A New Metastatic Lymph Node Classification-based Survival Predicting Model in Patients With Small Bowel Adenocarcinoma: A Derivation and Validation Study

Pancreas preserving duodenectomy (PPrD)

BACKGROUND

Pancreaticoduodenectomy has been the standard of care for managing duodenal neoplasms, but recent studies show similar overall and disease-specific survival after pancreas-preserving duodenectomy (PPrD) with potentially less morbidity.

METHODS

Retrospective cohort of all adult (age >18) patients who underwent PPrD with curative intent of a neoplasm in or invading into the duodenum at our institution from 2011 to 2022 (n ​= ​29), excluding tumors involving the Ampulla of Vater or the pancreas. Statistical analyses were performed using STATA.

RESULTS

R0 resection was achieved in 93 ​% patients. Ten (34.4 ​%) experienced postoperative complications (13.7 ​% within Clavien-Dindo III-V). PPrD patients had lower rates of pancreatic leak, delayed gastric emptying, and deep surgical site infection.

CONCLUSIONS

In this case series, we demonstrate PPrD is safe and effective, with a high rate of complete resection and lower complication rate than that seen in pancreaticoduodenectomy.

Clinical characteristics and prognosis of patients with primary squamous cell carcinoma of the retromolar trigone: A SEER-based analysis

BACKGROUND

Primary squamous cell carcinoma of the retromolar trigone (primary SCC RMT) is an uncommon malignant tumor. There is still much to learn about its clinicopathological characteristics and prognosis. In order to better understand the clinicopathological features and predictive survival aspects of primary SCC RMT, this study examined data from the SEER database from 2000 to 2020. Furthermore, in order to forecast the overall survival (OS) and cancer-specific survival (CSS) of patients with primary SCC RMT, we created nomograms.

METHOD

The Surveillance, Epidemiology and End Results (SEER) database was used to retrieve the information on individuals with primary SCC RMT who received a diagnosis between 2000 and 2020. Both univariate and multivariate analyses were conducted using the Cox proportional risk regression model. Using R software, prognostic nomograms were created to forecast the OS and CSS likelihood. The nomograms' prediction abilities were evaluated using the consistency index (C-index), calibration curve, and receiver operating characteristic (ROC) curve.

RESULT

A total of 1717 patients with primary SCC RMT were included, they were randomly assigned to the primary and validation cohorts in a 7:3 ratio using R software. Multivariate Cox regression revealed that age, marital status, regional nodes positive, Summary stage, TNM stage, T stage, N stage, surgery were independent prognostic factors of OS, and age, marital status, regional nodes positive, tumor sizes, Summary stage, N stage, surgery were independent prognostic factors of CSS in the primary cohort. The C-index of the nomogram OS was 0.705 (95 % CI: 0.685-0.725) and the C-index of CSS was 0.734 (95 % CI:0.714-0.754) in the primary cohort. In validation cohort, the C-index of the nomogram OS and CSS were 0.730 (95 % CI: 0.710-0.750) and 0.723 (95 % CI: 0.684-0.762), respectively. The 1-, 3-, and 5-year OS and CSS rates in the primary cohort and validation cohort were approximately in line with the nomogram estimations, in accordance to the calibration curves.

CONCLUSION

We conducted an analysis using the SEER database to investigate the features, survival outcomes, and prognostic parameters of patients with primary SCC RMT. And we developed two prognostic nomograms that can be used by clinicians to forecast the 1-, 3-, and 5-year overall survival and cancer-specific survival of patients with primary SCC RMT.

Machine learning-based analysis of cancer cell-derived vesicular proteins revealed significant tumor-specificity and predictive potential of extracellular vesicles for cell invasion and proliferation - A meta-analysis

BACKGROUND

Although interest in the role of extracellular vesicles (EV) in oncology is growing, not all potential aspects have been investigated. In this meta-analysis, data regarding (i) the EV proteome and (ii) the invasion and proliferation capacity of the NCI-60 tumor cell lines (60 cell lines from nine different tumor types) were analyzed using machine learning methods.

METHODS

On the basis of the entire proteome or the proteins shared by all EV samples, 60 cell lines were classified into the nine tumor types using multiple logistic regression. Then, utilizing the Least Absolute Shrinkage and Selection Operator, we constructed a discriminative protein panel, upon which the samples were reclassified and pathway analyses were performed. These panels were validated using clinical data (n = 4,665) from Human Protein Atlas.

RESULTS

Classification models based on the entire proteome, shared proteins, and discriminative protein panel were able to distinguish the nine tumor types with 49.15%, 69.10%, and 91.68% accuracy, respectively. Invasion and proliferation capacity of the 60 cell lines were predicted with R2 = 0.68 and R2 = 0.62 (p < 0.0001). The results of the Reactome pathway analysis of the discriminative protein panel suggest that the molecular content of EVs might be indicative of tumor-specific biological processes.

CONCLUSION

Integrating in vitro EV proteomic data, cell physiological characteristics, and clinical data of various tumor types illuminates the diagnostic, prognostic, and therapeutic potential of EVs. Video Abstract.

Development of nomograms for predicting the survival of intestinal-type gastric adenocarcinoma patients after surgery

Intestinal-type gastric adenocarcinoma (IGA) is a common phenotype of gastric cancer. Currently, few studies have constructed nomograms that may predict overall (OS) and cancer-specific survival (CSS) probability after surgery. This study is to establish novel nomograms for predicting the survival of IGA patients who received surgery. A total of 1814 IGA patients who received surgery between 2000 and 2018 were selected from Surveillance, Epidemiology, and End Results database and randomly assigned to the training and validating sets at a ratio of 7:3. Then univariate and multivariate cox regression analyses were performed to screen significant indictors for the construction of nomograms. The calibration curve, the area under the receiver operating characteristic (receiver operating characteristic, ROC) curve (the area under curve, AUC), C-index, net reclassification index (NRI), integrated discrimination improvement (IDI) and decision curve analysis (DCA) curves were applied to assess the performance of the model. The significant outcomes of multivariate analysis revealed that ten variables (age, sex, race, surgery type, summary stage, grade, AJCC TNM stage, radiotherapy, number of regional nodes examined, number of regional nodes positive) were demonstrated to construct the nomogram for OS and ten variables (age, sex, race, surgery type, summary stage, grade, AJCC TNM stage, chemotherapy, number of regional nodes examined, number of regional nodes positive) for CSS. The calibration and AUC uncovered their favorable predictive performance. Subsequently, C-index, NRI, IDI and DCA curves further validated the predicative superiority of nomograms over 7th AJCC Stage System. The validated nomogram provides more reliable OS and CSS predictions for postoperative IGA patients with good accuracy, which can help surgeons in treatment decision-making and prognosis evaluation.

The Prognostic Utility of the Metastatic Lymph Node Ratio and the Number of Regional Lymph Nodes Removed from Patients with Small Bowel Adenocarcinomas

Background and Objectives: Small bowel adenocarcinomas (SBAs) are rare tumors of the gastrointestinal system. Lymph node metastasis in patients with curatively resected SBAs is associated with poor prognosis. In this study, we determined the prognostic utility of the number of removed lymph nodes and the metastatic lymph node ratio (the N ratio). Materials and Methods: The data of 97 patients who underwent curative SBA resection in nine hospitals of Turkey were retrospectively evaluated. Univariate and multivariate analyses of potentially prognostic factors including the N ratio and the numbers of regional lymph nodes removed were evaluated. Results: Univariate analysis showed that perineural and vascular invasion, metastatic lymph nodes, advanced TNM stage, and a high N ratio were significant predictors of poor survival. Multivariate analysis revealed that the N ratio was a significant independent predictor of disease-specific survival (DSS). The group with the lowest N ratio exhibited the longest disease-free survival (DFS) and DSS; these decreased significantly as the N ratio increased (both, p < 0.001). There was no significant difference in either DFS or DSS between groups with low and high numbers of dissected lymph nodes (i.e., <13 and ≥13) (both, p = 0.075). Conclusions: We found that the N ratio was independently prognostic of DSS in patients with radically resected SBAs. The N ratio is a convenient and accurate measure of the severity of lymph node metastasis.

Development and validation a model for predicting overall survival of bladder cancer with lung metastasis: a population-based study

BACKGROUND

Although the number of patients with bladder cancer and lung metastasis is increasing there is no accurate model for predicting survival in these patients.

METHODS

Patients enrolled in the Surveillance, Epidemiology, and End Results database between 2010 and 2015 were selected for the study. Univariate and multivariate Cox regression were used to determine independent prognostic factors, followed by development of a nomogram based on the multivariate Cox regression models. The consistency index, receiver operating characteristic curve, and calibration curve were used to validate the prognostic nomogram.

RESULTS

506 eligible bladder cancer patients with lung metastasis were enrolled in the study and then divided randomly into training and validation sets (n = 356 vs. n = 150). Multivariate Cox regression analysis indicated that age at diagnosis, primary site, histological type, surgery of the primary site, chemotherapy, bone metastasis, and liver metastasis were prognostic factors for overall survival (OS) in patients with lung metastasis in the training set. The C-index of the nomogram OS was 0.699 and 0.747 in the training and validation sets, respectively. ROC curve estimation of the nomogram in the training and validation sets showed acceptable accuracy for classifying 1-year survival, with an area under the curve (AUC) of 0.766 and 0.717, respectively. More importantly, the calibration plot showed the nomogram had favorable predictive accuracy in both the training and validation sets.

CONCLUSIONS

The prognostic nomogram created in our study provides an individualized diagnosis, remedy, and risk evaluation for survival in patients with bladder cancer and lung metastasis. The nomogram would therefore enable clinicians to make more precise treatment decisions for patients with bladder cancer and lung metastasis.

The application of clinical variable-based nomogram in predicting overall survival in malignant phyllodes tumors of the breast

Background: We aimed to explore prognostic risk factors in patients with malignant phyllodes tumors (PTs) of the breast and construct a survival prediction model. Methods: The Surveillance, Epidemiology, and End Results database was used to collect information on patients with malignant breast PTs from 2004 to 2015. The patients were randomly divided into training and validation groups using R software. Univariate and multivariate Cox regression analyses were used to screen out independent risk factors. Then, a nomogram model was developed in the training group and validated in the validation group, and the prediction performance and concordance were evaluated. Results: The study included 508 patients with malignant PTs of the breast, including 356 in the training group and 152 in the validation group. Univariate and multivariate Cox proportional hazard regression analyses showed that age, tumor size, tumor stage, regional lymph node metastasis (N), distant metastasis (M) and tumor grade were independent risk factors for the 5-year survival rate of patients with breast PTs in the training group (p < 0.05). These factors were used to construct the nomogram prediction model. The results showed that the C-indices of the training and validation groups were 0.845 (95% confidence interval [CI] 0.802-0.888) and 0.784 (95% CI 0.688-0.880), respectively. The calibration curves of the two groups were close to the ideal 45° reference line and showed good performance and concordance. Receiver operating characteristic and decision curve analysis curves showed that the nomogram has better predictive accuracy than other clinical factors. Conclusion: The nomogram prediction model constructed in this study has good predictive value. It can effectively assess the survival rates of patients with malignant breast PTs, which will aid in the personalized management and treatment of clinical patients.

Prognostic Effect of Lymph Node Metastases and Mesenteric Deposits in Neuroendocrine Tumors of the Small Bowel

Well-differentiated, low-grade neuroendocrine tumors (NETs) are the most frequent tumor types of the small bowel. Despite their generally indolent growth patterns and grade, these tumors tend to metastasize; indeed, at presentation, approximately 50% show nodal metastases and 30% of patients have distant metastases, even though they potentially show long survival. Little is available in the literature concerning the optimal nodal yield in small-bowel resections, and the clinical significance of nodal metastases and lymph node ratio (LNR) at this site is still debated. The aim of this review, through a systematic literature search, is to explore and analyze data regarding nodal status, adequacy of lymphadenectomy, and LNR on the prognosis of small bowel NETs using defined end points (progression-free survival, recurrence-free survival, and overall survival). Some surgical series have demonstrated that extended regional mesenteric lymphadenectomy, together with primary tumor resection, is associated with improved patient survival, and LNR is proving a prognostically important parameter. The new feature of mesenteric tumor deposits (MTDs; neoplastic deposits found in the mesenteric perivisceral adipose tissue that are not LN associated) seems to be a better prognostic predictor in small-bowel NETs compared to nodal metastases, and this feature is explored and critiqued in this review. In particular, increasing number of tumor deposits is correlated with increased risk of disease-specific death, and MTDs seem to correlate with peritoneal carcinomatosis.

Development and validation of a prognostic nomogram for predicting cancer-specific survival in patients with metastatic clear cell renal carcinoma: A study based on SEER database

Objectives

Clear cell renal cell carcinoma (ccRCC) is highly prevalent, prone to metastasis, and has a poor prognosis after metastasis. Therefore, this study aimed to develop a prognostic model to predict the individualized prognosis of patients with metastatic clear cell renal cell carcinoma (mccRCC).

Patients and Methods

Data of 1790 patients with mccRCC, registered from 2010 to 2015, were extracted from the Surveillance, Epidemiology and End Results (SEER) database. The included patients were randomly divided into a training set (n = 1253) and a validation set (n = 537) based on the ratio of 7:3. The univariate and multivariate Cox regression analyses were used to identify the important independent prognostic factors. A nomogram was then constructed to predict cancer specific survival (CSS). The performance of the nomogram was internally validated by using the concordance index (C-index), calibration plots, receiver operating characteristic curves, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA). We compared the nomogram with the TNM staging system. Kaplan–Meier survival analysis was applied to validate the application of the risk stratification system.

Results

Diagnostic age, T-stage, N-stage, bone metastases, brain metastases, liver metastases, lung metastases, chemotherapy, radiotherapy, surgery, and histological grade were identified as independent predictors of CSS. The C-index of training and validation sets are 0.707 and 0.650 respectively. In the training set, the AUC of CSS predicted by nomogram in patients with mccRCC at 1-, 3- and 5-years were 0.770, 0.758, and 0.757, respectively. And that in the validation set were 0.717, 0.700, and 0.700 respectively. Calibration plots also showed great prediction accuracy. Compared with the TNM staging system, NRI and IDI results showed that the predictive ability of the nomogram was greatly improved, and DCA showed that patients obtained clinical benefits. The risk stratification system can significantly distinguish the patients with different survival risks.

Conclusion

In this study, we developed and validated a nomogram to predict the CSS rate in patients with mccRCC. It showed consistent reliability and clinical applicability. Nomogram may assist clinicians in evaluating the risk factors of patients and formulating an optimal individualized treatment strategy.

A modified survival model for patients with esophageal squamous cell carcinoma based on lymph nodes: A study based on SEER database and external validation

Background

The counts of examined lymph nodes (ELNs) in predicting the prognosis of patients with esophageal squamous cell carcinoma (ESCC) is a controversial issue. We conducted a retrospective study to develop an ELNs-based model to individualize ESCC prognosis.

Methods

Patients with ESCC from the SEER database and our center were strictly screened. The optimal threshold value was determine by the X-tile software. A prognostic model for ESCC patients was developed and validated with R. The model’s efficacy was evaluated by C-index, ROC curve, and decision curve analysis (DCA).

Results

3,629 cases and 286 cases were screened from the SEER database and our center, respectively. The optimal cut-off value of ELNs was 10. Based on this, we constructed a model with a favorable C-index (training group: 0.708; external group 1: 0.687; external group 2: 0.652). The model performance evaluated with ROC curve is still reliable among the groups. 1-year AUC for nomogram in three groups (i.e., 0.753, 0.761, and 0.686) were superior to that of the TNM stage (P < 0.05). Similarly, the 3-year AUC and the 5-year AUC results for the model were also higher than that of the 8th TNM stage. By contrast, DCA showed the benefit of this model was better in the same follow-up period.

Conclusion

More than 10 ELNs are helpful to evaluate the survival of ESCC patients. Based on this, an improved model for predicting the prognosis of ESCC patients was proposed.

Prediction of Solitary Plasmacytoma of Bone in Elderly Patients: A Nomogram and a Risk Classification System for Overall Survival

Background

Solitary plasmacytoma of bone (SPB) is an isolated plasmacytoma of bone origin, most commonly seen in the elderly, with a poor prognosis. So far, there is no precise nomogram to predict the overall survival (OS) of elderly patients with SPB. Our goal is to construct and validate a nomogram for elderly patients with SPB.

Methods

This study collected all elderly patients with SPB in the Surveillance, Epidemiology and End Results (SEER) database from 2000 to 2018, and the variables included were age, sex, race, marital status, primary site, grade, stage, surgery, chemotherapy, and radiotherapy. Independent prognostic factors were identified using univariate and multivariate Cox analysis. The nomogram was constructed to predict 1-, 2-, and 3-year OS of elderly patients with SPB. The receiver-operating characteristic (ROC) and the calibration curves were used to differentiate and calibrate the nomogram. The clinical validity of the nomogram was evaluated by decision curve analysis (DCA). The total OS scores of all elderly SPB patients were calculated and divided into two risk subgroups for comparison.

Results

A total of 1837 patients diagnosed with SPB were screened from the SEER database, with a final inclusion of 1180 patients (age ≥ 60 years). Age, radiotherapy, and marital status were significantly correlated with OS. These characteristics were further incorporated into the creation of the nomogram for predicting 1-, 2-, and 3-year OS of elderly patients with SPB. For this predictive model, the area under the ROC curves, calibration curves, and DCA have good performance in terms of differentiation, consistency, and validity, respectively. In addition, patients in the high-risk group (≥96) had a worse prognosis than those in the low-risk group (<96).

Conclusion

We constructed a nomogram and a risk classification system that could provide an intuitive and effective tool for clinicians to better predict the OS of elderly SPB patients.

Development and validation of prognostic nomograms for patients with metastatic small bowel adenocarcinoma: a retrospective cohort study

We aimed to explore factors associated with prognosis in patients with metastatic small bowel adenocarcinoma (SBA) as well as to develop and validate nomograms to predict overall survival (OS) and cancer-specific survival (CSS). Relevant information of patients diagnosed between 2004 and 2016 was extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Nomograms for predicting 1- and 3-year OS and CSS were established with potential risk factors screened from multivariate cox regression analysis. The discrimination and accuracy of the nomograms were assessed by concordance index (C-index), calibration plots, and the area under receiver operating characteristic curve (AUC). In total, 373 SBA patients with M1 category were enrolled. Multivariate analysis revealed that age, size and grade of primary tumor, primary tumor surgery, and chemotherapy were significant variables associated with OS and CSS. The C-index values of the nomogram for OS were 0.715 and 0.687 in the training and validation cohorts, respectively. For CSS, it was 0.711 and 0.690, respectively. Through AUC, decision curve analysis (DCA) and calibration plots, the nomograms displayed satisfactory prognostic predicted ability and clinical application both in the OS and CSS. Our models could be served as a reliable tool for prognostic evaluation of patients with metastatic SBA, which are favorable in facilitating individualized survival predictions and clinical decision-making.

Small Bowel Adenocarcinoma: From Molecular Insights to Clinical Management

Small bowel adenocarcinoma (SBA) is a rare malignancy, with a rising incidence in recent decades, and accounts for roughly 40% of all cancers of the small bowel. The majority of SBAs arise in the duodenum and are associated with a dismal prognosis. Surgery remains the mainstay of treatment for localized disease, while systemic treatments parallel those used in colorectal cancer (CRC), both in the adjuvant and palliative setting. In fact, owing to the lack of prospective data supporting its optimal management, SBA has historically been treated in the same way as CRC. However, recent genetic and molecular data suggest a distinct profile from other gastrointestinal malignancies and support a more nuanced approach to its management. Herein, we briefly review the state-of-the-art in the clinical management of early-stage and advanced disease and recent discoveries of potentially actionable genetic alterations or pathways along with the most promising ongoing clinical trials, which will hopefully revolutionize the treatment landscape of this orphan disease in the foreseeable future.

Nomograms predicting prognosis for locally advanced hypopharyngeal squamous cell carcinoma

PURPOSE

This study aimed to construct nomograms to predict the overall survival (OS) and cancer-specific survival (CSS) for patients with locally advanced hypopharyngeal squamous cell carcinoma (HSCC).

METHODS

864 patients with locally advanced HSCC during 2010-2015 from the surveillance, epidemiology and end results (SEER) database were selected. After classifying continuous data by risk, Cox regression analyses were applied to detect significant independent prognostic factors, with which nomograms were established. To evaluate the value of nomograms, concordance index (C-index), area under the receiver-operating characteristic (ROC) curve (AUC), calibration curves, and decision curve analysis (DCA), Kaplan-Meier analysis was adopted. The efficacy of surgery in different risk groups was also studied to figure out people who can benefit from surgery.

RESULTS

A total of 864 locally advanced HSCC patients were randomized into the training cohort (n = 608) and the validation cohort (n = 256). Age, race, tumor size, T stage, N stage, primary site, radiotherapy, and chemotherapy were independent prognostic factors for OS and CSS (except race) and formed the nomograms. The nomograms revealed satisfied performance in C-index, AUC, DCA, and calibration curves, and prevailed over American Joint Committee on Cancer (AJCC) TNM staging system in predicting OS and CSS. After risk stratification, patients of low-risk group resulted in the best outcomes. Patients in moderate-risk may benefit from surgery.

CONCLUSIONS

Convenient and well-calibrated nomograms to predict OS and CSS for III/IVA/IVB-stage HSCC patients were set up and assessed and may do a favor to make clinical decisions.

Analyzing and predicting the LNM rate and prognosis of patients with intraductal papillary mucinous neoplasm of the pancreas

Background

Current the surveillance and management are controversial for patients with IPMN. We aimed to develop an alternative nomogram to individualize IPMN prognosis and LNM.

Methods

Based on the data from SEER database of patients diagnosed with IPMN between 2004 and 2015, a nomogram predicting the survival and LNM of IPMN based on univariate and multivariate and Lasso regression analysis was performed, internally and externally validated, and measured by C‐index, and decision curve analysis (DCA), and compared to the 7^th TNM stage.

Results

A total of 941 patients were included. Age, T stage examined nodes, tumor size, and pathology grade were identified as an independent factor for predicting LNM. The nomogram we established to predict LNM had a high predicting value with a C‐index value of 0.735 and an AUC value of 0.753. Interestingly, including T1 stage, we found an inverse correlation was between age and LNM. In addition, nomogram for predicting CSS also performed better than TNM stage both in the internal validation group (1‐year AUC:0.753 vs. 0.693, 3‐year AUC: 0.801 vs. 0.731, 5‐year AUC: 0.803 vs. 0.733) and external validation group (1‐year AUC: 0.761 vs. 0.701, 3‐year AUC: 0.772 vs. 0.713, 5‐year AUC:0.811 vs. 0.735). DCA analysis showed the nomogram showed a greater benefit across the period of follow‐up compared to 7^th TNM stage.

Conclusion

A nomogram based on multivariate and Lasso regression analysis showed great clinical usability compared with current criteria. Also, for LNM of IPMN, younger age patients with IPMN should be attached more importance.

Development and validation of a novel competing risk model for predicting survival of esophagogastric junction adenocarcinoma: a SEER population-based study and external validation

Background

Adenocarcinoma in Esophagogastric Junction (AEG) is a severe gastrointestinal malignancy with a unique clinicopathological feature. Hence, we aimed to develop a competing risk nomogram for predicting survival for AEG patients and compared it with new 8th traditional tumor-node-metastasis (TNM) staging system.

Methods

Based on data from the Surveillance, Epidemiology, and End Results (SEER) database of AEG patients between 2004 and 2010, we used univariate and multivariate analysis to filter clinical factors and then built a competing risk nomogram to predict AEG cause-specific survival. We then measured the clinical accuracy by comparing them to the 8th TNM stage with a Receiver Operating Characteristic (ROC) curve, Brier score, and Decision Curve Analysis (DCA). External validation was performed in 273 patients from China National Cancer Center.

Results

A total of 1755 patients were included in this study. The nomogram was based on five variables: Number of examined lymph nodes, grade, invasion, metastatic LNs, and age. The results of the nomogram was greater than traditional TNM staging with ROC curve (1-year AUC: 0.747 vs. 0.641, 3-year AUC: 0.761 vs. 0.679, 5-year AUC: 0.759 vs. 0.682, 7-year AUC: 0.749 vs. 0.673, P < 0.001), Brier score (3-year: 0.198 vs. 0.217, P = 0.012; 5-year: 0.198 vs. 0.216, P = 0.008; 7-year: 0.199 vs. 0.215, P = 0.014) and DCA. In external validation, the nomogram also showed better diagnostic value than traditional TNM staging and great prediction accuracy.

Conclusion

We developed and validated a novel nomogram and risk stratification system integrating clinicopathological characteristics for AEG patients. The model showed superior prediction ability for AEG patients than traditional TNM classification.

Novel Prognostic Models Predicting the Cancer-Specific Survival in Patients with Cutaneous Melanoma Based on Metastatic Lymph Node Status

BACKGROUND

In cutaneous melanoma (CM), the present methods of lymph node (LN) staging have not sufficiently utilized the prognostic information of metastatic LNs. In this study, we aimed to construct prognostic nomograms based on the number of positive LNs (PLNs) and other clinicopathologic characteristics of CM patients.

METHODS

Two prognostic models were constructed in the none/single PLN (PLN_none/single) and multiple PLN (PLN_multiple) cohorts, respectively. Independent prognostic predictors associated with cancer-specific survival (CSS) in the above two cohorts were integrated to construct two nomograms for predicting the probability of 2-, 4-, and 6-year CSS in the PLN_none/single and PLN_multiple cohorts. The nomograms were evaluated by the area under the receiver operating characteristic curves (AUC), the calibration plots, and the decision curve analyses (DCAs).

RESULTS

A total of 31,065 CM cases were included in this study. Factors included in the prognostic nomogram for patients in the PLN_none/single cohort were age, sex, race, marital status, insurance, primary tumor site, T stage, and number of PLNs, while factors included in the nomogram for cases in the PLN_multiple cohort included age, sex, marital status, insurance, primary tumor site, T stage, and number of PLNs. The AUC values for 2-, 4-, and 6-year CSS in the validation group of the PLN_none/single cohort were 0.833, 0.811, and 0.818, respectively, while in the validation group of the PLN_multiple cohort, the AUC values for 2-, 4,- and 6-year CSS were 0.720, 0.723, and 0.745, respectively. Compared with the American Joint Committee on Cancer 7th edition staging system, our two nomograms showed better predictive values. Additionally, the calibration plots and DCA curves for 2-, 4-, and 6-year CSS prediction demonstrated good coordination and net benefit in both the PLN_none/single and PLN_multiple cohorts.

CONCLUSION

Our nomograms, based on the number of PLNs and other clinicopathologic characteristics, showed good predictive ability for predicting the survival of CM patients.

Novel survival nomograms for patients with lung metastatic clear cell renal cell carcinoma: A population-based study

Survival heterogeneity is observed among renal cell carcinoma (RCC) patients with metastases in different organs. Moreover, almost all previous prognostic nomograms based on data from metastatic RCC patients did not take competing events, such as death from cerebrovascular and heart diseases, into account. We aimed to construct novel prognostic nomograms for patients with lung metastatic clear cell RCC (LMCCRCC).Data of 712 non-Hispanic white LMCCRCC patients registered in the Surveillance, Epidemiology, and End Results database were retrospectively analyzed. Nomograms for predicting overall survival (OS) and disease-specific survival (DSS) were established using the Cox approach and Fine and Gray approach, respectively, and their performances were assessed using the concordance index (C-index), calibration plots, and an independent cohort comprising 181 Hispanic patients.Sex, tumor grade, T stage, N stage, presence or absence of bone metastases, and presence or absence of brain metastases were independent predictors for both OS and DSS. Additionally, presence or absence of liver metastases was an independent predictor only for DSS. Meanwhile, age at diagnosis was independently associated with OS. The C-indexes of the nomograms were 0.702 for OS and 0.723 for DSS in internal validation. In external validation, the C-indexes were 0.700 for OS and 0.708 for DSS. Both internal and external calibration plots showed excellent consistency between the prediction and the observation.The current study developed a novel nomogram for predicting individual OS in LMCCRCC patients. Moreover, we constructed an effective competing risk nomogram for predicting their individual DSS for the first time.

Log Odds of Positive Lymph Node- (LODDS-) Based Competing-Risk Nomogram for Predicting Prognosis of Resected Rectal Cancer: A Development and Validation Study

Background and Aims. Cancer-specific survival (CSS) of rectal cancer (RC) is associated with several factors. We aimed to build an efficient competing-risk nomogram based on log odds of positive lymph nodes (LODDS) to predict RC survival. Methods. Medical records of 8754 patients were collected from the Surveillance, Epidemiology, and End Results (SEER) database, of 4895 patients from SEER during 2011–2014 and of 478 patients from an Eastern center as a development cohort, validation cohort, and test cohort, respectively. Univariate and multivariate competing-risk analyses were performed to build competing-risk nomogram for predicting the CSS of RC patients. Prediction efficacy was evaluated and compared with reference to the 8th TNM classification using the factor areas under the receiver operating characteristic curve (AUC) and Brier score. Results. The competing-risk nomogram was based on 6 variables: size, M stage, LODDS, T stage, grade, and age. The competing-risk nomogram showed a higher AUC value in predicting the 5-year death rate due to RC than the 8th TNM stage in the development cohort (0.81 vs. 0.76), validation cohort (0.85 vs. 0.82), and test cohort (0.71 vs. 0.66). The competing-risk nomogram also showed a higher Brier score in predicting the 5-year death rate due to RC than the 8th TNM stage in the development cohort (0.120 vs. 0.127), validation cohort (0.123 vs. 0.128), and test cohort (0.202 vs. 0.226). Conclusion. We developed and validated a competing-risk nomogram for RC death, which could provide the probability of survival averting competing risk to facilitate clinical decision-making.

Development and validation of prognostic nomogram for germ cell testicular cancer patients

The purpose of our study was to establish a reliable and practical nomogram based on significant clinical factors to predict the overall survival (OS) and cancer-specific survival (CSS) of patients with germ cell testicular cancer (GCTC). Patients diagnosed with GCTC between 2004 and 2015 were obtained from the SEER database. Nomograms were constructed using the R software to predict the OS and CSS probabilities and the constructed nomograms were validated and calibrated. A total of 22,165 GCTC patients were enrolled in the study, including the training cohort (15,515 patients) and the validation cohort (6,650 patients). In the training cohort, multivariate Cox regression showed that age, race, AJCC stage, SEER stage and surgery were independent prognostic factors for OS, while age, race, AJCC stage, TM stage, SEER stage and radiotherapy were independent prognostic factors for CSS. Based on the above Cox regression results, we constructed prognostic nomograms of OS and CSS in GCTC patients and found that the OS nomograms had higher C-index and AUC compared to TNM stage in the training and validation cohorts. In addition, in the training and external validation cohorts, the calibration curves showed a good consistency between the predicted and actual 3-, 5- and 10-year OS and CSS rates of the nomogram. The current prognostic nomogram can provide a personalized risk assessment for the survival of GCTC patients.

Nomograms Predict Overall Survival and Cancer-Specific Survival in Patients with Fibrosarcoma: A SEER-Based Study

Purpose

Due to the rarity, it is difficult to predict the survival of patients with fibrosarcoma. This study aimed to apply a nomogram to predict survival outcomes in patients with fibrosarcoma.

Methods

A total of 2235 patients with diagnoses of fibrosarcoma were registered in the Surveillance, Epidemiology, and End Results database, of whom 663 patients were eventually enrolled. Univariate and multivariate Cox analyses were used to identify independent prognostic factors. Nomograms were constructed to predict 3-year and 5‐year overall survival and cancer‐specific survival of patients with fibrosarcoma.

Results

In univariate and multivariate analyses of OS, age, sex, race, tumor stage, pathologic grade, use of surgery, and tumor size were identified as independent prognostic factors. Age, sex, tumor stage, pathologic grade, use of surgery, and tumor size were significantly associated with CSS. These characteristics were further included to establish the nomogram for predicting 3-year and 5-year OS and CSS. For the internal validation of the nomogram predictions of OS and CSS, the C-indices were 0.784 and 0.801.

Conclusion

We developed the nomograms that estimated 3-year and 5-year OS and CSS. These nomograms not only have good discrimination performance and calibration but also provide patients with better clinical benefits.

Personalized four-category staging for predicting prognosis in patients with small bowel Adenocarcinoma: an international development and validation study

BACKGROUND

Log odds of positive lymph nodes (LODDS) classification showed superiority over 8^th edition N staging in predicting survival of small bowel adenocarcinoma (SBA) patients. The aim of this study was to develop and validate the Tumor, LODDS, and Metastasis (TLM) staging of SBA.

METHODS

Totally 1789 SBA patients from the Surveillance, Epidemiology, and End Results (SEER) database between 1988-2010, 437 patients from SEER database between 2011-2013 and 166 patients from multicenters were categorized into development, validation and test cohort, respectively. The TLM staging was developed in the development cohort using Ensemble Algorithm for Clustering Cancer Data (EACCD) method. C-index was used to assess the performance of the TLM staging in predicting cancer-specific survival (CSS) and was compared with the traditional 8^th edition TNM staging.

FINDINGS

Four-category TLM staging designed for the development cohort showed higher discriminatory power than TNM staging in predicting CSS in the development cohort (0.682 vs. 0.650, P < 0.001), validation cohort (0.682 vs. 0.654, P = 0.022), and test cohort (0.659 vs. 0.611, P = 0.023), respectively. TLM staging continued to show its higher predictive efficacy than the 8^th TNM in TNM stage II/III patients or in patients with lymph node yield less than 8.

INTERPRETATION

TLM staging showed a better prognostic performance than the 8^th TNM staging especially TNM stage II/III or patients with lymph node yield less than 8 and therefore, could serve to complement the TNM staging in patients with SBA.

FUNDING

A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

Analysis of the Incidence and Survival of Gastric Cancer Based on the Lauren Classification: A Large Population-Based Study Using SEER

Background: Limited evidence exists on the incidence of gastric cancer (GC), and contradictory results exist for the prognosis of GC based on the Lauren classification. We analyzed the incidence and survival of GC based on the Lauren classification. Methods: The Surveillance, Epidemiology, and End Results (SEER) database from 1975 through 2015 was used to identify all patients with surgically resected, histologically diagnosed intestinal or diffused-type GC. Propensity score matching was used to analyze the association between the Lauren classification type and prognosis. Results: The trend of total GC incidence showed an obvious decrease (APC = -1.51, 95% CI: -2.31 to -1.01) as well as that of the intestinal type (APC = -1.43, 95% CI: -2.01 to -1.12). However, we found that the relative incidence of the diffused type was increased (APC = 0.6, 95% CI: 0.41-0.82). The trend of the total incidence of GC (APC = -1.31, 95% CI: -1.91 to -1.03) and that of the intestinal type (APC = -1.11, 95% CI: -1.53 to -0.98) was decreased in 40-49-year-olds, but that of the diffused type was increased (APC = 1.5, 95% CI: 1.2-1.72). We found that trends in GC incidence exhibited a similar pattern in the regional and distant stages and showed a decrease from 1975 through 2015. However, the incidence rate of the local stage was increased, with an APC of 0.5 (95% CI: 0.3-0.7). We identified 15,989 GC cases from the SEER database, including 13,852 intestinal-type and 2,138 diffused-type cases. The 1,336 intestinal-type cases were matched with 1,336 diffused-type cases using propensity score matching (PSM), and patients with the diffused type had a better prognosis than patients with the intestinal type (HR = 0.56, 95% CI: 0.45-0.78). However, we found that patients with diffused-type GC had worse survival than patients with intestinal-type GC in the cohort from Renji Hospital (P < 0.001). Conclusion: The total incidence of GC and that of the intestinal-type GC decreased, but the incidence of diffused-type GC increased in 40-49-year-olds. Diffused types of GCs may have a different prognosis compared to intestinal-type GCs in different patient cohorts. Nevertheless, these results should be interpreted with caution in assessing the prognosis in combination with other factors.

Comprehensive analysis of autophagy-related prognostic genes in breast cancer

Accumulating evidence revealed that autophagy played vital roles in breast cancer (BC) progression. Thus, the aim of this study was to investigate the prognostic value of autophagy-related genes (ARGs) and develop a ARG-based model to evaluate 5-year overall survival (OS) in BC patients. We acquired ARG expression profiling in a large BC cohort (N = 1007) from The Cancer Genome Atlas (TCGA) database. The correlation between ARGs and OS was confirmed by the LASSO and Cox regression analyses. A predictive model was established based on independent prognostic variables. Thus, time-dependent receiver operating curve (ROC), calibration plot, decision curve and subgroup analysis were conducted to determine the predictive performance of ARG-based model. Four ARGs (ATG4A, IFNG, NRG1 and SERPINA1) were identified using the LASSO and multivariate Cox regression analyses. A ARG-based model was constructed based on the four ARGs and two clinicopathological risk factors (age and TNM stage), dividing patients into high-risk and low-risk groups. The 5-year OS of patients in the low-risk group was higher than that in the high-risk group (P < 0.0001). Time-dependent ROC at 5 years indicated that the four ARG-based tool had better prognostic accuracy than TNM stage in the training cohort (AUC: 0.731 vs 0.640, P < 0.01) and validation cohort (AUC: 0.804 vs 0.671, P < 0.01). The mutation frequencies of the four ARGs (ATG4A, IFNG, NRG1 and SERPINA1) were 0.9%, 2.8%, 8% and 1.3%, respectively. We built and verified a novel four ARG-based nomogram, a credible approach to predict 5-year OS in BC, which can assist oncologists in determining effective therapeutic strategies.

Construction and validation of a novel prognostic nomogram for patients with sarcomatoid renal cell carcinoma: a SEER-based study

OBJECTIVE

The only one established prognostic nomogram for patients with sarcomatoid renal cell carcinoma (sRCC) was based on a small sample-sized study without external validation, and a nomogram can be applied to western sRCC patients has not yet been developed. Therefore, our study aimed to construct and validate an effective nomogram to predict overall survival (OS) for these patients.

METHODS

The independent predictors for OS were identified and the nomogram was constructed on the basis of a retrospective study of a training cohort consisted of 428 non-Hispanic white sRCC patients registered in the Surveillance, Epidemiology and End Results (SEER) database from January 2010 to December 2015. Then, the discriminative performance of the nomogram was assessed by the concordance index (C-index). OS calibrations of the nomogram were also performed by comparing the nomogram-predicted probability to the observed survival rate. Furthermore, our nomogram was externally validated using two independent cohorts consisted of 71 non-Hispanic black patients and 82 Hispanic patients, respectively.

RESULTS

Age at diagnosis, T stage, N stage, bone metastases, liver metastases, lung metastases and nephrectomy were identified as independent predictors for OS. In the training cohort and two validation cohorts, the C-indexes of the nomogram were 0.737, 0.801 and 0.764, respectively. Besides, excellent agreements between the nomogram prediction and the actual observation were achieved in all cohorts.

CONCLUSIONS

The current study constructed and validated an effective prognostic nomogram for patients with sRCC, which can be used to perform accurate predictions of the 0.5-, 1-, and 2-year possibilities of OS.

Nomogram for predicting the survival of gastric adenocarcinoma patients who receive surgery and chemotherapy

Background

Surgery is the only way to cure gastric adenocarcinoma (GAC), and chemotherapy is the basic adjuvant management for GAC. A significant prognostic nomogram for predicting the respective disease-specific survival (DSS) rates of GAC patients who receive surgery and chemotherapy has not been established.

Objective

We were planning to establish a survival nomogram model for GAC patients who receive surgery and chemotherapy.

Methods

We identified 5764 GAC patients who had received surgery and chemotherapy from the record of Surveillance, Epidemiology, and End Results (SEER) database. About 70% (n = 4034) of the chosen GAC patients were randomly assigned to the training set, and the rest of the included ones (n = 1729) were assigned to the external validation set. A prognostic nomogram was constructed by the training set and the predictive accuracy of it was validated by the validation set.

Results

Based on the outcome of a multivariate analysis of candidate factors, a nomogram was developed that encompassed age at diagnosis, number of regional lymph nodes examined after surgery, number of positive regional lymph nodes, sex, race, grade, derived AJCC stage, summary stage, and radiotherapy status. The C-index (Harrell’s concordance index) of the nomogram model was some larger than that of the traditional seventh AJCC staging system (0.707 vs 0.661). Calibration plots of the constructed nomogram displayed that the probability of DSS commendably accord with the survival rate. Integrated discrimination improvement (IDI) revealed obvious increase and categorical net reclassification improvement (NRI) showed visible enhancement. IDI for 3-, 5- and 10- year DSS were 0.058, 0.059 and 0.058, respectively (P > 0.05), and NRI for 3-, 5- and 10- year DSS were 0.380 (95% CI = 0.316–0.470), 0.407 (95% CI = 0.350–0.505), and 0.413 (95% CI = 0.336–0.519), respectively. Decision curve analysis (DCA) proved that the constructed nomogram was preferable to the AJCC staging system.

Conclusion

The constructed nomogram supplies more credible DSS predictions for GAC patients who receive surgery and chemotherapy in the general population. According to validation, the new nomogram will be beneficial in facilitating individualized survival predictions and useful when performing clinical decision-making for GAC patients who receive surgery and chemotherapy.

Development and validation of a SEER-based prognostic nomogram for patients with bone metastatic prostate cancer

Controversies exist between the previous two prognostic nomograms for patients with bone metastatic prostate cancer (PCa), and a nomogram applied to western patients has yet to be established. Thus, we aimed to build a reliable and generic nomogram to individualize prognosis.The independent prognostic factors were identified in a retrospective study of 1556 patients with bone metastatic PCa registered in the Surveillance, Epidemiology and End Results (SEER) database. Besides, the prognostic nomogram was developed using R software according to the result of multivariable Cox regression analysis. Then, the discriminative ability of the nomogram was assessed by analyses of receiver operating characteristic curves (ROC curves). We also performed 1-, 2-, and 3-year calibrations of the nomogram by comparing the predicted survival to the observed survival. Furthermore, the model was externally validated using the data of 711 patients diagnosed at different times enrolled in the SEER database.Age ≥70 years, Gleason score ≥8, PSA value of 201 to 900 ng/ml, stage T4, stage N1, with liver metastases, and Asian/Pacific ethnicity were identified as independent prognostic factors. In the primary cohort, 1-, 2-, and 3-year area under the ROC curve (AUC) of the nomogram for predicting cancer-specific survival (CSS) were 0.71, 0.70, and 0.70, respectively. Besides 1-, 2-, and 3-year AUC were 0.70, 0.68, and 0.69, respectively, in the external validation cohort. Moreover, calibration curves presented perfect agreements between the nomogram-predicted and actual 1-, 2-, and 3-year CSS rate in both the primary and external validation cohorts. In other words, our nomogram has great predictive accuracy and reliability in predicting 1-, 2-, and 3-year CSS for patients with bone metastatic prostate cancer.This study established and validated a prognostic nomogram applied to not only Asian patients but western patients with bone metastatic PCa, which will be useful for patients' counseling and clinical trial designing.

An Examination of Lymph Node Sampling as a Predictor of Survival in Resected Node-Negative Small Bowel Adenocarcinoma: a SEER Database Analysis

BACKGROUND

Small bowel adenocarcinoma (SBA) is a rare disease. Current recommendations are largely extrapolated from the colorectal literature. For node-negative (N -ve) cases, optimally stratifying cases into high or low risk, may help define optimal management. The objective of this analysis was to determine the importance of lymph node sampling for prognostication and to define what number of lymph nodes sampled is adequate.

METHODS

Cases of non-metastatic SBA with complete staging, pathologic, and demographic information were selected from the SEER database and SAS 9.4 software was used. Variables included age, gender, race, grade, TNM staging, and number of lymph nodes were examined. Comparisons were made between N -ve and N +ve cases. Survival analysis using N -ve cases was performed to characterize the impact of nodal sampling on survival and to determine which nodal cut-offs best predict survival.

RESULTS

A total of 523 cases from 2004 to 2014 were included in this analysis. Statistically significant differences identified included the median number of nodes sampled between the N -ve and N +ve groups, and the distribution of T stage and grade. Survival analysis in the N -ve cases demonstrated that the strongest predictor of survival was sampling of 16 or more lymph nodes.

CONCLUSION

In this analysis, lymph node sampling was shown to be the most important pathologic predictor of survival in cases of N -ve SBA. Replicating these findings in a secondary dataset and determining whether a clinical benefit of adjuvant chemotherapy exists for SBA patients with inadequate sampling are both important next steps.

Comparison of three lymph node staging schemes for predicting the outcome in patients with small bowel adenocarcinoma: A population-based cohort and international multicentre cohort study

Background

The prognostic roles of three common lymph node staging schemes, number of positive lymph nodes (pN), lymph node ratio (LNR) and log odds of positive lymph nodes (LODDS) in small bowel adenocarcinoma (SBA) are unclear. We assessed their prognostic ability in SBA.

Methods

A total of 2128 patients diagnosed with SBA between 1988 and 2010 from the Surveillance, Epidemiology, and End Results (SEER) database and 186 patients from 15 hospitals in France and China were identified. We evaluated the prognostic ability of the schemes in both continuous and stratified patterns using R², Harrell's C, and time-dependent receiver operating characteristic curve analyses.

Findings

For continuous pattern, the LODDS had a better capacity of discrimination and higher accuracy of prognosis than pN and LNR. Similarly, the stratified LODDS classification had a better performance of discrimination and higher accuracy of prognosis than the pN and LNR classification. The multivariable model using the LODDS classification also showed superiorly predictive accuracy and discriminatory capacity to those of the 7th and, 8th TNM node and LNR classification. These results were fully validated in an independent international multicentre cohort.

Interpretation

The LODDS scheme showed a better prognostic performance than the LNR or pN schemes in patients with SBA regardless of continuous or stratified pattern. The LODDS scheme could serve as an auxiliary to lymph node staging systems in future revisions of the American Joint Committee on Cancer (AJCC) manual.

Fund

This work was funded by the Zhejiang Province Natural Science Fund of China.

Identification of a 4-mRNA metastasis-related prognostic signature for patients with breast cancer

Metastasis‐related mRNAs have showed great promise as prognostic biomarkers in various types of cancers. Therefore, we attempted to develop a metastasis‐associated gene signature to enhance prognostic prediction of breast cancer (BC) based on gene expression profiling. We firstly screened and identified 56 differentially expressed mRNAs by analysing BC tumour tissues with and without metastasis in the discovery cohort (GSE102484, n = 683). We then found 26 of these differentially expressed genes were associated with metastasis‐free survival (MFS) in the training set (GSE20685, n = 319). A metastasis‐associated gene signature built using a LASSO Cox regression model, which consisted of four mRNAs, can classify patients into high‐ and low‐risk groups in the training cohort. Patients with high‐risk scores in the training cohort had shorter MFS (hazard ratio [HR] 3.89, 95% CI 2.53‐5.98; P < 0.001), disease‐free survival (DFS) (HR 4.69, 2.93‐7.50; P < 0.001) and overall survival (HR 4.06, 2.56‐6.45; P < 0.001) than patients with low‐risk scores. The prognostic accuracy of mRNAs signature was validated in the two independent validation cohorts (GSE21653, n = 248; GSE31448, n = 246). We then developed a nomogram based on the mRNAs signature and clinical‐related risk factors (T stage and N stage) that predicted an individual's risk of disease, which can be assessed by calibration curves. Our study demonstrated that this 4‐mRNA signature might be a reliable and useful prognostic tool for DFS evaluation and will facilitate tailored therapy for BC patients at different risk of disease.