Individualized prediction of colon cancer recurrence using a nomogram

Nomograms predicting survival and recurrence in colonic cancer in the era of complete mesocolic excision

Background

More extensive lymphadenectomy may improve survival after resection of colonic cancer. Nomograms were created predicting overall survival and recurrence for patients who undergo D2-D3 lymph node dissection, and their validity determined.

Methods

This was a multicentre study of patients with colonic cancer who underwent resection with D2-D3 lymph node dissection in Japan. Inclusion criteria included R0 resection. A training cohort of patients operated on from 2007 to 2008 was analysed to construct prognostic models predicting survival and recurrence. Discrimination and calibration were performed using an external validation cohort from the Japanese colorectal cancer registry (procedures in 2005-2006).

Results

The training cohort consisted of 2746 patients. Predictors of survival were: age (hazard ratio (HR) 1·04), female sex (HR 0·71), depth of tumour invasion (HR 1·15, 1·22, 2·96 and 3·14 for T2, T3, T4a and T4b respectively versus T1), lymphatic invasion (HR 1·11, 1·15 and 2·95 for ly1, ly2 and ly3 versus ly0), preoperative carcinoembryonic antigen (CEA) level (HR 1·21, 1·59 and 1·99 for 5·1-10·0, 10·1-20·0 and 20·1 and over versus 0-5·0 ng/ml), number of metastatic lymph nodes (HR 1·07), number of lymph nodes examined (HR 0·98) and extent of lymphadenectomy (HR 0·23, 0·13 and 0·11 for D1, D2 and D3 versus D0). Predictors of recurrence were: female sex (HR 0·82), macroscopic type (HR 3·82, 4·56, 6·66, 7·74 and 3·22 for types I, II, III, IV and V versus type 0), depth of invasion (HR 1·25, 2·66, 5·32 and 6·43 for T2, T3, T4a and T4b versus T1), venous invasion (HR 1·43, 3·05 and 4·79 for v1, v2 and v3 versus v0), preoperative CEA level (HR 1·39, 1·43, 1·56 and 1·85 for 5·1-10·0, 10·1-20·0, 20·1-40·0 and 40·1 or more versus 0-5 ng/ml), number of metastatic lymph nodes (HR 1·07) and number of lymph nodes examined (HR 0·98). The validation cohort comprised 4446 patients. The internal and external validated Harrell's C-index values for the nomogram predicting survival were 0·75 and 0·74 respectively. Corresponding values for recurrence were 0·78 and 0·75.

Conclusion

These nomograms could predict survival and recurrence after curative resection of colonic cancer.

Prognostic Significance of PSMD1 Expression in Patients with Gastric Cancer

Background: PSMD1 has been considered to be involved in many human cancers, but its prognostic significance in gastric cancer (GC) has not been elucidated. The aim of this study was to evaluate the prognostic value of PSMD1 expression in tumor tissues of GC patients. Methods: We retrospectively analyzed the expression of PSMD1 in 241 paraffin-embedded GC specimens of the training cohort by immunohistochemistry. The prognostic value of PSMD1 expression was assessed using Kaplan-Meier survival curves and multivariate COX regression models. PSMD1 expression and other GC-associated risk factors were used to generate two nomograms to evaluate prognosis, and the performance of the two nomograms was assessed with respect to its calibration, discrimination, and clinical usefulness. Further validation was performed using an independent cohort of 170 cases. Results: High PSMD1 expression was significantly associated with decreased disease-free survival (DFS) and overall survival (OS) in GC patients. Furthermore, multivariate Cox proportional hazard analysis demonstrated that PSMD1 was an independent prognostic factor for DFS and OS. The two nomograms that were developed by integrating PSMD1 expression and the TNM staging system showed better prediction of DFS and OS than TNM staging system alone(C-index for training cohort: 0.708 (95% CI:0.670-0.746) and 0.712 (0.671-0.752), respectively; C-index for validation cohort: 0.704 (0.651-0.757) and 0.711 (0.656-0.767), respectively). Decision curve analysis demonstrated that the nomograms showed potential for clinical use. Conclusion: Intratumoral PSMD1 expression is a novel independent predictor of DFS and OS in GC patients. In the future, large-scale prospective studies will be necessary to confirm our findings regarding its potential prognostic and therapeutic value for GC patients.

Poorly Differentiated Clusters Predict Colon Cancer Recurrence: An In-Depth Comparative Analysis of Invasive-Front Prognostic Markers

This study aimed to compare common histologic markers at the invasive front of colon adenocarcinoma in terms of prognostic accuracy and interobserver agreement. Consecutive patients who underwent curative resection for stages I to III colon adenocarcinoma at a single institution in 2007 to 2014 were identified. Poorly differentiated clusters (PDCs), tumor budding, perineural invasion, desmoplastic reaction, and Crohn-like lymphoid reaction at the invasive front, as well as the World Health Organization (WHO) grade of the entire tumor, were analyzed. Prognostic accuracies for recurrence-free survival (RFS) were compared, and interobserver agreement among 3 pathologists was assessed. The study cohort consisted of 851 patients. Although all the histologic markers except WHO grade were significantly associated with RFS (PDCs, tumor budding, perineural invasion, and desmoplastic reaction: P<0.001; Crohn-like lymphoid reaction: P=0.021), PDCs (grade 1 [G1]: n=581; G2: n=145; G3: n=125) showed the largest separation of 3-year RFS in the full cohort (G1: 94.1%; G3: 63.7%; hazard ratio [HR], 6.39; 95% confidence interval [CI], 4.11-9.95; P<0.001), stage II patients (G1: 94.0%; G3: 67.3%; HR, 4.15; 95% CI, 1.96-8.82; P<0.001), and stage III patients (G1: 89.0%; G3: 59.4%; HR, 4.50; 95% CI, 2.41-8.41; P<0.001). PDCs had the highest prognostic accuracy for RFS with the concordance probability estimate of 0.642, whereas WHO grade had the lowest. Interobserver agreement was the highest for PDCs, with a weighted kappa of 0.824. The risk of recurrence over time peaked earlier for worse PDCs grade. Our findings indicate that PDCs are the best invasive-front histologic marker in terms of prognostic accuracy and interobserver agreement. PDCs may replace WHO grade as a prognostic indicator.

Development and validation of prognostic nomograms for patients with metastatic prostate cancer

OBJECTIVE

This study aimed to develop and validate nomograms to predict overall survival (OS) and cancer-specific survival (CSS) in patients with prostate cancer.

METHODS

Clinical data of patients with mPCa between 2010 and 2014 were retrieved retrospectively, and randomized into training (2/3) and validation sets (1/3). Nomograms were built with potential risk factors based on COX regression analysis. Accuracy was validated using the discrimination and calibration curve for the training and validation groups, respectively.

RESULTS

6659 mPCa patients were collected and enrolled, including 4440 in the training set and 2219 in the validation set. Multivariate analysis showed that age, marital status, PSA, biopsy Gleason score, T stage, and bone metastasis were independent risk factors for both OS and CSS. The concordance index (C-index) of OS was 0.735 (95% CI 0.722-0.748) for the internal validation and 0.735 (95% CI 0.717-0.753) for the external validation. For CSS, it was 0.734 (95% CI 0.721-0.747) and 0.742 (95% CI 0.723-0.761), respectively. The nomograms for predicting OS and CSS displayed better discrimination power in both training and validation sets. Moreover, a favorable consistency between the predicted and actual survival probabilities was demonstrated using calibration curves.

CONCLUSIONS

The nomograms showed good performances for predicting OS and CSS in patients with prostate cancer. It might be a convenient individualized predictive tool for prognosis in clinical practice.

Beppu's Nomogram Score Is an Independent Prognostic Factor for Colorectal Liver Metastasis Receiving Perioperative Chemotherapy and/or Targeted Therapy

BACKGROUND/AIM

We investigated the impact of Beppu's nomogram on colorectal liver metastasis in patients receiving perioperative chemotherapy and/or targeted therapy.

PATIENTS AND METHODS

This study included 43 patients who underwent primary hepatic resection for colorectal liver metastasis at the Kanagawa Cancer Center from June 2006 to March 2011. The patients were classified as having a Beppu's nomogram score ≤9 (low-risk group) or ≥10 (high-risk group). The risk factors for the disease-free survival (DFS) were identified.

RESULTS

The respective DFS rates at 1, 2, and 3 years after surgery were 72.0%, 43.3%, and 17.3% in the low-risk group and 27.8%, 16.7%, and 8.3% in the high-risk group, the difference being significant (p=0.009). The multivariate analysis showed that Beppu's nomogram score ≥10 was a significant independent risk factor for the DFS.

CONCLUSION

Beppu's nomogram score was an independent prognostic factor for colorectal liver metastasis in patients receiving perioperative chemotherapy and/or targeted therapy. Thus, Beppu's nomogram might be a useful tool for predicting the risk of recurrence after hepatectomy, even in the era of newly-developed chemotherapy.

Novel nomograms to predict lymph node metastasis and liver metastasis in patients with early colon carcinoma

Background

Lymph node status and liver metastasis (LIM) are important in determining the prognosis of early colon carcinoma. We attempted to develop and validate nomograms to predict lymph node metastasis (LNM) and LIM in patients with early colon carcinoma.

Methods

A total of 32,819 patients who underwent surgery for pT1 or pT2 colon carcinoma were enrolled in the study based on their records in the SEER database. Risk factors for LNM and LIM were assessed based on univariate and multivariate binary logistic regression. The C-index and calibration plots were used to evaluate LNM and LIM model discrimination. The predictive accuracy and clinical values of the nomograms were measured by decision curve analysis. The predictive nomograms were further validated in the internal testing set.

Results

The LNM nomogram, consisting of seven features, achieved the same favorable prediction efficacy as the five-feature LIM nomogram. The calibration curves showed perfect agreement between nomogram predictions and actual observations. The decision curves indicated the clinical usefulness of the prediction nomograms. Receiver operating characteristic curves indicated good discrimination in the training set (area under the curve [AUC] = 0.667, 95% CI 0.661–0.673) and the testing set (AUC = 0.658, 95% CI 0.649–0.667) for the LNM nomogram and encouraging performance in the training set (AUC = 0.766, 95% CI 0.760–0.771) and the testing set (AUC = 0.825, 95% CI 0.818–0.832) for the LIM nomogram.

Conclusion

Novel validated nomograms for patients with early colon carcinoma can effectively predict the individualized risk of LNM and LIM, and this predictive power may help doctors formulate suitable individual treatments.

Association of the prognostic nutritional index and overall survival in patients with colorectal cancer: A STROBE compliant retrospective cohort study

BACKGROUND

The TNM classification does not completely reflect the prognosis of patients with colorectal cancer (CRC). Several clinical factors have been used to increase its prognostic value, but factors pertaining to the patient's immunonutritional status have not usually been addressed. The aim of this study is to evaluate the role of Prognostic nutritional index (PNI) and other well-known prognostic factors by multivariate analysis in a cohort of patients with CRC.

METHODS

This is a retrospective cohort study of consecutive patients with CRC managed in a cancer center between January 1992 and December 2016. Cox's model was used to define the association of the PNI and other factors with Overall survival (OS).

RESULTS

A total of 3301 patients were included: 47.7% were female and 52.3% were male, with a mean age of 58.7 years. By bivariate analysis, PNI was strongly associated with OS (Risk ratio [RR] 0.968, 95% Confidence interval [CI] 0.962-0.974; P < 0.001). On multivariate analysis, PNI was an independent explanatory variable (as continuous variable and as categorized variable; RR 0.732, 95% CI 0.611-0.878; RR 0.656, 95% CI 0.529-0.813 and RR 0.646, 95% CI 0.521-0.802, for quintiles 2, 3, and 4-5, respectively); a biological gradient effect was demonstrated. The final prognostic model included PNI, location of the neoplasia in the colorectum, basal hemoglobin, lymphocyte count, neutrophil/lymphocyte ratio, platelet/lymphocyte ratio, TNM stage, differentiation degree, R classification, and postoperative complications.

CONCLUSIONS

PNI is a significant and independent prognostic factor in patients with CRC. Its prognostic value adds precision to the TNM staging system including specific subgroups of patients with CRC; it should be evaluated in prospective clinical studies.

Use of Machine-Learning Algorithms in Intensified Preoperative Therapy of Pancreatic Cancer to Predict Individual Risk of Relapse

Background: Although surgical resection is the only potentially curative treatment for pancreatic cancer (PC), long-term outcomes of this treatment remain poor. The aim of this study is to describe the feasibility of a neoadjuvant treatment with induction polychemotherapy (IPCT) followed by chemoradiation (CRT) in resectable PC, and to develop a machine-learning algorithm to predict risk of relapse. Methods: Forty patients with resectable PC treated in our institution with IPCT (based on mFOLFOXIRI, GEMOX or GEMOXEL) followed by CRT (50 Gy and concurrent Capecitabine) were retrospectively analyzed. Additionally, clinical, pathological and analytical data were collected in order to perform a 2-year relapse-risk predictive population model using machine-learning techniques. Results: A R0 resection was achieved in 90% of the patients. After a median follow-up of 33.5 months, median progression-free survival (PFS) was 18 months and median overall survival (OS) was 39 months. The 3 and 5-year actuarial PFS were 43.8% and 32.3%, respectively. The 3 and 5-year actuarial OS were 51.5% and 34.8%, respectively. Forty-percent of grade 3-4 IPCT toxicity, and 29.7% of grade 3 CRT toxicity were reported. Considering the use of granulocyte colony-stimulating factors, the number of resected lymph nodes, the presence of perineural invasion and the surgical margin status, a logistic regression algorithm predicted the individual 2-year relapse-risk with an accuracy of 0.71 (95% confidence interval [CI] 0.56–0.84, p = 0.005). The model-predicted outcome matched 64% of the observed outcomes in an external dataset. Conclusion: An intensified multimodal neoadjuvant approach (IPCT + CRT) in resectable PC is feasible, with an encouraging long-term outcome. Machine-learning algorithms might be a useful tool to predict individual risk of relapse. A small sample size and therapy heterogeneity remain as potential limitations.

Contemporary Validation of a Nomogram Predicting Colon Cancer Recurrence, Revealing All-Stage Improved Outcomes

Background

The Memorial Sloan Kettering Cancer Center (MSK) colon cancer recurrence nomogram is a risk calculator that provides patients and clinicians with individualized prediction of recurrence following curative resection of colon cancer. Although validated on multiple separate cohorts, the nomogram requires periodic updating as patient care changes over time. The aim of this study was to evaluate the nomogram’s accuracy in a contemporary cohort and modify the tool to reflect improvements in outcome related to advances in colon cancer therapy.

Methods

A contemporary patient cohort was compiled, including consecutive colon cancer patients undergoing curative resection for stage I–III colon adenocarcinoma at MSK from 2007 to 2014. The nomogram’s predictive accuracy was assessed by concordance index and calibration plots of predicted vs actual freedom from recurrence at 5 years after surgery.

Results

Data from a total of 999 eligible patients with complete records were used for validation. Median follow-up among survivors was 37 months. The concordance index was 0.756 (95% confidence interval = 0.707 to 0.805), indicating continued discriminating power, but the calibration plot revealed that the nomogram overestimated recurrence risk. Recalibration of the nomogram by estimating a new baseline freedom-from-recurrence function restored the nomogram’s accuracy.

Conclusion

The updated nomogram retains the original nomogram’s variables but includes a lower baseline estimation of recurrence risk, reflecting improvements in outcomes for all stages of colon cancer, likely resulting from advances in imaging and integration of multiple treatment modalities.

Development and validation of prognostic nomograms for medullary thyroid cancer

Background

This aim of study was to develop and validate clinical nomograms to predict the survival of patients with medullary thyroid cancer.

Patients and methods

Patient data were collected from the Surveillance, Epidemiology, and End Results database between 2004 and 2013. All included patients were randomly assigned into the training and validation sets. Multivariate analysis using Cox proportional hazards regression was performed, and nomograms were constructed. Model performance was evaluated by discrimination and calibration plots.

Results

A total of 1,657 patients were retrospectively analyzed. The multivariate Cox model identified age, tumor size, extrathyroidal extension, N stage, and M stage as independent covariates associated with overall survival (OS) and cancer-specific survival (CSS). Nomograms predicting OS and CSS were constructed based on these covariates. The nomograms predicting both OS and CSS exhibited superior discrimination power to that of TNM staging system in the training and validation sets. Calibration plots indicated that both the nomograms in OS and CSS exhibited high correlation to actual observed results.

Conclusion

The nomograms established in this study provided an alternative tool for prognostic prediction, which may thereby improve individualized assessment of survival risks and lead to the creation of additional clinical therapies.

Evaluation of the transferability of survival calculators for stage II/III colon cancer across healthcare systems

Adjuvant! Online Inc (A!O), the Memorial Sloan Kettering Cancer Center (MSKCC), MD Anderson (MDA) and Mayo Clinic (MC) provide calculators to predict survival probabilities for patients with resected early-stage colon cancer, trained on data from United States (US) patient cohorts or patients enrolled in international clinical trials. Limited data exist on the transferability of calculators across healthcare systems. Calculator transferability to Australian community practice was evaluated for 1,401 stage II/III patients. Calibration and discrimination were assessed for overall (OS), cancer-specific (CSS) or recurrence-free survival (RFS). The US patient cohort-based calculators, A!O, MSKCC and MDA, significantly overestimated risks of recurrence and death in Australian patients, with 5-year OS, CSS and RFS prediction differences of -6.5% to -9.9%, -9.1% to -14.4% and - 3.8% to -6.8%, respectively (p < 0.001). Significant heterogeneity in calibration was observed for subgroups by tumor stage and treatment, age, gender, tumor location, ECOG and ASA score. Calibration appeared acceptable for the clinical trial patient-based MC calculator, but restricted tool applicability (stage III patients, ≥12 examined lymph nodes, receiving adjuvant treatment) limited the sample size. Compared to AJCC 7th edition tumor staging, calculators showed improved discrimination for OS, but no improvement for CSS and RFS. In conclusion, deficiencies in calibration limited transferability of US patient cohort-based survival calculators for early-stage colon cancer to the setting of Australian community practice. Our results demonstrate the utility for multi-feature survival calculators to improve OS predictions but highlight the importance for performance assessment of tools prior to implementation in an external health care setting.

Development and external validation of a nomogram predicting prognosis of upper tract urothelial carcinoma after radical nephroureterectomy

OBJECTIVE

To create multivariable models with readily available clinicopathologic variables for predicting the prognosis of upper tract urothelial carcinomas (UTUC).

PATIENTS AND METHODS

We retrospectively analyzed patients diagnosed as UTUC and underwent radical nephroureterectomy in 2 high volumes, tertiary care centers. A total of 445 patients and 227 patients met the inclusion criteria were included for constructing the prediction model and external validation, respectively. Univariable and multivariable Cox regression models were used to analyze independent risk factors, and nomogram and calibration curve were constructed by R project.

RESULTS

The median follow-up for the development and external validation cohorts were 33.5 and 32.5 months, respectively. Multivariable analysis detected older age (≥65 years), with concurrent bladder cancer at diagnosis, with both ureter and renal pelvic tumor, lymphovascular invasion, urothelial carcinoma with divergent differentiation, higher pathological grade and stage, and positive lymph node were significantly associated with poorer outcome of UTUC. The c-index of the nomogram with these above-mentioned independent risk factors to predict the cancer specific survival was 0.74 (95% CI, 0.64-0.84) and 0.73 (95%CI, 0.59-0.87) for the development cohort and external validation cohort, respectively.

CONCLUSIONS

We developed and externally validated a novel and accurate nomogram with readily available clinicopathological information for predicting the cancer specific survival of UTUC. This nomogram could help clinicians stratify patients with UTUC into different risk groups with distinct prognosis by the total scores obtained from the prediction tool, thus facilitate decision-making and clinical trial designing.

A competing-risks nomogram for predicting probability of death from CRC in Chinese Han patients with Stage I-III CRC

Background

Many patients with colorectal cancer are elderly with competing comorbidities. When constructing nomogram for assessing survival, we should consider the influence of competing risk. A competing-risks nomogram was developed to estimate the probability of death due to colorectal cancer for patients after curative surgery.

Methods

A total of 2442 patients with non-metastatic colorectal cancer were included to develop competing-risks nomogram. Competing-risks nomogram were established based on the results of Fine and Gray competing-risks proportional hazards model. To maximize the accuracy of prediction, model selection was not carried out, and non-linear continuous variables were flexibly modeled with restricted cubic splines. The nomogram was internal-validated by bootstrapping, and externally validated with a separate database of 299 patients from The Cancer Genome Atlas. The performance of this model was assessed by concordance index and a calibration curve.

Results

There were 332 patients died of colorectal cancer and 46 died of other causes during the follow-up period. Age, T stage, N stage, histological type, tumor location, adjuvant chemotherapy, preoperative carcinoembryonic antigen, lymph vascular invasion, lymph node ratio and sample lymph nodes were integrated into competing-risks nomogram. The competing-risks nomogram for predicting probability of death due to colorectal cancer with a concordance index of 0.768, ameliorating the stratification provided by the seventh edition tumor-node-metastasis staging system of the American Joint Committee on Cancer (AJCC). The concordance index for validation dataset was 0.783.

Conclusion

We developed and externally validated a competing-risks nomogram for Chinese Han patients with non-metastatic colorectal cancer, which could provide probability of death from colorectal cancer in the presence of competing risks.

Nomogram-Based New Recurrence Predicting System in Early-Stage Papillary Thyroid Cancer

BACKGROUND AND OBJECTIVES

The clinicopathological risk factors to predict recurrence of papillary thyroid cancer (PTC) patients remain controversial.

METHODS

PTC patients treated with thyroidectomy between January 1997 and December 2011 at the First Affiliated Hospital of Zhejiang University (Zhejiang cohort) were included. Multivariate Cox regression analysis was conducted to identify independent recurrence predictors. Then, the nomogram model for predicting probability of recurrence was built.

RESULTS

According to Zhejiang cohort (N = 1,697), we found that the 10-year event-free survival (EFS) rates of PTC patients with early-stage (TNM stages I, II, and III) were not well discriminated (91.6%, 89.0%, and 90.7%; P=0.768). The multivariate Cox model identified age, bilaterality, tumor size, and nodal status as independent risk factors for tumor recurrence in PTC patients with TNM stages I-III. We then developed a nomogram with the C-index 0.70 (95% CI, 0.64 to 0.76), which was significantly higher (P < 0.0001) than the AJCC staging system (0.52). In the validation group, the C-index remained at a similar level.

CONCLUSIONS

In this study, we build up a new recurrence predicting system and establish a nomogram for early-stage PTC patients. This prognostic model may better predict individualized outcomes and conduct personalized treatments.

Prognostic Significance of CSN2, CD8, and MMR Status-Associated Nomograms in Patients with Colorectal Cancer

BACKGROUND

COP9 signalosome subunit 2 (CSN2) is believed to be involved in human cancer, but its prognostic significance in colorectal cancer (CRC) has not been elucidated.

PATIENTS AND METHODS

We retrospectively analyzed the expression of CSN2 andCD8+ tumor-infiltrating lymphocytes (TILs), and mismatch repair (MMR) status in 267 paraffin-embedded specimens using immunohistochemistry in a training cohort. A number of risk factors were used to form nomograms to evaluate survival, and Harrell's concordance index (C-index) was used to evaluate the predictive accuracy. Further validation was performed in an independent cohort of 238cases.

RESULTS

Low CSN2 expression and a low number of CD8 + TILs were significantly associated with diminished disease-free survival (DFS) and overall survival (OS) in CRC patients, and patients with MMR-deficient CRC had enhanced DFS and OS. Moreover, the multivariate Cox analysis identified CSN2, CD8 + TILs, and MMR status as independent prognostic factors for DFS and OS. Using these three markers and four clinicopathological risk variables, two nomograms were constructed and validated for predicting DFS and OS (C-index: training cohort, 0.836 (95% CI:0.804-0.868) and 0.841 (0.808-0.874), respectively; validation cohort, 0.801 (0.760-843) and 0.843 (0.806-0.881), respectively).

CONCLUSIONS

CSN2, CD8+ TILs, and MMR status were independent prognostic factors. The nomograms could be used to generate individualized predictions for DFS and OS.

Development and validation of a nomogram for predicting survival in Chinese han patients with resected colorectal cancer

BACKGROUND

Estimates of survival after curative colorectal cancer (CRC) surgery are the basis of patient care and treatment planning. A nomogram is a useful tool for individualized cancer prognosis.

METHODS

A total of 2450 patients with nonmetastatic CRC were included to develop a nomogram. Prognostic factors were identified and integrated by the Cox proportional hazards model. Then, we developed and validated a prognostic nomogram. The performance of this model was assessed by the concordance index (C-index) and a calibration curve. The nomogram was internally validated by bootstrapping and externally validated with a separate database of 299 patients from The Cancer Genome Atlas.

RESULTS

Age, T stage, N stage, histological type, tumor location, lymph-vascular invasion, preoperative carcinoembryonic antigen, and sample lymph nodes were integrated into the nomogram. The C-index of the nomogram for predicting overall survival was higher than that of the seventh edition American Joint Committee on Cancer TNM staging system (training data set, 0.76 vs 0.68, respectively; P < 0.001; validation data set, 0.78 vs 0.69, respectively; P = 0.003).

CONCLUSION

We developed a prognostic nomogram for patients with nonmetastatic CRC, which could provide a more individualized outcome prognostication than that afforded by the TNM staging system by using common clinicopathologic factors.

Nomogram Predicting Survival After Recurrence in Patients With Stage I to III Colon Cancer: A Nationwide Multicenter Study

BACKGROUND

Although a number of studies have been conducted to investigate factors affecting colon cancer recurrence and patient overall survival after surgical treatment, no prognostic risk models have been proposed for predicting survival specifically after postsurgical recurrence.

OBJECTIVE

We aimed to identify factors affecting the survival of the patients with recurrent colon cancer and to construct a nomogram for predicting their survival.

DESIGN

This was a retrospective study.

SETTINGS

This study used the Japanese Study Group for Postoperative Follow-Up of Colorectal Cancer database, which contains retrospectively collected data of all consecutive patients with stage I to III colorectal cancer who underwent surgical curative resection between 1997 and 2008 at 23 referral institutions.

PATIENTS

A total of 2563 patients with stage I to III colon cancer who experienced recurrence after surgery were included in the present study.

MAIN OUTCOME MEASURES

A nomogram predicting survival was constructed using a training cohort composed of patients from 15 hospitals (n = 1721) using a Cox regression hazard model analysis. The clinical applicability of this nomogram was validated in patients from the 8 remaining hospitals (the validation cohort; n = 842).

RESULTS

Eight factors (age, location of the primary tumor, histopathological type, positive lymph node status, presence of peritoneal metastasis, number of organs involved in the first recurrence, treatment for recurrence, and the interval between initial surgery and recurrence) were identified as nomogram variables. Our nomogram showed good calibration, with concordance indexes of 0.744 in the training cohort and 0.730 in the validation cohort. The survival curves stratified by the risk score calculated by the nomogram were almost identical for the training and validation cohorts.

LIMITATIONS

The study was conducted using the data until 2008, and more advanced chemotherapeutic agents and multidisciplinary therapies that might have improved the outcomes predicted by our nomogram were not available. In addition, treatment strategies for recurrence might differ between countries.

CONCLUSIONS

Our nomogram, which is based on a nationwide multicenter study, is the first statistical model predicting survival after recurrence in patients with stage I to III colon cancer. It promises to be of use in postoperative colon cancer surveillance. See Video Abstract at http://links.lww.com/DCR/A687.

Recurrence Risk After Up-to-Date Colon Cancer Staging, Surgery, and Pathology: Analysis of the Entire Swedish Population

BACKGROUND

Developments in the quality of care of patients with colon cancer have improved surgical outcome and thus the need for adjuvant chemotherapy.

OBJECTIVE

To investigate the recurrence rate in a large population-based cohort after modern staging, surgery, and pathology have been implemented.

DESIGN

This was a retrospective registry study.

SETTINGS

Data from patients included in the Swedish Colorectal Cancer Registry covering 99% of all cases and undergoing surgery for colon cancer stages I to III between 2007 and 2012 were obtained.

PATIENTS

In total, 14,325 patients who did not receive any neoadjuvant treatment, underwent radical surgery, and were alive 30 days after surgery were included.

MAIN OUTCOME MEASURES

Tumor and node classification and National Comprehensive Cancer Network-defined risk factors for recurrence were used to assess overall and stage-specific 5-year recurrence rates.

RESULTS

The median follow-up of nonrecurrent cases was 77 months (range, 47-118 mo). The 5-year recurrence rate was 5% in stage I, 12% in stage II, and 33% in stage III patients. In patients classified as having pT3N0 cancer with no or 1 risk factor, the 5-year recurrence rates were 9% and 11%. Risk factors for shorter time to recurrence were male sex, more advanced pT and pN classification, vascular and perineural invasion, emergency surgery, lack of central ligature, short longitudinal resection margin, postoperative complications, and, in stage III, no adjuvant chemotherapy.

LIMITATIONS

The registry does not contain some recently identified factors of relevance for recurrence rates, and some late recurrences may be missing.

CONCLUSIONS

The recurrence rate is less than that previously observed in historical materials, but current, commonly used risk factors are still useful in evaluating recurrence risks. Stratification by pT and pN classification and the number of risk factors enables the identification of large patient groups characterized by such a low recurrence rate that it is questionable whether adjuvant treatment is motivated. See Video Abstract at http://links.lww.com/DCR/A663.

Adjuvant Therapy for Colon Cancer: Genes, Genes… and the Patient in the Center

Although molecular subtype-based stratification and genomic signatures of increasing complexity are becoming a new strategy to guide therapeutic decisions in stage II/III colon cancer, several prognostic factors that can be easily obtained from formalin-fixed paraffin-embedded (FFPE) specimens should be considered to create combined models that better define individual patients' needs. Clin Cancer Res; 24(16); 3787-9. ©2018 AACRSee related article by Kandimalla et al., p. 3867.

Real-World Implications of Nonbiological Factors with Staging, Prognosis and Clinical Management in Colon Cancer

Background: The present study analyzed the nonbiological factors (NBFs) together with the American Joint Committee on Cancer (AJCC) Tumor-Node-Metastasis (TNM) staging system to generate a refined, risk-adapted stage for the clinical treatment of colon cancer. Methods: Eligible patients (N = 28,818) with colon cancer between 1 January 2010 and 31 December 2014, were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Kaplan-Meier curves and Cox proportional hazards regression, analyzed the probabilities of cancer-specific survival (CSS) in patients with colon cancer, with different NBF-TNM stages. Results: Insurance status, marital status, and median household income were significant prognostic NBFs in the current study (p < 0.05). The concordance index of NBF-TNM stage was 0.857 (95% confidence interval (CI) = 0.8472⁻0.8668). Multivariate Cox analyses, indicated that NBF1-stage was independently associated with a 50.4% increased risk of cancer-specific mortality in colon cancer (p < 0.001), which increased to 77.1% in non-metastatic colon cancer. NBF0-stage improved in CSS as compared to the NBF1-stage in the respective stages (p < 0.05). Conclusions: The new proposed NBF-stage was an independent prognostic factor in colon cancer. Effect of NBFs on the survival of colon cancer necessitates further clinical attention. Moreover, the incorporation of NBF-stage into the AJCC TNM staging system is essential for prognostic prediction, and clinical guidance of adjuvant chemotherapy in stage II and III colon cancer.

P-TNM staging system for colon cancer: combination of P-stage and AJCC TNM staging system for improving prognostic prediction and clinical management

AIM

This study focused on improving the American Joint Committee on Cancer TNM staging system and demonstrated an improvement in prognostic accuracy and clinical management of colon cancer using the P-TNM staging system.

PATIENTS AND METHODS

Eligible patients (N=56,800) were identified from the Surveillance, Epidemiology, and End Results database between January 1, 2010, and December 31, 2014. The P-stage (P0 or P1) was assigned to each patient based on age at diagnosis, tumor grade, and tumor size. The outcome of interest was cancer-specific survival (CSS). The Cox proportional hazards regression analyses were used to identify independent prognostic factors and analyze the CSS probabilities of patients with colon cancer having different P-TNM stages, respectively.

RESULTS

A total of 29,627 patients were assigned to P0-stage and 27,173 patients were assigned to P1-stage. The P1-stage was associated with a 98.1% increased risk of cancer-specific mortality (hazard ratio =1.981, 95% confidence interval =1.891-2.076, P<0.001), which was higher in patients with nonmetastatic colon cancer. The P1-stage patients had improvement in CSS compared with those in P0-stage in respective stages (P<0.001). Moreover, CSS decreased in stage I-P1 compared with stage IIA-P0 or IIIA-P0 (P<0.001), stage IIIA-P1 compared with stage IIA-P0 (P<0.001), stage IIB-P1 compared with stage IIIB-P0 or IIC-P0 (P<0.001), stage IIIB-P1 compared with stage IIC-P0 (P<0.001), and stage IIC-P1 compared with stage IIIC-P0 (P<0.001).

CONCLUSION

P-stage was an independent prognostic factor for colon cancer. This study strongly supported the incorporation of P-stage into the American Joint Committee on Cancer TNM staging system for a better approach to prognostication and, thus, more individualized risk-adaptive therapies in colon cancer.

GADD45B as a Prognostic and Predictive Biomarker in Stage II Colorectal Cancer

GADD45B acts as a member of the growth arrest DNA damage-inducible gene family, which has demonstrated to play critical roles in DNA damage repair, cell growth, and apoptosis. This study aimed to explore the potential relationship between GADD45B expression and tumor progression and evaluate the clinical value of GADD45B in stage II colorectal cancer (CRC). The expression patterns and prognostic value of GADD45B in CRC were analyzed based on The Cancer Genomic Atlas (TCGA). GADD45B expression features of 306 patients with stage II CRC and 201 patients with liver metastasis of CRC were investigated using immunochemical staining on tissue microarrays. Afterward, survival analysis and stratification analysis were performed in stage II to explore the prognostic and predictive significance of GADD45B. Overexpressed GADD45B is associated with poorer prognosis for CRC patients both in overall survival (OS) (p < 0.001) and disease-free survival (DFS) (p = 0.001) based on the TCGA database. Analysis results according to the stage II CRC cohort and the liver metastatic CRC cohort revealed that GADD45B was gradually upregulated in normal mucosa including primary colorectal cancer (PCC). Colorectal liver metastases (CLM) tissues were arranged in order (normal tissue vs. PCC p = 0.005 and PCC vs. CLM p = 0.001). The low GADD45B group had a significantly longer five-year OS (p = 0.001) and progression-free survival (PFS) (p < 0.001) than the high GADD45B group for the stage II patients. The multivariate Cox regression analysis results proved that the expression level of GADD45B was an independent prognostic factor for stage II after radical surgery (OS: Hazard Ratio (HR) 0.479, [95% confidence interval (CI) 0.305⁻0.753] and PFS:HR 0.490, [95% CI 0.336⁻0.714]). In high GADD45B expression subgroup of stage II cohort, the patients who underwent adjuvant chemotherapy had longer PFS than those who did not (p = 0.008). High expression levels of GADD45B is an independent prognostic factor of decreased OS and PFS in stage II CRC patients. The stage II CRC patients with high GADD45B expression might benefit from adjuvant chemotherapy.

Nomograms and risk scores for predicting the risk of oral cancer in different sexes: a large-scale case-control study

Background: Although previous studies have explored the associations of modifiable lifestyle factors with oral cancer risk, few studies integrated these factors and established predictive tools for oral cancer risk in different sexes. Methods: Using a case-control study design, a total of 978 oral cancer cases and 2646 healthy controls were recruited in this study. Nomograms were constructed according to significant factors in multivariable logistic regression. Risk scores were calculated based on the nomograms and quantified the risk of oral cancer using restricted cubic spline. Results: Multivariate analyses demonstrated that smoking, alcohol drinking, tea, intake of fish, seafood, vegetables, fruits, teeth loss, regular dental visits and repetitive dental ulcer were independent factors for male oral cancer. Passive smoking, age at first intercourse, cooking oil fumes exposure, tea, intake of beans, vegetables, fruits, teeth loss, regular dental visits and repetitive dental ulcer were associated with female oral cancer. Then, two nomograms were developed for predicting the probability of oral cancer in men and women with the C-index of 0.768 (95% CI: 0.723-0.813) and 0.700 (95% CI: 0.635-0.765), respectively. Restricted cubic splines graphically revealed the risk of oral cancer in individuals with different risk scores. Moreover, the risk escalated continuously with the increasing number of the risk scores among both sexes. Conclusions: Combining nomograms with risk scores developed in this study could precisely predict oral cancer occurrence and provide an accurate risk assessment.

Trends in presentation, treatment and survival of 1777 patients with colorectal cancer over a decade: a Biobank study

BACKGROUND

Most survival data in colorectal cancer (CRC) is derived from clinical trials or register-based studies. Hospital Biobanks, linked with hospital electronic records, could serve as a data-gathering method based on consecutively collected tumor samples. The aim of this Biobank study was to analyze survival of colorectal patients diagnosed and treated in a single-center university hospital over a period of 12 years, and to evaluate factors contributing to outcome.

MATERIAL AND METHODS

A total of 1777 patients with CRC treated during 2001-2012 were identified from the Auria Biobank, Turku, Finland. Longitudinal clinical information was collected from various hospital electronic records and date and cause of death obtained from Statistics Finland.

RESULTS

Cancer-specific, overall and disease-free survival was higher in patients diagnosed during 2004-2008 as compared with patients diagnosed in 2001-2003. Further improvement was not seen during years 2009-2012. Potential factors contributing to the improvement were introduction of multidisciplinary meetings, centralization of rectal cancer surgery, use of adjuvant chemotherapy and systematic preoperative radiotherapy of rectal cancer. The proportion of patients with stage I-IV CRC remained similar over the study period, but a marked decrease in non-metastatic rectal cancer with biopsy only (locally advanced disease) was observed. In stage I-III rectal cancer, Cox multivariate analysis suggested age, comorbidity, R1 resection, T staging and tumor grade as prognostic factors. In colon cancer, prognostic factors were age, comorbidity, gender and presence of lymph node metastases.

CONCLUSIONS

Organizational changes in the treatment of CRC patients made since 2004 coincide with improved survival in CRC and a marked reduction in locally advanced rectal cancers. The clinical presentation of CRC has remained similar between 2001 and 2012.

A novel nomogram individually predicting disease-specific survival after D2 gastrectomy for advanced gastric cancer

BACKGROUND

Few studies have shown nomograms that may predict disease-specific survival (DSS) probability after curative D2 gastrectomy for advanced gastric cancer (AGC), particularly among Chinese patients. This study sought to develop an elaborative nomogram that predicts long-term DSS for AGC in Chinese patients.

METHODS

A retrospective study was conducted on 6753 AGC patients undergoing D2 gastrectomy between January 1, 2000 and December 31, 2012 from three large medical hospitals in China. We assigned patients from Sun Yat-sen University Cancer Center to the training set, and patients from the First Affiliated Hospital of China Medical University and Tianjin Medical University Cancer Hospital to two separate external validation sets. A multivariate survival analysis was performed using Cox proportional hazards regression model in a training set, and a nomogram was constructed. Harrell's C-index was used to evaluate discrimination and calibration plots were used to validate similarities between survival probabilities predicted by the nomogram model and actual survival rates in two validation sets.

RESULTS

The multivariate Cox regression model identified age, tumor size, location, Lauren classification, lymphatic/venous invasion, depth of invasion, and metastatic lymph node ratio as covariates associated with survival. In the training set, the nomogram exhibited superior discrimination power compared with the 8th American Joint Committee on Cancer TNM classification (Harrell's C-index, 0.82 vs. 0.74; P < 0.001). In two validation sets, the nomogram's discrimination power was also excellent relative to TNM classification (C-index, 0.83 vs. 0.75 and 0.81 vs. 0.74, respectively; P < 0.001 for both). After calibration, the nomogram produced survival predictions that corresponded closely with actual survival rate.

CONCLUSIONS

The established nomogram was able to predict 3-, 5-, and 10-year DSS probabilities for AGC patients. Validation revealed that this nomogram exhibited excellent discrimination and calibration capacity, suggesting its clinical utility.

Nomograms for predicting disease progression in patients of Stage I non-small cell lung cancer treated with stereotactic body radiotherapy

Objective

Non-local progression is a major concern in non-small cell lung cancer (NSCLC) treated with stereotactic body radiotherapy (SBRT). Herein we aimed to create a pre-treatment prognostic nomogram for patients with Stage I NSCLC receiving SBRT.

Methods

We retrospectively studied 182 eligible patients. Patients were randomly divided into a model (70%) group and a validation (30%) group. In the model group, thirteen parameters consisting of patient, treatment, and tumor factors were studied and multivariate Cox proportional hazards regression was performed to identify independent predictors for survival outcome, based on which we developed clinical nomogram. The nomogram was externally validated in the validation group.

Results

Multivariate analysis showed that tumor size (P = 0.011) was the only factor correlated with 2-year overall survival, whereas 2-year locoregional control (LRC) was significantly related to tumor size (P = 0.024) and the maximum standardized uptake value (SUVmax) (P = 0.044), so does 2-year progression-free survival (PFS) (tumor size: P = 0.026; SUVmax: P = 0.038). Nomogram for 2-year LRC and 2-year PFS were created based on aforementioned results. The C-indexes for the nomograms to predict 2-year LRC and PFS were 0.816 and 0.804, respectively, in model group, and were 0.729 and 0.731, respectively, in the validation group. Calibration plots also showed that the model performed well.

Conclusions

Tumor of larger size and higher SUVmax predisposed patients to early onset of locoregional and distant progression. The nomogram developed in our study would be helpful in clinical decision-making and selection of patients who may benefit from more rigorous follow-up and aggressive systemic treatment plan.

Predictive Nomogram for Recurrence of Stage I Colorectal Cancer After Curative Resection

BACKGROUND

Patients with stage I colorectal cancer (CRC) have excellent prognosis after curative surgery. However, approximately 5% to 10% of patients experience recurrence and have a poor prognosis. Because the incidence of stage I CRC is increasing with active screening programs worldwide, a more accurate and easy-to-use predictive tool for recurrence is becoming more important. This study aimed to develop a predictive nomogram for recurrence in stage I CRC.

PATIENTS AND METHODS

A total of 1538 patients who underwent curative surgery for stage I CRC were enrolled. Predictive factors for recurrence were determined by multivariate Cox regression model and were used to develop a predictive nomogram. This model was internally validated, and performance was evaluated through calibration plots.

RESULTS

The cumulative recurrence rate at 5 years after surgery for stage I CRC was 5.3%. In multivariate Cox analysis, independent predictors of recurrence were tumor location at rectum, pT2 stage, and presence of lymphovascular invasion. The 5-year recurrence rate was significantly different depending on the number of risk factors (0.7% for 0, 5.8% for 1, and 9.7% for ≥ 2 risk factors). On this basis, a nomogram for recurrence-free survival was developed and internally validated. The concordance index of the nomogram was 0.71, and the performance was acceptable.

CONCLUSION

We developed and internally validated a nomogram that can predict postoperative recurrence in stage I CRC patients. This nomogram may be used to more accurately stratify the risk of recurrence and to perform personalized postoperative surveillance in stage I CRC patients.

Development and Validation of a Prediction Model for Postoperative Peritoneal Metastasis After Curative Resection of Colon Cancer

BACKGROUND

Detection of peritoneal metastasis remains challenging due to the limited sensitivity of current examination methods. This study aimed to establish a prediction model for estimating the individual risk of postoperative peritoneal metastasis from colon cancer to facilitate early interventions for high-risk patients.

METHODS

This study investigated 1720 patients with stages 1-3 colon cancer who underwent curative resection at the University of Tokyo Hospital between 1997 and 2015. The data for the patients were retrospectively retrieved from their medical records. The risk score was developed using the elastic net techniques in a derivation cohort (973 patients treated in 1997-2009) and validated in a validation cohort (747 patients treated in 2010-2015).

RESULTS

The factors selected using the elastic net approaches included the T stage, N stage, number of examined lymph nodes, preoperative carcinoembryonic antigen level, large bowel obstruction, and anastomotic leakage. The model had good discrimination (c-index, 0.85) and was well-calibrated after application of the bootstrap resampling method. Discrimination and calibration were favorable in external validation (c-index, 0.83). The model presented a clear stratification of patients' risk for postoperative peritoneal recurrence, and decision curve analysis showed its net benefit across a wide range of threshold probabilities.

CONCLUSIONS

This study established and validated a prediction model that can aid clinicians in optimizing postoperative surveillance and therapeutic strategies according to the individual patient risk of peritoneal recurrence.

Prognostic significance of cystatin SN associated nomograms in patients with colorectal cancer

Colorectal cancer (CRC) is one of most malignant tumors, mainly due to its high rate of metastasis and recurrence. The prognosis of CRC is difficult due to early CRC patients have no specific symptoms. Therefore, it is emergent to identify a biomarker for CRC prognosis. Cystatin SN (CST1) shows elevated expression in many tumors, but its role in CRCs is still unknown. Through immunohistochemistry analysis, we found that CST1 was upregulated in CRC samples. The survival analysis had demonstrated that high CST1 expression was closely associated with poor clinical status, providing that CST1 plays a role in CRC tumorigenesis. Furthermore, nomograms were generated using CST1 levels and other factors to evaluate survival of CRCs. We evaluated the reliabilities of these nomograms using an independent cohort of 141 CRC cases and found that high CST1 expression is linked to low survival, which is consistent with the clinical results. Thus, we could predict the survival of a CRC patient via these nomograms. In addition, the multivariate analysis identified CST1 as an independent prognostic factor for CRCs, providing CST1 as a biomarker for CRC prognosis. Taken together, our studies revealed a close relationship between CST1 and CRCs, suggesting that CST1 possibly acts as a marker for CRC prognosis and a target for CRC therapy.

[Nomograms in routine clinical practice: Methodology, interest and limitations]

In order to help the clinician, mathematical models including several clinical and pathological variables are proposed in the literature with the aim to predict the occurrence of an event of interest. Nomograms allow individual prognosis for each patient. When they are developed, validated and correctly used, nomograms can provide important information for patients' care. But, despite the strong interest in nomograms in oncology, statistical methodologies used remain unknown from the medical community. This paper presents the major steps in the development, the validation and the clinical use of nomograms. Examples are given to illustrate these different points and the limits of this methodology. Finally, guidelines on the use of nomograms are proposed for clinicians.

Insufficient Lymph Node Sampling in Patients with Colorectal Cancer Perforation is Associated with an Adverse Oncological Outcome

BACKGROUND

The impact of lymph node (LN) dissection on long-term outcomes for patients with colorectal cancer (CRC) perforation remains unclear. We aim to investigate factors associated with poor prognosis and recurrence in patients with CRC, with special reference to cancer perforation and LN dissection.

METHODS

The subjects comprised 550 patients who underwent colorectal surgery for CRC at Stage II or III (TNM classification) between February 2006 and November 2013. Short- and long-term outcomes of patients with or without CRC perforation were evaluated. We also sought risk factors on poor prognosis, focusing on LN dissection in patients with CRC perforation.

RESULTS

A total of 508 underwent surgery for CRC without perforation (the non-perforation group) and 39 for CRC with perforation (the perforation group). Both overall survival and recurrence-free survival rates were significantly lower in the perforation group than in the non-perforation group (overall survival, P = 0.009; recurrence-free survival, P < 0.001). The relapse rates at the peritoneum (P = 0.002), lung (P = 0.007) and LNs (P = 0.021) were significantly higher in the perforation group than in the non-perforation group. Multivariable Cox proportional hazards model revealed that CRC perforation (hazard ratio [HR] 2.55, 95 % confidential interval [CI] 1.16-4.98, P = 0.022), LN dissection <12 (HR 1.83, 95 % CI 1.07-3.13, P = 0.027), and Stage III (HR 1.79, 95 % CI 1.06-3.08, P = 0.031) were significant and independent risk factors for poor prognosis.

CONCLUSIONS

Conducting <12 LN dissections independently increased the risk of reduction in overall survival for patients with CRC perforation. Thus, radical LN dissections should be performed to improve patients' survival rates, when patients' general and surgical conditions allow.

Hazard rate of tumor recurrence over time in patients with colon cancer: implications for postoperative surveillance from three Japanese Foundation for Multidisciplinary Treatment of Cancer (JFMC) clinical trials

Purpose: Reliable risk estimates of recurrence are necessary to establish optimal postoperative surveillance strategies. The purpose of the present study was to clarify changes in the hazard rate (HR) for tumor recurrence over time in Japanese patients with colon cancer. Methods: Data for 3984 patients from three clinical trials evaluating the benefit of adjuvant chemotherapy for colon cancer were analyzed. Estimated HRs were plotted over time for the entire cohort, as well as for node-positive and node-negative patients separately. The changes in risk were further analyzed according to eight clinical variables, and factors predictive of early (<3 years) and late (>3 years) recurrence were explored using Cox's regression analysis. Results: In node-positive patients, there was a prominent HR peak 0.6 years after surgery, whereas HR remained at consistently low levels in node-negative patients. In node-positive patients, HR decreased steadily until 3 years, after which the decline in HR plateaued. Those with T4 tumors had a prominent HR peak around 1 year, including node-negative patients. The HR for T1/T2 Stage III colon cancers showed a similar pattern as that for T1-T3 node-negative colon cancers. Cox regression analysis revealed that a lack of adjuvant chemotherapy, positive node status, T3/T4 factors, and male gender predict early recurrence, whereas patients with lymph node metastasis, T4 tumors, and a lesser extent of lymph node removal have a higher risk of recurrence 3-4 years after surgery (P<0.05). Conclusion: The present study supports the concept of intensive surveillance during the first 3 years after curative resection. However, a reduction in surveillance intensity may be acceptable for patients with T3 Stage II and T1/T2 Stage III colon cancer.

Development and validation of a prognostic nomogram for colorectal cancer after radical resection based on individual patient data from three large-scale phase III trials

Background

Few prediction models have so far been developed and assessed for the prognosis of patients who undergo curative resection for colorectal cancer (CRC).

Materials and Methods

We prepared a clinical dataset including 5,530 patients who participated in three major randomized controlled trials as a training dataset and 2,263 consecutive patients who were treated at a cancer-specialized hospital as a validation dataset. All subjects underwent radical resection for CRC which was histologically diagnosed to be adenocarcinoma. The main outcomes that were predicted were the overall survival (OS) and disease free survival (DFS). The identification of the variables in this nomogram was based on a Cox regression analysis and the model performance was evaluated by Harrell's c-index. The calibration plot and its slope were also studied. For the external validation assessment, risk group stratification was employed.

Results

The multivariate Cox model identified variables; sex, age, pathological T and N factor, tumor location, size, lymphnode dissection, postoperative complications and adjuvant chemotherapy. The c-index was 0.72 (95% confidence interval [CI] 0.66-0.77) for the OS and 0.74 (95% CI 0.69-0.78) for the DFS. The proposed stratification in the risk groups demonstrated a significant distinction between the Kaplan–Meier curves for OS and DFS in the external validation dataset.

Conclusions

We established a clinically reliable nomogram to predict the OS and DFS in patients with CRC using large scale and reliable independent patient data from phase III randomized controlled trials. The external validity was also confirmed on the practical dataset.

Nomogram individually predicts the overall survival of patients with gastroenteropancreatic neuroendocrine neoplasms

Background:

The current study aimed to establish a novel nomogram to predict the overall survival of individual Chinese patients with gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs). Furthermore, this study sought to externally validate this nomogram using the Surveillance, Epidemiology, and End Results (SEER) database.

Methods:

The records of 1183 patients with GEP-NENs treated at five high-capacity institutions in China between 2005 and 2015 were retrospectively analysed. In addition, 10 236 GEP-NEN cases from the SEER database were included as an external validation set.

Results:

A multivariate analysis using Cox proportional hazards (PHs) regression was performed, and a nomogram was constructed. Discrimination, calibration, and external validation were performed using the SEER data set. The multivariate Cox model indicated that age, tumour size, differentiation, lymph node metastases, and distant metastases were independent covariates associated with survival. With respect to the training set, the nomogram exhibited better discrimination power than TNM classification (Harrell’s concordance index (C-index): 0.837 vs 0.784, P=0.006). Discrimination was also excellent and superior to that of TNM classification for the SEER-based validation set (C-index: 0.808 vs 0.717, P<0.001). The calibrated nomogram predicted a survival rate that closely corresponded to the actual survival rate.

Conclusions:

We developed a nomogram that predicted the 3- and 5-year overall survival rates of patients with GEP-NENs. Validation revealed excellent discrimination and calibration for this nomogram, suggesting that it exhibits satisfactory clinical utility that might improve individualised predictions of survival risks and lead to the creation of additional clinical therapies.

Extramural perineural invasion in pT3 and pT4 rectal adenocarcinoma as prognostic factor after preoperative chemoradiotherapy

Perineural invasion (PNI) is widely studied in malignant tumors, and its prognostic significance is well demonstrated in the head and neck and prostate carcinomas, but its significance in rectal cancer is controversial. Most studies have focused on evaluating mural PNI (mPNI); however, extramural PNI (ePNI) may influence the prognosis after rectal cancer resection. We evaluated the prognostic value of ePNI compared with mPNI and with non-PNI, in rectal resections after preoperative chemoradiotherapy in 148 patients with pT3 and pT4 rectal carcinomas. PNI was identified in 35 patients (23.6%), 60% of which were in the mPNI group. Factors associated with PNI were tumor invasion depth, lymph node metastasis, lymphovascular invasion, and venous invasion; patients with PNI were more likely to have positive resection margins (65.7% versus 11.6%). ePNI, compared with mPNI, was associated with female sex (64.3% versus 28.6%), positive surgical margins (42.8% versus 28.6%), recurrence (50% versus 28.6%), and death (92.9% versus 28.6%). The 5-year disease-specific survival rate was 78.1% for patients without PNI, compared with 63.7% for the mPNI group and 26.4% for the ePNI group (P<.001). On multivariate analysis, the independent adverse prognostic factors were ePNI (odds ratio [OR], 22.17; 95% confidence interval [CI], 17.03-24.58; P<.001), overall recurrence (OR, 9.19; CI, 6.11-10.63; P=.002), clinical stage IV (OR, 8.56; CI, 6.34-9.47; P=.003), and positive surgical margin (OR, 3.95; CI, 2.00-4.28; P=.047). In conclusion, we demonstrated the prognostic effect of ePNI for disease-specific survival in surgically resected pT3-pT4 rectal cancer patients with preoperative chemoradiotherapy.

Baseline serum albumin and other common clinical markers are prognostic factors in colorectal carcinoma: A retrospective cohort study

The aim of the present study was to define the prognostic role of baseline serum albumin (BSA) in colorectal cancer (CRC) across tumor-node-metastasis (TNM) stages and other well defined prognostic factors. Many prognostic models in medicine employ BSA to define or refine treatments in very specific settings; in CRC, BSA has been found to be a prognostic factor as well. A retrospective cohort study of consecutive patients with CRC demonstrated by biopsy, who attended a cancer center during a 7-year period. Multivariate analysis was utilized to define prognostic factors associated with overall survival (OS) employing the Cox model. In this retrospective cohort study, 1465 patients were included; 46.6% were females and 53.4% males (mean age, 59.1 years). Mean BSA was inversely correlated with TNM stages. By multivariate analysis, it was an independent explanatory variable. TNM stages, "R" classification, age, lymphocyte count, neutrophil/platelet ratio, neutrophil/lymphocyte ratio, platelet/lymphocyte ratio, postoperative morbidity, and BSA were independently associated with OS. Morbidities, surgery type, chemotherapy, and radiotherapy were considered confounders after adjusting by TNM stages. BSA is a significant and independent prognostic factor in patients with CRC, and its effect is maintained across TNM strata and other well known clinical prognostic factors. It can be easily used in prognostic models and should be employed to stratify prognosis in therapeutic randomized clinical trials.

Prognostic Value of E-cadherin-, CD44-, and MSH2-associated Nomograms in Patients With Stage II and III Colorectal Cancer

BACKGROUND

To evaluate the prognostic value of E-cadherin, CD44, and MSH2 expression for colorectal cancer (CRC) and construct nomograms that can predict prognosis.

METHODS

We retrospectively analyzed the expression of E-cadherin, CD44, and MSH2 in 223 paraffin-embedded stage II and III CRC specimens using immunohistochemistry in the training cohort. Their prognostic values were assessed using Kaplan-Meier curves and univariate and multivariate COX regression models. Moreover, a number of risk factors were used to form nomograms to evaluate survival, and Harrell's concordance index (C-index) was used to evaluate the predictive accuracy. Further validation of the nomograms was performed in an independent cohort of 115 cases.

RESULTS

Low E-cadherin expression and low CD44 expression were significantly associated with diminished overall survival (OS) and disease-free survival (DFS) in stage II and III CRC patients and patients with negative MSH2 expression had better clinical outcomes. Moreover, the multivariate COX analysis identified E-cadherin, CD44 and MSH2 expression as independent prognostic factors for DFS and OS. Using these three markers and three clinicopathological risk variables, two nomograms were constructed and externally validated for predicting OS and DFS (C-index: training cohort, 0.779 (95% CI 0.722-0.835) and 0.771 (0.720-0.822), respectively; validation cohort, 0.773 (0.709-0.837) and 0.670 (0.594-0.747), respectively).

CONCLUSION

The expression levels of E-cadherin, CD44 and MSH2 were independent prognostic factors for stage II and III CRC patients. By incorporating clinicopathological features and these biomarkers, we have established two nomograms that could be used to make individualized predictions for OS and DFS.

Nomogram for predicting recurrence in stage II colorectal cancer

BACKGROUND

There have been no established criteria to distinguish patients at high and low risk of recurrence in stage II colorectal cancer. Several risk factors have been identified but recurrence could not be fully predicted by each factor alone. This retrospective study sought to develop a nomogram for accurate prediction of recurrence in stage II colorectal cancer.

MATERIAL AND METHODS

We reviewed the data for 4167 patients with stage II colorectal cancer who underwent surgery between January 1997 and December 2006. The risk factors for recurrence were identified, and a nomogram for recurrence was created using the factors. The performance of the nomogram was assessed with a bootstrapped-concordance index and calibration plots.

RESULTS

Sex, carcinoembryonic antigen, tumor location, tumor depth, lymphatic invasion, venous invasion and number of lymph nodes studied were significantly associated with recurrence. A nomogram for five-year freedom from recurrence was created with these factors. The bootstrapped-concordance index of the nomogram was 0.64, and it was well calibrated.

CONCLUSIONS

Our nomogram can be a useful tool for accurate prediction of recurrence in stage II colorectal cancer.

Preoperative carcinoembryonic antigen and prognosis of colorectal cancer. An independent prognostic factor still reliable

To evaluate whether, in a sample of patients radically treated for colorectal carcinoma, the preoperative determination of the carcinoembryonic antigen (p-CEA) may have a prognostic value and constitute an independent risk factor in relation to disease-free survival. The preoperative CEA seems to be related both to the staging of colorectal neoplasia and to the patient's prognosis, although this-to date-has not been conclusively demonstrated and is still a matter of intense debate in the scientific community. This is a retrospective analysis of prospectively collected data. A total of 395 patients were radically treated for colorectal carcinoma. The preoperative CEA was statistically compared with the 2010 American Joint Committee on Cancer (AJCC) staging, the T and N parameters, and grading. All parameters recorded in our database were tested for an association with disease-free survival (DFS). Only factors significantly associated (P < 0.05) with the DFS were used to build multivariate stepwise forward logistic regression models to establish their independent predictors. A statistically significant relationship was found between p-CEA and tumor staging (P < 0.001), T (P < 0.001) and N parameters (P = 0.006). In a multivariate analysis, the independent prognostic factors found were: p-CEA, stages N1 and N2 according to AJCC, and G3 grading (grade). A statistically significant difference (P < 0.001) was evident between the DFS of patients with normal and high p-CEA levels. Preoperative CEA makes a pre-operative selection possible of those patients for whom it is likely to be able to predict a more advanced staging.

The development and validation of the AMPREDICT model for predicting mobility outcome after dysvascular lower extremity amputation

OBJECTIVE

The objective of this study was the development of AMPREDICT-Mobility, a tool to predict the probability of independence in either basic or advanced (iBASIC or iADVANCED) mobility 1 year after dysvascular major lower extremity amputation.

METHODS

Two prospective cohort studies during consecutive 4-year periods (2005-2009 and 2010-2014) were conducted at seven medical centers. Multiple demographic and biopsychosocial predictors were collected in the periamputation period among individuals undergoing their first major amputation because of complications of peripheral arterial disease or diabetes. The primary outcomes were iBASIC and iADVANCED mobility, as measured by the Locomotor Capabilities Index. Combined data from both studies were used for model development and internal validation. Backwards stepwise logistic regression was used to develop the final prediction models. The discrimination and calibration of each model were assessed. Internal validity of each model was assessed with bootstrap sampling.

RESULTS

Twelve-month follow-up was reached by 157 of 200 (79%) participants. Among these, 54 (34%) did not achieve iBASIC mobility, 103 (66%) achieved at least iBASIC mobility, and 51 (32%) also achieved iADVANCED mobility. Predictive factors associated with reduced odds of achieving iBASIC mobility were increasing age, chronic obstructive pulmonary disease, dialysis, diabetes, prior history of treatment for depression or anxiety, and very poor to fair self-rated health. Those who were white, were married, and had at least a high-school degree had a higher probability of achieving iBASIC mobility. The odds of achieving iBASIC mobility increased with increasing body mass index up to 30 kg/m² and decreased with increasing body mass index thereafter. The prediction model of iADVANCED mobility included the same predictors with the exception of diabetes, chronic obstructive pulmonary disease, and education level. Both models showed strong discrimination with C statistics of 0.85 and 0.82, respectively. The mean difference in predicted probabilities for those who did and did not achieve iBASIC and iADVANCED mobility was 33% and 29%, respectively. Tests for calibration and observed vs predicted plots suggested good fit for both models; however, the precision of the estimates of the predicted probabilities was modest. Internal validation through bootstrapping demonstrated some overoptimism of the original model development, with the optimism-adjusted C statistic for iBASIC and iADVANCED mobility being 0.74 and 0.71, respectively, and the discrimination slope 19% and 16%, respectively.

CONCLUSIONS

AMPREDICT-Mobility is a user-friendly prediction tool that can inform the patient undergoing a dysvascular amputation and the patient's provider about the probability of independence in either basic or advanced mobility at each major lower extremity amputation level.

Validation of a rectal cancer outcome prediction model with a cohort of Chinese patients

The risk of local recurrence (LR), distant metastases (DM) and overall survival (OS) of locally advanced rectal cancer after preoperative chemoradiation can be estimated by prediction models and visualized using nomograms, which have been trained and validated in European clinical trial populations. Data of 277 consecutive locally advanced rectal adenocarcinoma patients treated with preoperative chemoradiation and surgery from Shanghai Cancer Center, were retrospectively collected and used for external validation. Concordance index (C-index) and calibration curves were used to assess the performance of the previously developed prediction models in this routine clinical validation population. The C-index for the published prediction models was 0.72 ± 0.079, 0.75 ± 0.043 and 0.72 ± 0.089 in predicting 2-year LR, DM and OS in the Chinese population, respectively. Kaplan-Meier curves indicated good discriminating performance regarding LR, but could not convincingly discriminate a low-risk and medium-risk group for distant control and OS. Calibration curves showed a trend of underestimation of local and distant control, as well as OS in the observed data compared with the estimates predicted by the model.

In conclusion, we externally validated three models for predicting 2-year LR, DM and OS of locally advanced rectal cancer patients who underwent preoperative chemoradiation and curative surgery with good discrimination in a single Chinese cohort. However, the model overestimated the local control rate compared to observations in the clinical cohort. Validation in other clinical cohorts and optimization of the prediction model, perhaps by including additional prognostic factors, may enhance model validity and its applicability for personalized treatment of locally advanced rectal cancer.

Nomograms to predict survival after colorectal cancer resection without preoperative therapy

Background

The predictive accuracy of the American Joint Committee on Cancer (AJCC) stages of colorectal cancer (CRC) is mediocre. This study aimed to develop postoperative nomograms to predict cancer-specific survival (CSS) and overall survival (OS) after CRC resection without preoperative therapy.

Methods

Eligible patients with stage I to IV CRC (n = 56072) diagnosed from 2004 to 2010 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. The patients were allocated into training (n = 27,700), contemporary (n = 3158), and prospective (n = 25,214) validation cohorts. Clinically important variables were incorporated and selected using the Akaike information criterion in multivariate Cox regressions to derive nomograms with the training cohort. The performance of the nomograms was assessed and externally testified using the concordance index (c-index), bootstrap validation, calibration, time-dependent receiver-operating characteristic curves, Kaplan–Meier curves, mosaic plots, and decision curve analysis (DCA). Performance of the conventional AJCC stages was also compared with the nomograms using similar statistics.

Results

The nomograms for CSS and OS shared common predictors: sex, age, race, marital status, preoperative carcinoembryonic antigen status, surgical extent, tumor size, location, histology, differentiation, infiltration depth, lymph node count, lymph node ratio, and metastasis. The c-indexes of the nomograms for CSS and OS were 0.816 (95 % CI 0.810–0.822) and 0.777 (95 % CI 0.772–0.782), respectively. Performance evaluations showed that the nomograms achieved considerable predictive accuracy, appreciable reliability, and significant clinical validity with wide practical threshold probabilities, while the results remained reproducible when applied to the validation cohorts. Additionally, model comparisons and DCA proved that the nomograms excelled in stratifying each AJCC stage into three significant prognostic subgroups, allowing for more robust risk classification with an improved net benefit.

Conclusions

We propose two prognostic nomograms that exhibit improved predictive accuracy and net benefit for patients who have undergone CRC resection. The established nomograms are intended for risk assessment and selection of suitable patients who may benefit from adjuvant therapy and intensified follow-up after surgery. Independent external validations may still be required.

The prognostic role of lymphovascular invasion in urothelial carcinoma of the bladder

Outcome prediction in patients with bladder cancer has improved through the development of nomograms and predictive models. However, integration of further characteristics such as lymphovascular invasion (LVI) might increase the accuracy and clinical utility of these instruments. Assessment and reporting of LVI in specimens from transurethral resection of the bladder tumour (TURBT) or biopsy in patients with non-muscle-invasive bladder cancer (NMIBC) or muscle-invasive bladder cancer (MIBC) might enable improved staging, prognostication and clinical decision-making. In NMIBC, presence of LVI in TURBT and biopsy samples seems to be associated with understaging and increased risks of disease recurrence and progression. In MIBC, presence of LVI is associated with features of aggressive disease and predicts recurrence and survival. Integration of LVI status into predictive models might aid clinical decision-making regarding intravesical instillation schedules and regimens, early radical cystectomy in patients with high-grade T1 disease and perioperative chemotherapy. However, LVI assessment is hampered by insufficient reproducibility and reliability, lack of routine evaluation and limited concordance between findings in TURBT and radical cystectomy specimens. Standardization of the pathological criteria defining LVI is warranted to improve its reporting in routine clinical practice and its utility as a care-changing prognostic marker.

Predictive models in cancer management: A guide for clinicians

BACKGROUND

Predictive tools in cancer management are used to predict different outcomes including survival probability or risk of recurrence. The uptake of these tools by clinicians involved in cancer management has not been as common as other clinical tools, which may be due to the complexity of some of these tools or a lack of understanding of how they can aid decision-making in particular clinical situations.

AIMS

The aim of this article is to improve clinicians' knowledge and understanding of predictive tools used in cancer management, including how they are built, how they can be applied to medical practice, and what their limitations may be.

METHODS

Literature review was conducted to investigate the role of predictive tools in cancer management.

RESULTS

All predictive models share similar characteristics, but depending on the type of the tool its ability to predict an outcome will differ. Each type has its own pros and cons, and its generalisability will depend on the cohort used to build the tool. These factors will affect the clinician's decision whether to apply the model to their cohort or not.

CONCLUSIONS

Before a model is used in clinical practice, it is important to appreciate how the model is constructed, what its use may add over and above traditional decision-making tools, and what problems or limitations may be associated with it. Understanding all the above is an important step for any clinician who wants to decide whether or not use predictive tools in their practice.

Clinical Nomogram for Predicting Survival of Esophageal Cancer Patients after Esophagectomy

The aim of this study was to construct an effective clinical nomogram for predicting the survival of esophageal cancer patients after esophagectomy. We identified esophageal cancer patients (n = 4,281) who underwent esophagectomy between 1988 and 2007 from the Surveillance, Epidemiology, and End Results (SEER) 18 registries database. Clinically significant parameters for survival were used to construct a nomogram based on Cox regression analyses. The model was validated using bootstrap resampling and a Chinese cohort (n = 145). A total of 4,109 patients from the SEER database were included for analysis. The multivariate analyses showed that the factors of age, race, histology, tumor site, tumor size, grade and depth of invasion, and the numbers of metastases and retrieved nodes were independent prognostic factors. All of these factors were selected into the nomogram. The nomogram showed a clear prognostic superiority over the seventh AJCC-TNM classification (C-index: SEER cohort, 0.716 vs 0.693, respectively; P < 0.01; Chinese cohort, 0.699 vs 0.680, respectively; P < 0.01). Calibration of the nomogram predicted the probabilities of 3- and 5-year survival, which corresponded closely with the actual survival rates. This novel prognostic model may improve clinicians’ abilities to predict individualized survival and to make treatment recommendations.