methods

A total of 878 patients with Siewert type II T1 AEG were selected from the Surveillance, Epidemiology, and End Results (SEER) database to develop the LNM predictive models. The patients from two hospitals in Suzhou were collected as the test set. We applied five machine learning algorithms to develop the LNM prediction models. The performance of predictive models was assessed using various metrics including accuracy, sensitivity, specificity, the area under the curve (AUC), and receiver operating characteristic (ROC) curve.

Results

Patients with LNM exhibited a higher proportion of male individuals, a poor degree of differentiation, and submucosal infiltration, with statistical differences. The deep learning (DL) model demonstrated relatively good accuracy (0.713) and sensitivity (0.868) among the five models. Moreover, the DL model achieved the highest AUC (0.781) and sensitivity (1.000) in the test set.

Conclusion

The DL model showed good predictive performance among five AutoML models, indicating the advantage of AutoML in modeling LNM prediction in patients with Siewert type II T1 AEG.

Differences in overall survival of penile cancer patients versus population-based controls

PURPOSE

To assess whether 5-year overall survival (OS) of squamous cell carcinoma of the penis (SCCP) patients differs from age-matched male population-based controls.

METHODS

We relied on the Surveillance Epidemiology and End Results database (2004-2018) to identify newly diagnosed (2004-2013) SCCP patients. For each case, we simulated an age-matched control (Monte Carlo simulation), relying on the Social Security Administration (SSA) Life Tables with 5 years of follow-up. We compared OS between SCCP patients and population-based controls in a stage-specific fashion. Smoothed cumulative incidence plots displayed cancer-specific mortality (CSM) versus other-cause mortality (OCM).

RESULTS

Of 2282 SCCP patients, the stage distribution was as follows: stage I 976 (43%) versus stage II 826 (36%) versus stage III 302 (13%) versus stage IV 178 (8%). At 5 years, OS of SCCP patients versus age-matched population-based controls was as follows: stage I 63% versus 80% (Δ = 17%), stage II 50% versus 80% (Δ = 30%), stage III 39% versus 84% (Δ = 45%), stage IV 26% versus 87% (Δ = 61%). At 5 years, CSM versus OCM in SCCP patients according to stage was as follows: stage I 12% versus 24%, stage II 22% versus 28%, stage III 47% versus 14%, and stage IV 60% versus 14%.

CONCLUSION

SCCP patients exhibit worse OS across all stages. The difference in OS at 5 years between SCCP and age-matched male population-based controls ranged from 17% to 61%. At 5 years, CSM accounted for 12% to 60% of all deaths, across all stages.

Cardiovascular-specific mortality and risk factors in colorectal Cancer patients: A cohort study based on registry data of over 500,000 individuals in the US

BACKGROUND

Colorectal cancer (CRC) is one of the most common cancers worldwide, and recent studies have found that CRC patients are at increased risk for cardiovascular disease (CVD). This study aimed to investigate competing causes of death and prognostic factors among a large cohort of CRC patients and to describe cardiovascular-specific mortality in relation to the US standard population.

METHODS

This registry-based cohort study identified patients diagnosed with CRC between 1973 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database in the US. Cumulative mortality functions, conditional standardized mortality ratios, and cause-specific hazard ratios were calculated.

RESULTS

Of the 563,298 eligible CRC patients included in this study, 407,545 died during the follow-up period. CRC was the leading cause of death, accounting for 49.8% of all possible competing causes of death. CVD was the most common non-cancer cause of death, accounting for 17.8% of total mortality. This study found that CRC patients have a significantly increased risk of cardiovascular-specific mortality compared to the US standard population, with the risk increasing with age and extended survival time.

CONCLUSION

This study highlights the need to develop multidisciplinary prevention and management strategies for CRC and CVD to improve CRC patients' survival and quality of life.

Prognostic nomogram for primary splenic lymphoma: a SEER database-based study

This study aimed to establish a nomogram model based on the clinicopathological factors affecting the prognosis of patients with primary splenic lymphoma (PSL) to predict the overall survival (OS) and cancer-specific survival (CSS) of patients. A total of 4074 patients diagnosed with PSL were included in this study. Among them, 4052 cases from the SEER (Surveillance, Epidemiology, and End Results) database were randomized into a training set and an internal validation set in a 7:3 ratio. Another 22 patients from the First Affiliated Hospital of Xi'an Jiaotong University were used as an external validation set. The prognostic factors affecting the OS and CSS of patients were analyzed using univariate and multivariate Cox regression models. Survival analysis was performed using Kaplan-Meier (KM) method and compared by Log-rank test. Then, a nomogram model was established to predict OS and CSS. Finally, the model was validated both internally and externally using the concordance index (C-index), receiver operating characteristic curve (ROC), and calibration curve to evaluate its predictive value, and the decision curve analysis (DCA) was conducted to assess its clinical utility. Our results showed that the model displayed a good prediction ability. In the training set, the OS rates at 1, 3, and 5 years were 85.9%, 75.8% and 70.1%, respectively, while the CSS rates at 1, 3, and 5 years were 91.9%, 86.2% and 82.3%, respectively. Predictors in the prediction model of OS included age, sex, marital status, Ann Arbor stage, histology, surgery, chemotherapy and year at diagnosis. On the other hand, predictors in the model of CSS included age, Ann Arbor stage, histology, chemotherapy, and year at diagnosis. Internal and external validation of the nomogram model showed that the C-index for predicting OS was 0.678 (0.662, 0.694) in the training set, 0.672 (0.648, 0.696) in the internal validation set, and 0.704 (0.565, 0.843) in the external validation set; the C-index for predicting CSS was 0.685 (0.661, 0.709) in the training set, 0.683 (0.650, 0.716) in the internal validation set, and 0.676 (0.488, 0.864) in the external validation set. The calibration curves for several groups showed good consistency, and DCA suggested its clinical usability. In conclusion, the nomogram constructed in this study has a good predictive value for the survival of patients with PSL, and can be a clinically applicable and practical prediction tool, facilitating rapid and accurate individualized predictions of the patient survival.

How to use the Surveillance, Epidemiology, and End Results (SEER) data: research design and methodology

In the United States (US), the Surveillance, Epidemiology, and End Results (SEER) program is the only comprehensive source of population-based information that includes stage of cancer at the time of diagnosis and patient survival data. This program aims to provide a database about cancer incidence and survival for studies of surveillance and the development of analytical and methodological tools in the cancer field. Currently, the SEER program covers approximately half of the total cancer patients in the US. A growing number of clinical studies have applied the SEER database in various aspects. However, the intrinsic features of the SEER database, such as the huge data volume and complexity of data types, have hindered its application. In this review, we provided a systematic overview of the commonly used methodologies and study designs for retrospective epidemiological research in order to illustrate the application of the SEER database. Therefore, the goal of this review is to assist researchers in the selection of appropriate methods and study designs for enhancing the robustness and reliability of clinical studies by mining the SEER database.

Prognostic Significance of Primary Tumor Surgery in Adenoid Cystic Carcinoma Patients With Distant Metastases at Diagnosis: A Population-Based Database Analysis in Head and Neck Region

Purpose: Adenoid cystic carcinoma (ACC) is an aggressive cancer that often leads to poor prognosis, especially when it has metastasized. The prognostic significance of primary tumor surgery (PTS) for ACC with distant metastasis (DM) at the time of diagnosis has not been extensively studied. Methods: Using data from the surveillance, epidemiology, and end results (SEER) database from 2010 to 2019, we identified patients with ACC in head and neck region and synchronous DM. We evaluated the effect of PTS on different patterns of metastasis using Kaplan-Meier analysis, log-rank tests, and multivariate Cox regression analysis to assess the therapeutic benefit of PTS in the overall cohort and various subgroups. Results: Of the 192 identified patients with synchronous metastatic ACC of head and neck, 91 (47.4%) underwent PTS. Patients who received PTS had significantly better survival than nonsurgical patients (median overall survival: 19 vs 43 months, P = .006). Cox regression analysis also showed that PTS was associated with improved survival (HR = .46, 95% CI: 0.42-0.88; P = .028). In sub-analyses, except for patients with liver metastases [overall survival (OS), P = .107, cancer-specific survival (CSS), P = .153], PTS consistently conferred significant survival benefits in patients with bone metastases (OS, P = .041, CSS, P = .065) and lung metastases (OS, P = .016, CSS, P = .027). PTS also led to better survival in patients who did not receive radiotherapy (median OS: 13 vs 52 months, P = .007). Conclusion: Our study suggests that PTS in metastatic ACC patients of head and neck improved overall and CSS, particularly in those with bone or lung metastases and those who did not receive radiotherapy. However, further prospective studies are needed to confirm these findings, and the indications for PTS in metastatic ACC should be carefully evaluated by a multidisciplinary board.

Deciphering the DNA methylation landscape of colorectal cancer in a Korean cohort

Aberrant DNA methylation plays a pivotal role in the onset and progression of colorectal cancer (CRC), a disease with high incidence and mortality rates in Korea. Several CRC-associated diagnostic and prognostic methylation markers have been identified; however, due to a lack of comprehensive clinical and methylome data, these markers have not been validated in the Korean population. Therefore, in this study, we aimed to obtain the CRC methylation profile using 172 tumors and 128 adjacent normal colon tissues of Korean patients with CRC. Based on the comparative methylome analysis, we found that hypermethylated positions in the tumor were predominantly concentrated in CpG islands and promoter regions, whereas hypomethylated positions were largely found in the open-sea region, notably distant from the CpG islands. In addition, we stratified patients by applying the CpG island methylator phenotype (CIMP) to the tumor methylome data. This stratification validated previous clinicopathological implications, as tumors with high CIMP signatures were significantly correlated with the proximal colon, higher prevalence of microsatellite instability status, and MLH1 promoter methylation. In conclusion, our extensive methylome analysis and the accompanying dataset offers valuable insights into the utilization of CRC-associated methylation markers in Korean patients, potentially improving CRC diagnosis and prognosis. Furthermore, this study serves as a solid foundation for further investigations into personalized and ethnicity-specific CRC treatments. [BMB Reports 2023; 56(10): 569-574].

Prediction model of liver metastasis risk in patients with gastric cancer: A population-based study

Liver was the most common site of distant metastasis in patients with gastric cancer (GC). The prediction model of the risk of liver metastasis was rarely proposed. Therefore, we aimed to establish a prediction model for liver metastasis in patients with GC. In this retrospective cohort study, we extracted demographic and clinical data of all the GC patients from the Surveillance, Epidemiology, and End Results registration database from 2010 to 2015. Patients were divided into training set (n = 1691) for model development and testing set (n = 3943) for validation. Univariable and multivariable logistic regression analyses were carried out on the training set to screen potential predictors of liver metastasis and constructed a prediction model. The receiver operator characteristics curves with the area under curve values were used to assess the predictive performance of the liver metastasis prediction model. And a nomogram of the prediction model was also constructed. Of the total 5634 GC patients, 444 (7.88%) had liver metastasis. Variables including age, gender, N stage, T stage, Lauren classification, tumor size, histological type, and surgery were included in the liver metastasis prediction model. The study results indicated that the model had excellent discriminative ability with an area under curve of 0.851 (95% confidence interval: 0.829-0.873) in the training set, and that of 0.849 (95% confidence interval: 0.813-0.885) in the testing set. We have developed an effective prediction model with 8 easily acquired predictors of liver metastasis. The prediction model could predict the risk of liver metastasis in GC patients and performed well, which would assist clinicians to make individualized prediction of liver metastasis in GC patients and adjust treatment strategies in time to improve the prognosis.

An Updated Overview of Existing Cancer Databases and Identified Needs

Our search of existing cancer databases aimed to assess the current landscape and identify key needs. We analyzed 71 databases, focusing on genomics, proteomics, lipidomics, and glycomics. We found a lack of cancer-related lipidomic and glycomic databases, indicating a need for further development in these areas. Proteomic databases dedicated to cancer research were also limited. To assess overall progress, we included human non-cancer databases in proteomics, lipidomics, and glycomics for comparison. This provided insights into advancements in these fields over the past eight years. We also analyzed other types of cancer databases, such as clinical trial databases and web servers. Evaluating user-friendliness, we used the FAIRness principle to assess findability, accessibility, interoperability, and reusability. This ensured databases were easily accessible and usable. Our search summary highlights significant growth in cancer databases while identifying gaps and needs. These insights are valuable for researchers, clinicians, and database developers, guiding efforts to enhance accessibility, integration, and usability. Addressing these needs will support advancements in cancer research and benefit the wider cancer community.

National Databases for Assessment of Quality

With the rise in the availability of large health care datasets, database research has become an important tool for colorectal surgeon to assess health care quality and implement practice changes. In this chapter, we will discuss the benefits and drawbacks of database research for quality improvement, review common markers of quality for colorectal surgery, provide an overview of frequently used datasets (including Veterans Affairs Surgical Quality Improvement Program, National Surgical Quality Improvement Project, National Cancer Database, National Inpatient Sample, Medicare Data, and Surveillance, Epidemiology, and End Results), and look ahead to the future of database research for the improvement of quality.

A postsurgical prognostic nomogram for patients with lymph node positive rectosigmoid junction adenocarcinoma

OBJECTIVE

The definition of rectosigmoid junction (RSJ) is still in debate. The treatment and prognosis of patients with rectosigmoid junction cancer (RSJC) and positive lymph nodes (PLN-RSJCs) are mostly based on the American Joint Committee on Cancer (AJCC) staging system. Our study aims to assist clinicians in creating a more intuitive and accurate nomogram model for PLN-RSJCs for the prediction of patient overall survival (OS) after surgery.

METHODS

Based on the Surveillance, Epidemiology, and End Results (SEER) database, we extracted 3384 patients with PLN-RSJCs and randomly divided them into development (n = 2344) and validation (n = 1004) cohorts at a ratio of 7:3. Using univariate and multivariate COX regression analysis, we identified independent risk factors associated with OS in PLN-RSJCs in the development cohort, which were further used to establish a nomogram model. To verify the accuracy of the model, the concordance index (C-index), receiver operating characteristic (ROC) curves, calibration curves, and an internal validation cohort have been employed. Decision curve analysis (DCA) was used to assess the clinical applicability and benefits of the generated model. Survival curves of the low- and high-risk groups were calculated using the Kaplan-Meier method together with the log-rank test.

RESULTS

Age, marital, chemotherapy, AJCC stage, T and N stage of TNM system, tumor size, and regional lymph nodes were selected as independent risk factors and included in the nomogram model. The C-index of this nomogram in the development (0.751;0.737-0.765) and validation cohorts (0.750;0.764-0.736) were more significant than that of the AJCC 7th staging system (0.681; 0.665-0.697). The ROC curve with the calculated area under the curve (AUC) in the development cohort was 0.845,0.808 and 0.800 for 1-year, 3-year and 5-year OS, AUC in the validation cohort was 0.815,0.833 and 0.814 for 1-year, 3-year and 5-year, respectively. The calibration plots of both cohorts for 1-year,3-year and 5-year OS all demonstrated good agreement between actual clinical observations and predicted outcomes. In the development cohort, the DCA showed that the nomogram prediction model is more advantageous for clinical application than the AJCC 7th staging system. Kaplan-Meier curves in the low and high groups showed significant difference in patient OS.

CONCLUSIONS

We established an accurate nomogram model for PLN-RSJCs, intended to support clinicians in the treatment and follow-up of patients.

Patterns of care amongst older adults diagnosed with locally advanced esophageal cancer: A cohort study

INTRODUCTION

Since the early 2010s, neoadjuvant chemoradiation followed by esophagectomy (trimodal therapy) has been a recommended treatment for patients diagnosed with locally advanced esophageal cancer. However, it may also add treatment-related toxicity, particularly for older adults with significant comorbidity and frailty burdens. We examined contemporary patterns of care in older adults, which have not been well characterized.

MATERIALS AND METHODS

We used the Surveillance Epidemiology and End Results-Medicare database to identify a cohort of US adults aged 66 years and older diagnosed with incident locally advanced esophageal cancer between 2004 and 2017. Calendar year age-standardized percentages of treatment receipt were calculated. Joinpoint regression was used to detect temporal trends in treatment receipt. Descriptive associations between patient factors and treatment were assessed. Trend analyses quantified how the percentage of trimodal and definitive chemoradiation (no surgery) patients receiving cisplatin-based, carboplatin-based, and other chemotherapy regimens evolved over time.

RESULTS

In total, 4332 adults aged ≥66 years with locally advanced esophageal cancer were included. The age-standardized percentage of patients receiving trimodal therapy increased from 16.7% in 2004 to 26.1% in 2017 (annual percent change = 3.5%; 95% confidence interval [CI], 0.7%-6.4%) in adenocarcinomas and from 7.3% in 2004 to 9.1% in 2017 (annual percent change = 0.4%; 95% CI, -4.1%-5.1%) in squamous cell carcinomas. By 2017, definitive chemoradiation became the most frequently used treatment modality for adenocarcinomas (49.8%; 95% CI, 43.5-56.0) and squamous cell carcinomas (59.5%; 95% CI, 50.8-68.2). Patients with higher comorbidity and frailty burdens were less likely to be treated with trimodal therapy. Amongst patients receiving chemoradiation as part of their treatment, a large and swift channeling away from cisplatin and towards carboplatin-based regimens was observed.

DISCUSSION

In practice, definitive chemoradiation is the most commonly received treatment by older adults with locally advanced esophageal cancer. Four out of five older adults do not receive trimodal therapy, some of whom are potentially undertreated.

Survival analysis of small cell carcinomas of the genitourinary system

Due to low incidence, there are no large prospective studies or clinical trials for small cell carcinoma (SCC) of the genitourinary system (GU), and most data are extrapolated from SCC of the lung. Using the SEER database, we analyzed incidence trends, overall survival, and cancer-specific survival using the log-rank test. Analysis of variables was performed using the Cox proportional hazards regression model. The analysis showed that SCC of the bladder and prostate were the most common types of GU SCC, with 1836 and 606 cases, respectively. In 2018, the incidence of SCC of the bladder and prostate was twice that of 2010 (P < 0.001). The overall survival and cancer-specific survival of patients with SCC of the bladder were significantly longer than those of patients with SCC of the prostate (P < 0.0001). SCC bladder patients with advanced age, more extensive growth, lymph node involvement, no surgical intervention, and the presence of the metastasis had worse survival outcomes (P < 0.05). The Asian/Pacific Islander race provided some survival benefits for patients with SCC of the bladder (P < 0.05). For patients with SCC of the prostate, only advanced age was a risk factor for poor outcomes (P < 0.05).

Risk Factors for Colorectal Adenocarcinoma in an Indigenous Population in East Africa

Introduction

The incidence of colorectal cancer (CRC) is increasing in East Africa. Changes in lifestyle and dietary changes, particularly alcohol consumption, smoking, and consumption of cooked meats with a reduction in fibre in the diet may be responsible. The objective of our study was to determine the risk factors responsible for CRC in Uganda.

Methods

We recruited 129 participants with histologically proven colorectal adenocarcinoma and 258 control participants from four specialized hospitals in central Uganda from 2019 to 2021. Controls were block matched for age (±5 years) and sex of the case participants. The risk factor variables included; area of residence, tribe, body mass index (BMI), smoking, alcohol consumption and family history of gastrointestinal cancer. We used conditional or ordinal logistic regression to obtain crude and adjusted odds ratios for risk factors associated with CRC.

Results

In bivariate analysis, case participants were more likely to be associated with urban residence (cOR:62.11; p<0.001); family history of GI cancer (cOR: 14.34; p=0.001); past smokers (cOR: 2.10; p=0.080); past alcohol drinkers (cOR: 2.35; p=0.012); current alcohol drinkers (cOR: 3.55; p<0.001); high BMI 25–29.9 kg/m² (cOR: 2.49; p<0.001); and high BMI ≥30kg/m² (cOR: 2.37; p=0.012). In the multivariate analysis, urban residence (aOR: 82.79; p<0.001), family history of GI cancer (aOR: 61.09; p<0.001) and past smoking (aOR: 4.73; p=0.036) were independently associated with a higher risk of developing CRC.

Conclusion

A family history of gastrointestinal cancer was a risk factor for CRC. While population-based CRC screening may not be feasible in low income-countries, targeted CRC screening for first-degree relatives with CRC should be considered in East Africa. Molecular genetic studies need to be carried out to determine the role of hereditary factors in our population. Prevention strategies should be adopted to avoid smoking in our population which was associated with an increased risk of CRC.

Conformal Prediction in Clinical Medical Sciences

The use of machine learning (ML) and artificial intelligence (AI) applications in medicine has attracted a great deal of attention in the medical literature, but little is known about how to use Conformal Predictions (CP) to assess the accuracy of individual predictions in clinical applications. We performed a comprehensive search in SCOPUS® to find papers reporting the use of CP in clinical applications. We identified 14 papers reporting the use of CP for clinical applications, and we briefly describe the methods and results reported in these papers. The literature reviewed shows that CP methods can be used in clinical applications to provide important insight into the accuracy of individual predictions. Unfortunately, the review also shows that most of the studies have been performed in isolation, without input from practicing clinicians, not providing comparisons among different approaches and not considering important socio-technical considerations leading to clinical adoption.

Oncological liver resection in elderly - A retrospective comparative study

BACKGROUND

Due to demographic changes and higher life expectancy especially in industrial nations, the number of liver resections in patients ≥70 years is rising. It is known that older age is associated with higher postoperative morbidity and mortality after surgery under general anesthesia. The aim of this analysis is to compare the postoperative outcome after liver resections for malignancies in patients aged below and above 70 years.

MATERIALS AND METHODS

A prospectively collected electronic database of 1034 liver resections between 01/2013 and 12/2019 was retrospectively analyzed. Comparative analysis of patients <70 and ≥ 70 years receiving liver resections for malignancies included 889 operations in 703 patients. Analysis of postoperative outcome and uni- and multivariate analyses of associated risk factors were performed.

RESULTS

Median age of the whole cohort was 65 years (range 18-87 years). N = 582 liver resections (65.7%) were performed in patients <70 years with 42.8% major hepatectomies and n = 307 (34.3%) liver resections in patients ≥70 years with 50.5% major hepatectomies (p = 0.034). Relevant postoperative morbidity of the whole cohort was 27.9%. The 30-day mortality was 3.9% and re-operation rate 14.8%. Patients ≥70 years had significantly higher postoperative morbidity and mortality rates than patients <70 years. Major resections, longer operating time, need of intraoperative transfusions of blood products as well as biliodigestive anastomosis (BDA) and inferior vena cava (IVC) resection were independent risk factors for worse postoperative outcome.

CONCLUSION

Liver resections in patients ≥70 years are associated with a worse postoperative course after. Parenchyma sparing resections should be preferred in those patients.

Distant Metastasis Pattern and Prognostic Prediction Model of Colorectal Cancer Patients Based on Big Data Mining

Aims

This study aimed to investigate the distant metastasis pattern from newly diagnosed colorectal cancer (CRC) and also construct and validate a prognostic nomogram to predict both overall survival (OS) and cancer-specific survival (CSS) of CRC patients with distant metastases.

Methods

Primary CRC patients who were initially diagnosed from 2010 to 2016 in the SEER database were included in the analysis. The independent risk factors affecting the OS, CSS, all-cause mortality, and CRC-specific mortality of the patients were screened by the Cox regression and Fine-Gray competitive risk model. The nomogram models were constructed to predict the OS and CSS of the patients. The reliability and accuracy of the prediction model were evaluated by consistency index (C-index) and calibration curve. The gene chip GSE41258 was downloaded from the GEO database, and differentially expressed genes (DEGs) were screened by the GEO2R online tool (p < 0.05, |logFC|>1.5). The Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway and Gene Ontology (GO) annotation and String website were used for enrichment analysis and protein-protein interaction (PPI) analysis of DEGs, respectively, and Cytoscape software was used to construct PPI network and screen function modules and hub genes.

Results

A total of 57,835 CRC patients, including 47,823 without distant metastases and 10,012 (17.31%) with metastases, were identified. Older age, unmarried status, poorly differentiated or undifferentiated grade, right colon site, larger tumor size, N2 stage, more metastatic sites, and elevated carcinoembryonic antigen (CEA) might lead to poorer prognosis (all p < 0.01). The independent risk factors of OS and CSS were included to construct a prognosis prediction model for predicting OS and CSS in CRC patients with distant metastasis. C-index and calibration curve of the training group and validation group showed that the models had acceptable predictive performance and high calibration degree. Furthermore, by comparing CRC tissues with and without liver metastasis, 158 DEGs and top 10 hub genes were screened. Hub genes were mainly concentrated in liver function and coagulation function.

Conclusion

The big data in the public database were counted and transformed into a prognostic evaluation tool that could be applied to the clinic, which has certain clinical significance for the formulation of the treatment plan and prognostic evaluation of CRC patients with distant metastasis.

Variations in Care and Real World Outcomes in those with Rectal Cancer: A protocol for the Ontario Rectal Cancer Cohort (OntaReCC) (Preprint)

Background

Individuals with rectal cancer require a number of pretreatment investigations, often require multidisciplinary treatment, and require ongoing follow-ups after treatment is completed. Due to the complexity of treatments, large variations in practice patterns and outcomes have been identified. At present, few comprehensive, population-level data sets are available for assessing interventions and outcomes in this group.

Objective

Our study aims to create a comprehensive database of individuals with rectal cancer who have been treated in a single-payer, universal health care system. This database will provide an excellent resource that investigators can use to study variations in the delivery of care to and real-world outcomes of this population.

Methods

The Ontario Rectal Cancer Cohort database will include comprehensive details about the management and outcomes of individuals with rectal cancer who have been diagnosed in Ontario, Canada (population: 14.6 million), between 2010 and 2019. Linked administrative data sets will be used to construct this comprehensive database. Individual and care provider characteristics, investigations, treatments, follow-ups, and outcomes will be derived and linked. Surgical pathology details, including the stage of disease, histopathology characteristics, and the quality of surgical excision, will be included. Ethics approval for this study was obtained through the Queen’s University Health Sciences and Affiliated Teaching Hospitals Research Ethics Board.

Results

Approximately 20,000 individuals who meet the inclusion criteria for this study have been identified. Data analysis is ongoing, with an expected completion date of March 2023. This study was funded through the Canadian Institute of Health Research Operating Grant.

Conclusions

The Ontario Rectal Cancer Cohort will include a comprehensive data set of individuals with rectal cancer who received care within a single-payer, universal health care system. This cohort will be used to determine factors associated with regional variability and adherence to recommended care, and it will allow for an assessment of a number of understudied areas within the delivery of rectal cancer treatment.

International Registered Report Identifier (IRRID)

RR1-10.2196/38874

Establishment of a Competing Risk Nomogram in Patients with Pulmonary Sarcomatoid Carcinoma

Background and aim: Pulmonary sarcomatoid carcinoma (PSC) is a rare subtype of nonsmall cell lung cancer with a poor prognosis. This study aimed to analyze the clinicopathological characteristics and survival outcomes among patients with PSC, lung squamous cell cancer (SCC), and lung adenocarcinoma (LAC), and to construct a competing risk nomogram for patients with PSC. Method: Data of 3 groups of patients diagnosed with PSC, SCC, or LAC from the surveillance, epidemiology, and end results (SEER) database between 1988 and 2015 were retrospectively reviewed. A 1:1 propensity score matching (PSM) analysis was used to balance the baseline data of patients. Independent risk factors associated with survival outcomes were screened by the least absolute shrinkage and selection operator and further determined by univariate and multivariate Cox proportional risk regression analyses. The overall survival (OS) of patients was evaluated by Kaplan–Meier analysis and compared with a log-rank test. The cumulative incidence function was used to estimate the 5-year probabilities of the cancer-specific mortality of PSC. A nomogram was constructed to illustrate the competing risk model to predict the 3- and 5-year OS, and corresponding concordance indexes (C-indexes) and calibration curves were used to assess and validate the competing risk nomogram. Results: A total of 2285 patients with PSC were included in this study. Compared with SCC and LAC patients, the Kaplan–Meier analysis showed that patients with PSC had a worse prognosis, with a median survival of 5 months (95% confidence interval [CI]: 5-6 months) and a 5-year OS rate of 15.3% (95% CI: 13.9%-16.9%). Similar outcomes were demonstrated after 1:1 PSM. Moreover, the competing risk model showed that age, T stage, M stage, tumor size, lymph node ratio (LNR), surgery, and chemotherapy were associated with PSC-specific mortality. The 5-year C-index of the nomogram was 0.718. Calibration curves illustrated that the nomogram was well-validated and had great accuracy. Conclusions: Patients with PSC had a worse survival outcome compared with SCC or LAC patients. Age, T stage, M stage, tumor size, LNR, surgery, and chemotherapy were associated with PSC-specific mortality. The competing risk nomogram displayed excellent discrimination in predicting PSC-specific mortality.

The Value of Serum miR-139-3p Expression Level in Predicting Postoperative Survival of Colon Cancer Patients

Background

To explore the value of serum miR-139-3p expression level in predicting postoperative survival of colon cancer patients.

Methods

We selected 158 cases enrolled in our hospital from January 2017 to December 2019. Using real-time fluorescence quantitative PCR, the expression extents of serum miR-139-3p among patients suffering from colon cancer were detected. The enrollment of patients was performed in the high or low miR-139-3p group on the basis of the cutoff value determined by ROC curve analysis. The risk elements influencing the postoperative survival of colon cancer patients were analyzed by the Kaplan–Meier approach and univariate and multivariate Cox regression models.

Results

Compared with control group, significantly lower expression level of serum miR-139-3p was shown in colon cancer group (P < 0.05). Its low expression of miR-139-3p was associated with TNM stage, degree of differentiation, tumor sizes, lymph node metastasis and vascular infiltration in patients with colon cancer (all P < 0.05), which was also significantly associated with short survival time of colon cancer patients (P < 0.05). Multivariate Cox regression model analysis displayed that TNM phase, lymph node metastasis and miR-139-3p <2.17 were independent risk elements affecting postoperative survival (P < 0.05).

Conclusion

The low expression level of miR-139-3p is related to the short survival time of colon cancer patients, and it is expected to be used as a biological indicator to predict the postoperative survival of colon cancer.

Application of artificial intelligence in a real-world research for predicting the risk of liver metastasis in T1 colorectal cancer

Background

Liver is the most common metastatic site of colorectal cancer (CRC) and liver metastasis (LM) determines subsequent treatment as well as prognosis of patients, especially in T1 patients. T1 CRC patients with LM are recommended to adopt surgery and systematic treatments rather than endoscopic therapy alone. Nevertheless, there is still no effective model to predict the risk of LM in T1 CRC patients. Hence, we aim to construct an accurate predictive model and an easy-to-use tool clinically.

Methods

We integrated two independent CRC cohorts from Surveillance Epidemiology and End Results database (SEER, training dataset) and Xijing hospital (testing dataset). Artificial intelligence (AI) and machine learning (ML) methods were adopted to establish the predictive model.

Results

A total of 16,785 and 326 T1 CRC patients from SEER database and Xijing hospital were incorporated respectively into the study. Every single ML model demonstrated great predictive capability, with an area under the curve (AUC) close to 0.95 and a stacking bagging model displaying the best performance (AUC = 0.9631). Expectedly, the stacking model exhibited a favorable discriminative ability and precisely screened out all eight LM cases from 326 T1 patients in the outer validation cohort. In the subgroup analysis, the stacking model also demonstrated a splendid predictive ability for patients with tumor size ranging from one to50mm (AUC = 0.956).

Conclusion

We successfully established an innovative and convenient AI model for predicting LM in T1 CRC patients, which was further verified in the external dataset. Ultimately, we designed a novel and easy-to-use decision tree, which only incorporated four fundamental parameters and could be successfully applied in clinical practice.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02424-7.

Socioeconomic Determinants of the Use of Molecular Testing in Stage IV Colorectal Cancer

OBJECTIVES

Treatment with epidermal growth factor receptor monoclonal antibodies extends life for patients with advanced colorectal cancers (CRCs) whose tumors exhibit wild-type KRAS, but KRAS testing may be underused. We studied the role of socioeconomic factors in the application of KRAS testing.

MATERIALS AND METHODS

We identified subjects with stage IV colorectal adenocarcinoma diagnosed 2010-2015 in the Surveillance, Epidemiology, and End Results (SEER) database. We used multivariable logistic regression models to evaluate associations between clinical/demographic factors and the rate of KRAS testing. We used multivariable-adjusted Cox proportional hazards models to assess survival.

RESULTS

We identified 37,676 patients with stage IV CRC, 31.1% of whom were tested for KRAS mutations, of those who had documented KRAS testing, 44% were KRAS mutant. Patients were more likely to be tested if they were younger (odds ratio [OR]=5.10 for age 20 to 29 vs. 80+, 95% confidence interval [CI]: 3.99-6.54, P<0.01), diagnosed more recently (OR=1.92 for 2015 vs. 2010, 95% CI: 1.77-2.08, P<0.01), or lived in an area of high median household income (OR=1.24 for median household income of >$69,311 vs. <$49,265, 95% CI: 1.14-1.35, P<0.01). Patients were less likely to be tested if they had Medicaid (OR=0.83, 95% CI: 0.77-0.88, P<0.01) or were unmarried (OR=0.78, 95% CI: 0.75-0.82, P<0.0001). The risk of death was decreased in patients who received KRAS testing (hazard ratio=0.77, 95% CI: 0.75-0.80, P<0.01).

CONCLUSIONS

We found a low rate of KRAS testing in CRC patients with those living in low-income areas less likely to be tested, even after controlling for Medicaid insurance. Our study suggests that socioeconomic disparities persist despite Medicaid insurance.

Long-term cost of breast cancer treatment to the United States Medicare Program by stage at diagnosis

INTRODUCTION

Breast cancer treatment includes increasingly complex and expensive treatments. Accordingly, the current estimates of the cost of breast cancer treatment are out of date.

METHODS

The SEER-Medicare Data Link provided 142,837,978 paid Medicare claims from 398,148 female beneficiaries between the ages of 22 and 110 diagnosed with breast cancer between 2007 and 2016. These claims were compared with 153,071,044 claims from 443,952 Medicare beneficiaries without a cancer diagnosis. The total, fully adjudicated, amounts for each claim were summed to determine total treatment cost for each beneficiary. These costs were then aggregated by year after diagnosis and stage at diagnosis. The actuarial survival of beneficiaries with cancer was calculated using the Kaplan-Meier method.

RESULTS

Mean costs for the control group were $8,019 per year. The 10-year cost of cancer treatment in Medicare beneficiaries was directly related to stage at diagnosis and ranged from $103,573 for stage 0 cancers to $376,573 for stage 4 cancers. The highest cost occurred during the first 2 years after diagnosis, the time of the beneficiary's initial treatment. Following the first 2 years, healthcare costs remained elevated for at least 10 years after diagnosis.

CONCLUSIONS

The 10-year treatment cost of female Medicare beneficiaries with breast cancer increases with increasing stage at diagnosis. Any effective screening technology that reduces stage at diagnosis will result in significant treatment cost savings to the Medicare program.

Pathological complete response to pembrolizumab in patients with metastatic ascending colon cancer with microsatellite instability

Pembrolizumab is a novel immune-checkpoint inhibitor used for treatment of microsatellite instability-high (MSI-H) colorectal cancer. Several studies have reported clinical complete response (CR) after treatment with pembrolizumab, but none has confirmed pathological CR. Here we provide the first description of pathological CR with R0 resection after immune-checkpoint therapy. A 45-year-old man presented at our hospital with abdominal distention and highly elevated tumor markers. Contrast-enhanced abdominal CT showed a 110 × 75 mm bulky mass with markedly swollen lymph nodes and an isolated peritoneal metastasis in the pelvic space. Biopsy revealed poorly differentiated adenocarcinoma. We diagnosed ascending colon cancer cT4aN2bM1c Stage IVc. A biopsy specimen obtained during systemic chemotherapy (FOLFOXIRI) was confirmed pathologically as MSI-H, after which the treatment was changed to pembrolizumab. The tumor markers rapidly decreased to within normal ranges after three courses of treatment. After twenty courses, CT revealed shrinkage of the main tumor, lymph node metastases, and the peritoneal metastasis, and we performed extended right hemi-colectomy with dissection of the peritoneal metastasis. No residual tumor cells were found histologically. The patient achieved pathological CR and the postoperative course was uneventful. An accurate diagnosis and appropriate follow up are crucial for obtaining sufficient therapeutic effect of pembrolizumab.

Colorectal cancer databases and registries in Australia: what data is available?

BACKGROUND

There are multiple data sources relating to colorectal cancer (CRC) nationwide. Prospective clinical cancer databases, population-based registries and linked administrative data are powerful tools in clinical outcomes research and provide real-world perspective on cancer treatments. This study aims to review the different Australian data sources for CRC from the perspective of conducting comparative research studies using a PICO (patient, intervention, comparison, outcome) framework.

METHODS

Data dictionaries from the different data sources were evaluated for the types of exposure and outcome variables contained to highlight their differing research utility.

RESULTS

State or territory-based cancer registries contain limited histology, cancer staging and treatment detail. They enable investigation of population-level patterns in overall survival (OS) of cancer patients with different demographics. Prospective clinical cancer databases contain more detail, especially surgical. Their strength is in auditing short-term surgical outcomes. They vary in the amount of data collected for other cancer treatments and completion of follow up data. Linked administrative databases have broad population coverage but less surgical detail. They provide population-level data on treatment patterns, short-term outcome measures and OS, as well as long-term surgical outcomes such as identifying patients who did not undergo stoma reversal. These databases cannot assess disease-free survival.

CONCLUSION

Of the various CRC data sources within Australia, linked administrative databases have the potential to provide the widest population coverage combined with the broadest range of exposures and outcomes, and arguably the most research utility.

Comparison Between Decitabine and Azacitidine for Patients With Acute Myeloid Leukemia and Higher-Risk Myelodysplastic Syndrome: A Systematic Review and Network Meta-Analysis

Background: The hypomethylating agents (HMAs) azacitidine (AZA) and decitabine (DAC) have been widely used in patients with acute myeloid leukemia (AML) and higher-risk myelodysplastic syndrome (HR-MDS). However, few direct clinical trials have been carried out to compare the efficacy and adverse events (AEs) between these two agents. The clinical choice between them is controversial. A systematic review and network meta-analysis (NMA) was performed to compare the efficacy, safety, and survival of DAC and AZA in AML and HR-MDS patients.

Methods: We systematically searched MEDLINE, Embase, Web of Science, and Cochrane Library through March 15, 2021. Randomized controlled trials (RCTs) on AML or HR-MDS patients comparing the efficacy and safety between DAC and AZA or comparing one of HMAs to conventional care regimens (CCR) were selected.

Results: Eight RCTs (n = 2,184) were identified in the NMA. Four trials compared AZA to CCR, and four compared DAC to CCR. Direct comparisons indicated that, compared to CCR, both AZA and DAC were associated with higher overall response (OR) rate (AZA vs. CCR: relative risk (RR) = 1.48, 95% CI 1.05–2.1; DAC vs. CCR: RR = 2.14, 95% CI 1.21–3.79) and longer overall survival (OS) (AZA vs. CCR: HR = 0.64, 95% CI 0.50–0.82; DAC vs. CCR: HR = 0.84, 95% CI 0.72–0.98), and AZA showed higher rate of complete remission with incomplete blood count recovery (CRi) (HR = 2.52, 95% CI 1.27–5). For the indirect method, DAC showed a higher complete remission (CR) rate than AZA in patients with both AML (RR = 2.28, 95% CI 1.12–4.65) and MDS (RR = 7.57, 95% CI 1.26–45.54). Additionally, DAC significantly increased the risk of 3/4 grade anemia (RR = 1.61, 95% CI: 1.03–2.51), febrile neutropenia (RR = 4.03, 95% CI: 1.41–11.52), and leukopenia (RR = 3.43, 95% CI 1.64–7.16) compared with AZA. No statistical significance was found for the other studied outcomes.

Conclusion: Compared to CCR, both AZA and DAC can promote outcomes in patients with AML and HR-MDS. DAC showed higher efficacy especially CR rate than AZA (low-certainty evidence), while AZA experienced lower frequent grade 3/4 cytopenia than patients receiving DAC treatment.

Microbiome Metabolites and Thyroid Dysfunction

Thyroid diseases are common conditions that have a negative impact on the health of all populations. The literature sheds light on the differences in the composition of the intestinal microbiota in patients suffering from thyroid diseases compared to healthy individuals. The microbiome affects the proper functioning of the thyroid gland, and the existence of the gut–thyroid axis is discussed in the context of both thyroid diseases and intestinal dysbiosis. The purpose of this review is to describe associations between the microbiome and its metabolites and thyroid dysfunction. We try to explain the role of the microbiome in the metabolism of thyroid hormones and the impact of thyroid autoimmune diseases. In addition, we raise issues related to the influence of bacterial metabolites, such as short-chain fatty acids or secondary bile acids, in the functioning of the thyroid gland. Last but not least, we explored the interactions between the gut microbiota and therapeutics and supplements typically administered to patients with thyroid diseases.

Adenosquamous Carcinoma of the Cervix: A Population-Based Analysis

Background

Due to the rarity of adenosquamous carcinoma of the cervix (ASCC), studies on the incidence, prognostic factors, and treatment outcomes of ASCC remain scarce. Therefore, we performed a retrospective population-based study to systematically investigate the characteristics of ASCC patients.

Methods

Patients with a histopathologically confirmed diagnosis of ASCC were enrolled from the Surveillance, Epidemiology, and End Results database between 1975 and 2016. Univariate and multivariate Cox regression analyses were performed to identify the potential predictors of cancer-specific survival (CSS) in patients with ASCC. Selected variables were integrated to establish a predictive nomogram and the predictive performance of the nomogram was estimated using Harrell’s concordance index (C-index), calibration curve, and decision curve analysis (DCA).

Results

A total of 1142 ASCC patients were identified and included in this study and were further randomized into the training and validation cohorts in a 7:3 ratio. The age-adjusted incidence of ASCC declined from 0.19 to 0.09 cases per 100,000 person-years between 2000 and 2017, with an annual percentage change of -4.05% (P<0.05). We identified age, tumor grade, FIGO stage, tumor size, and surgical procedure as independent predictors for CSS in ASCC patients and constructed a nomogram to predict the 3- and 5-year CSS using these prognostic factors. The calibration curve indicated an outstanding consistency between the nomogram prediction and actual observation in both the training and testing cohorts. The C-index was 0.7916 (95% CI: 0.7990-0.8042) and 0.8148 (95% CI: 0.7954-0.8342) for the training and testing cohorts, respectively, indicating an excellent discrimination ability of the nomogram. The DCA showed that the nomogram exhibited more clinical benefits than the FIGO staging system.

Conclusions

We established and validated an accurate predictive nomogram for ASCC patients based on several clinical characteristics. This model might serve as a useful tool for clinicians to estimate the prognosis of ASCC patients.

Identification of Potential Biomarkers and Biological Pathways for Poor Clinical Outcome in Mucinous Colorectal Adenocarcinoma

Simple Summary

Patients with mucinous adenocarcinoma (MAC) have been considered to have a faster disease progression than patients with traditional adenocarcinoma (TAC) in colorectal cancer (CRC). However, to date, the roles of MAC in long-term survival remain controversial due to a small sample size and the nature of its relatively rare occurrence, although it potentially represents entities with different aggressiveness and prognoses. Here, using large-scale population data, we found that the patients with the MAC subtype had a significantly worse overall survival rate and a tendency of worse disease-specific survival rate in stage II compared with the patients with the TAC subtype. Furthermore, key gene signatures were identified using the established predictive models for the disease-specific survival of stage II mucinous CRC.

Abstract

Colorectal cancer (CRC) comprises several histological subtypes, but the influences of the histological subtypes on prognosis remains unclear. We sought to evaluate the prognosis of mucinous adenocarcinoma (MAC), compared to that of traditional adenocarcinoma (TAC). This study used the data of patients diagnosed with CRC between 2004 and 2016, as obtained from the Surveillance, Epidemiology, and End Results database. We established a predictive model for disease-specific survival using conditional survival forest, model, non-linear Cox proportional hazards, and neural multi-task logistic regression model and identified the gene signatures for predicting poor prognosis based on the arrayexpress datasets. In total, 9096 (42.1%) patients with MAC and 12,490 (58.9%) patients with TAC were included. Those with the MAC subtype were more likely to have a poorer overall survival rate compared to those with the TAC subtype in stage II CRC (p = 0.002). The eight major genes including RPS18, RPL30, NME2, USP33, GAB2, RPS3A, RPS25, and CEP57 were found in the interacting network pathway. MAC was found to have a poorer prognosis compared to TAC, especially in Stage II CRC. In addition, our findings suggest that identifying potential biomarkers and biological pathways can be useful in CRC prognosis.

Predictors of Lymph Node Metastasis in Siewert Type II T1 Adenocarcinoma of the Esophagogastric Junction: A Population-Based Study

Background:

Endoscopic resection has been introduced as an alternative treatment for superficial adenocarcinoma of the esophagogastric junction (AEG), but is limited by positive nodal status. We aimed to investigate the predictors of lymph node metastasis (LNM) in patients with Siewert type II T1 AEG.

Methods:

The Surveillance, Epidemiology, and End Results (SEER) database was used to identify eligible patients with Siewert type II T1 AEG. The prevalence of LNM was assessed. Logistic regression analysis with multivariable adjustment was used to determine predictors of LNM. We also performed Cox regression analysis to examine the prognostic value of LNM, which was further confirmed by competing risk analysis and cumulative incidence function (CIF).

Results:

In total, 2651 patients with T1 AEG were included, with a median age of 69 years and a median follow-up of 28 months. The overall prevalence of LNM was 17.2% in T1 AEG. When stratified by tumor invasion depth, the prevalence of LNM was 8.5% for intramucosal tumors and 22.6% for submucosal tumors. Adjusted logistic regression analysis showed that age, sex, tumor grade, tumor size and tumor infiltration depth were independent predictors of LNM in T1 AEG. Multivariate Cox regression analysis revealed that positive nodal status was significantly associated with worse overall survival and cancer-specific survival (CSS). Subgroup analysis consistently demonstrated that patients with LNM had significantly poorer CSS than those without LNM in most subgroups. Finally, the CIF was calculated, showing that patients with LNM had a significantly higher cancer-specific death rate than those without LNM.

Conclusions:

This population-based study identified age, sex, tumor grade, tumor infiltration depth and tumor size as independent predictors of LNM in T1 AEG. Considering the high prevalence of LNM in T1 AEG, endoscopic resection for curative aims may only be introduced in patients without high risks of LNM.

Head and neck cancer in Cali, Colombia: Population-based study

INTRODUCTION

Head and neck cancer (HNC) is the seventh most common type of cancer in the world. In Latin America, data on HCN are limited by the scarcity of population-based cancer registries.

OBJECTIVE

To describe survival and changes in the time trends of incidence and mortality rates of HCN with data from the Cali Cancer Population Registry (Colombia) during 1962-2018.

METHOD

Males and females of any age residing in Cali were included. The trends in incidence rates (1962-2016) and mortality (1984-2018) were analysed by calculating the mean annual percentage change (APC). Five-year net survival was estimated for the four 5-year periods of 1996-2015 using the Pohar-Perme method.

RESULTS

During 1962-2015, 5,110 new cases of HNC were recorded: 1,506 in the larynx, 1,377 in the oral cavity, 487 in the nose and paranasal sinuses, 643 in the oropharynx, 603 in the salivary glands and 360 in Naso-Hypopharynx region. The incidence rates of HNC decreased significantly at all subsites, except in those associated with the human papillomavirus. Between 1984 and 2018, there were 1,941 deaths attributed to HNC, and the mortality rate decreased significantly. The 5-year age-standardized net survival was 43.2% in 1996-2000, remained stable during the following decade, and for 2011-2015 it was 50.9%.

CONCLUSION

The incidence and mortality of HNC in Cali decreased significantly during the study period in both sexes.

Development and validation of a nomogram to predict survival outcome among epithelial ovarian cancer patients with site-distant metastases: a population-based study

Background

Increasing evidence indicates that site-distant metastases are associated with survival outcomes in patients with epithelial ovarian cancer. This study aimed to investigate the prognostic values of site-distant metastases and clinical factors and develop a prognostic nomogram score individually predicting overall survival (OS, equivalent to all-cause mortality) and cancer specific survival (CSS, equivalent to cancer-specific mortality) in patients with epithelial ovarian cancer.

Methods

We retrospectively collected data on patients with epithelial ovarian cancer from the Surveillance, Epidemiology, and End Results (SEER) database between 1975 and 2016. Multivariate Cox regression was performed to identify survival trajectories. A nomogram score was used to predict long-term survival probability. A comparison between the nomogram and the International Federation of Gynecology and Obstetrics (FIGO 2018) staging system was conducted using time-dependent receiver operating characteristic (tROC) curve.

Results

A total of 131,050 patients were included, 18.2, 7.8 and 66.1% had localized, regional and distant metastases, respectively. Multivariate analysis identified several prognostic factors for OS including race, grade, histology, FIGO staging, surgery, bone metastasis, liver metastasis, lung metastasis, and lymphatic metastasis. Prognostic factors for CSS included grade, site, FIGO staging, surgery, bone metastasis, brain metastasis, lung metastasis, lymphatic metastasis, and insurance. Following bootstrap correction, the C-index of OS and CSS was 0.791 and 0.752, respectively. These nomograms showed superior performance compared with the FIGO 2018 staging criteria (P < 0.05).

Conclusions

A novel prognostic nomogram score provides better prognostic performance than the FIGO 2018 staging system. These nomograms contribute to directing clinical treatment and prognosis assessment in patients harboring site-distant metastases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-07977-4.

Development of a Novel Prognostic Model for Predicting Lymph Node Metastasis in Early Colorectal Cancer: Analysis Based on the Surveillance, Epidemiology, and End Results Database

Background

Identification of a simplified prediction model for lymph node metastasis (LNM) for patients with early colorectal cancer (CRC) is urgently needed to determine treatment and follow-up strategies. Therefore, in this study, we aimed to develop an accurate predictive model for LNM in early CRC.

Methods

We analyzed data from the 2004-2016 Surveillance Epidemiology and End Results database to develop and validate prediction models for LNM. Seven models, namely, logistic regression, XGBoost, k-nearest neighbors, classification and regression trees model, support vector machines, neural network, and random forest (RF) models, were used.

Results

A total of 26,733 patients with a diagnosis of early CRC (T1) were analyzed. The models included 8 independent prognostic variables; age at diagnosis, sex, race, primary site, histologic type, tumor grade, and, tumor size. LNM was significantly more frequent in patients with larger tumors, women, younger patients, and patients with more poorly differentiated tumor. The RF model showed the best predictive performance in comparison to the other method, achieving an accuracy of 96.0%, a sensitivity of 99.7%, a specificity of 92.9%, and an area under the curve of 0.991. Tumor size is the most important features in predicting LNM in early CRC.

Conclusion

We established a simplified reproducible predictive model for LNM in early CRC that could be used to guide treatment decisions. These findings warrant further confirmation in large prospective clinical trials.

Application of smart solid lipid nanoparticles to enhance the efficacy of 5-fluorouracil in the treatment of colorectal cancer

5-Fluorouracil (5-FU) is a standard treatment option for colorectal cancer (CRC) but its rapid metabolism and systemic instability (short half-life) has hindered its therapeutic efficacy. The objective of this study was to develop a novel drug delivery system, solid lipid nanoparticle (SLN), capable of delivering high payload of 5-FU to treat CRC. The rational was to improve 5FU-nanocarrier compatibility and therapeutic efficacy. The SLN-loaded 5-FU was developed by utilizing a Strategic and unique Method to Advance and Refine the Treatment (SMART) of CRC through hot and cold homogenization approach. The SLN was made of unique PEGylated lipids and combination of the surfactants. Cytotoxicity studies, clonogenic assay, flow cytometry and confocal imaging were conducted to evaluate the effectiveness and cellular uptake of 5FU-SLN4 in HCT-116 cancer cells. Pharmacokinetic (PK) parameters and receptor expressions were determined while tumor efficacy studies were conducted on mouse bearing subcutaneous HCT-116 cancer. Among the all the formulations, 5FU-SLN4 was the most effective with particle size of was 263 ± 3 nm, zeta potential was 0.1 ± 0.02 and entrapment efficiency of 81 ± 10%. The IC50 value of 5FU-SLN4 (7.4 ± 0.02 µM) was 2.3 fold low compared with 5-FU (17.7 ± 0.03 µM). For tumor efficacy studies, 5FU-SLN4 significantly inhibited tumor growth in comparison to 5-FU while area-under plasma concentration-time curve (AUC) of 5FU-SLN4 was 3.6 fold high compared with 5-FU. HER2 receptors expression were markedly reduced in 5-FU-SLN4 treated mice compared with 5FU and liver and kidney tissues showed no toxicity at dose of 20 mg/kg. 5FU-SLN4 was highly cytotoxic against HCT-116 cells and significantly inhibited subcutaneous tumor growth in mice compared with 5-FU. This emphasizes the significance of developing a smart nano-delivery system to optimize the delivery efficiency of anticancer drugs to tumors.

Indirect comparison of azacitidine and decitabine for the therapy of elderly patients with acute myeloid leukemia: a systematic review and network meta-analysis

Background

The DNA hypomethylating agents (HMAs) decitabine and azacitidine have been widely used in the management of elderly patients with acute myeloid leukemia (AML). However, no direct clinical trials have been carried out to compare the two agents. A systematic review and network meta-analysis were performed to indirectly compare the efficacy and safety of decitabine and azacitidine in elderly AML patients.

Methods

We systematically searched PubMed, Medline, Web of Science, Embase and Cochrane Library through May 14, 2019. Randomized controlled trials on elderly AML patients comparing the efficacy and safety between decitabine and azacitidine, or comparing one of HMAs to standard supportive care or placebo were selected. The major outcomes of interest were performed with methods of adjusted indirect comparison and the fixed effect model.

Results

Only three RCTs including a total number of 1086 patients were identified. Direct comparisons showed that azacitidine significantly reduced mortality (RR = 0.90, 95% CI 0.83–0.97) while decitabine was not significantly associated with lower mortality (RR = 0.97, 95% CI 0.92–1.02) compared to the conventional care regimen (CCR). In addition, for the indirect method, azacitidine significantly reduced mortality compared to decitabine (RR = 0.83 95% CI 0.77–0.90) and was more likely to improve complete response (CR) (RR = 1.66, 95% CI 1.17–2.35, low-certainty evidence). No statistical significance was found for the other studied outcomes.

Conclusions

Compared to CCR, decitabine and azacitidine can promote studied outcomes in elderly AML patients. Indirect evidence with low certainty was used to compare these two agents. The superiority of either agent cannot be confirmed, and head-to-head clinical trials are still required.

Marital Status and Survival in Osteosarcoma Patients: An Analysis of the Surveillance, Epidemiology, and End Results (SEER) Database

Background

As the most malignant bone tumor globally, osteosarcoma has drawn increased attention. However, no studies have focused on the association between marital status and survival rate. The objectives of this study were to determine the association between marital and survival rate of osteosarcoma patients based on the SEER database.

Material/Methods

We enrolled a total of 2725 osteosarcoma patients between 1973 and 2015, including 1184 married, 154 divorced/separated, 136 widowed, and 1251 never-married patients. Survival rate was determined based on the Kaplan-Meier method in different marital subgroups. Multivariate Cox regression analysis was performed to explore independent prognostic factors.

Results

The 5-year overall survival (OS) and cancer-specific survival (CSS) rates of the married, separated/divorced, widowed, and never-married subjects were 45.93%, 41.39%, 19.08%, and 57.21% (OS), and 49.97%, 45.85%, 22.14%, and 60.69% (CSS), respectively. The survival outcome among subgroups exhibited a clear difference, with a log-rank test p-value <0.0001. Multivariate Cox regression showed that widowhood served as the independent prognostic factor for decreased OS rather than marriage (HR, 1.246; 95% CI, 1.011–1.536; p-value=0.039) and CSS (HR, 1.34; 95% CI, 1.07–1.68; p-value=0.01). Moreover, the OS and CSS in widowed patients were lower. Additionally, based on the propensity score matching (PSM) method, the prognosis of married patients was better than that of unmarried subjects.

Conclusions

Marital status was correlated with the survival rate, meaning that married patients had higher survival than widowed subjects, who had worse prognoses of osteosarcoma.

Development and implementation of a dynamically updated big data intelligence platform from electronic health records for nasopharyngeal carcinoma research

OBJECTIVE

To develop a big data intelligence platform for secondary use of electronic health records (EHRs) data to facilitate research for nasopharyngeal cancer (NPC).

METHODS

This project was launched in 2015 and carried out by the cooperation of an academic cancer centre and a technology company. Patients diagnosed with NPC at Sun Yat-sen University Cancer Centre since January 2008 were included in the platform. Standard data elements were established to defined 981 variables for the platform. For each patient, data from 13 EHRs systems were extracted, integrated, structurized and normalized. Eight functional modules were constructed for the platform to facilitate the investigators to identify eligible patients, establish research projects, conduct statistical analysis, track the follow-up, search literature, etc.

RESULTS

From January 2008 to December 2018, 54,703 patients diagnosed with NPC were included. Of these patients, 39,058 (71.4%) were male, and 15,645 (28.6%) were female; median age was 47 (interquartile range, 39-55) years. Of 981 variables, 341 were obtained from data structurization and normalization, of which 68 were generated by interacting multiple data sources via well-defined logical rules. The average precision rate, recall rate and F-measure for 341 variables were 0.97 ± 0.024, 0.92 ± 0.030, and 0.94 ± 0.027 respectively. The platform is regularly updated every seven days to include new patients and add new data for existing patients. Up to now, eight big data-driven retrospective studies have been published from the platform.

CONCLUSION

Our big data intelligence platform demonstrates the feasibility of integrating EHRs data of routine healthcare, and offers an important perspective on real-world study of NPC. The continued efforts may be focus on data sharing among multiple hospitals and publicly releasing of data files.

ADVANCES IN KNOWLEDGE

Our big data intelligence platform is the first disease-specific data platform for NPC research. It incorporates comprehensive EHRs data from routine healthcare, which can facilitate real-world study of NPC in risk stratification, decision-making and comorbidities management.