Nomogram predicting cancer-specific mortality in early-onset rectal cancer: a competing risk analysis

Mortality patterns of patients with tonsillar squamous cell carcinoma: a population-based study

Objective

Tonsillar squamous cell carcinoma (TSCC) and second primary malignancies (SPMs) are the most common causes of mortality in patients with primary TSCC. However, the competing data on TSCC-specific death (TSD) or SPM-related death in patients with TSCC have not been evaluated. This study aimed to analyze the mortality patterns and formulate prediction models of mortality risk caused by TSCC and SPMs.

Methods

Data on patients with a first diagnosis of TSCC were extracted as the training cohort from the 18 registries comprising the Surveillance, Epidemiology, and End Results (SEER) database. A competing risk approach of cumulation incidence function was used to estimate cumulative incidence curves. Fine and gray proportional sub-distributed hazard model analyses were performed to investigate the risk factors of TSD and SPMs. A nomogram was developed to predict the 5- and 10-year risk probabilities of death caused by TSCC and SPMs. Moreover, data from the 22 registries of the SEER database were also extracted to validate the nomograms.

Results

In the training cohort, we identified 14,530 patients with primary TSCC, with TSCC (46.84%) as the leading cause of death, followed by SPMs (26.86%) among all causes of death. In the proportion of SPMs, the lungs and bronchus (22.64%) were the most common sites for SPM-related deaths, followed by the larynx (9.99%), esophagus (8.46%), and Non-Melanoma skin (6.82%). Multivariate competing risk model showed that age, ethnicity, marital status, primary site, summary stage, radiotherapy, and surgery were independently associated with mortality caused by TSCC and SPMs. Such risk factors were selected to formulate prognostic nomograms. The nomograms showed preferable discrimination and calibration in both the training and validation cohorts.

Conclusion

Patients with primary TSCC have a high mortality risk of SPMs, and the competing risk nomogram has an ideal performance for predicting TSD and SPMs-related mortality. Routine follow-up care for TSCC survivors should be expanded to monitor SPMs.

Prediction of liver and lung metastases in patients with early-onset colorectal cancer by nomograms based on heterogeneous and homogenous risk factors

BACKGROUND

Identifying the risk factors for distant metastasis in early-onset colorectal cancer (EOCRC) is crucial for elucidating its etiology and facilitating preventive treatment. This study aims to characterize the variability in EOCRC incidence and discern both heterogeneous and homogeneous risk factors associated with synchronous liver, lung, and hepato-lung metastases.

METHODS

This study included patients with EOCRC enrolled in the SEER database between 2010 and 2015 and divided patients into three groups by synchronous liver, lung, and hepato-lung metastases. Each group of patients with different metastasis types was randomly assigned to the development and validation cohort in a ratio of 7:3. Logistic regression was used to analyze the heterogeneous and homogenous risk factors for synchronous liver, lung, and hepato-lung metastases in the development cohort of patients. Nomograms were built to calculate the risk of metastasis, and the receiver operating characteristic (ROC) curve and calibration curve were used to quantitatively evaluate their performance.

RESULTS

A total of 16,336 eligible patients with EOCRC were included in this study, of which 17.90% (2924/16,336) had distant metastases. The overall incidences of synchronous liver, lung, and hepato-lung metastases were 11.90% (1921/16,146), 2.42% (390/16,126), and 1.50% (241/16,108), respectively. Positive CEA values before treatment, increased lymphatic metastases, and deeper invasion of intestinal wall were positively correlated with three distant types of metastases. On the contrary, the correlation of age, ethnicity, location of primary tumor, and histologic grade among the three types was inconsistent. The ROC curve and calibration curve proved to have fine performance in predicting distant metastases of EOCRC.

CONCLUSIONS

There are significant differences in the incidence of distant metastases in EOCRC, and related risk factors are heterogeneous and homogenous. Although limited risk factors were incorporated in this study, the established nomograms indicated good predictive performance.

Development and validation of a competitive risk model in patients with rectal cancer: based on SEER database

BACKGROUND

Rectal cancer is one of the most common malignancies. To predict the specific mortality risk of rectal cancer patients, we constructed a predictive nomogram based on a competing risk model.

METHODS

The information on rectal cancer patients was extracted from the SEER database. Traditional survival analysis and specific death analysis were performed separately on the data.

RESULTS

The present study included 23,680 patients, with 16,580 in the training set and 7100 in the validation set. The specific mortality rate calculated by the competing risk model was lower than that of the traditional survival analysis. Age, Marriage, Race, Sex, ICD-O-3Hist/Behav, Grade, AJCC stage, T stage, N stage, Surgery, Examined LN, RX SUMM-SURG OTH, Chemotherapy, CEA, Deposits, Regional nodes positive, Brain, Bone, Liver, Lung, Tumor size, and Malignant were independent influencing factors of specific death. The overall C statistic of the model in the training set was 0.821 (Se = 0.001), and the areas under the ROC curve for cancer-specific survival (CSS) at 1, 3, and 5 years were 0.842, 0.830, and 0.812, respectively. The overall C statistic of the model in the validation set was 0.829 (Se = 0.002), and the areas under the ROC curve for CSS at 1, 3, and 5 years were 0.851, 0.836, and 0.813, respectively.

CONCLUSIONS

The predictive nomogram based on a competing risk model for time-specific mortality in patients with rectal cancer has very desirable accuracy. Thus, the application of the predictive nomogram in clinical practice can help physicians make clinical decisions and follow-up strategies.

Prediction of death probability in adenocarcinoma of the transverse colon: competing-risk nomograms based on 21,469 patients

PURPOSE

Tumors in parts of the colon other than the transverse colon have been well studied, but little is known about adenocarcinoma of the transverse colon (ATC).The aim of this study was to construct nomograms using competing-risk model for accurately predicting the probability of cancer-specific and non-cancer-specific death in patients with ATC.

METHODS

Data on eligible patients recorded during 2000-2019 in the Surveillance, Epidemiology, and End Results database were extracted and screened. Factors that influencing prognosis were screened for death from ATC (DATC) and death from other causes (DOC) using competing-risk analysis, including univariate and multivariate analyses based on Gray's test and the Fine-Gray model, respectively. Independent prognostic factors were identified and nomograms were constructed. For comparison, we also constructed a Cox model and an AJCC stage-only competing-risk model (AJCC model) for patients with DATC. Performance evaluations of the nomograms and comparison between the models were performed using calibration plots, Harrell's concordance index (C-index), receiver operating characteristic (ROC) curves, and the areas under the ROC curve (AUCs). The nomograms and models were validated using a validation cohort. The net reclassification index, integrated discrimination improvement, decision curves, and risk stratification were not assessed because no accepted methods were suited for competing-risk model.

RESULTS

This study included 21,469 patients with ATC, and 17 and 9 independent influencing factors were identified for the construction of DATC nomograms (DATCN) and DOC nomograms (DOCN), respectively. In both the training and validation cohorts, the calibration curves indicated good agreement between the nomogram-based predictions and the actual observations in the two nomograms, respectively. The C-index of the DATCN was higher than 80% (80.3-83.3%) at 1, 3 and 5 years in both the training and validation cohorts, significantly outperforming the AJCC (76.7-78%) and Cox (75.4-79.5%) model. The C-index of the DOCN was also higher than 69% (69.0-73.6%). In terms of ROC curves at each time point, those of the DATCN were very close to the upper-left corner of the coordinate axis in both the training and validation cohorts, and their AUCs were larger than 84% (84.2-85.4%).The AUCs of the AJCC (78.4-81.1%) and Cox (79.4-81.5%) models were significantly lower (p < 0.05), and the curves were closer to the diagonal. The ROC curves of the DOCN was similar to those of the DATCN, and the AUCs were 68.5-74%. The DATCN and DOCN therefore had good consistency, accuracy, and stability, respectively.

CONCLUSION

This study was the first to construct competing-risk nomograms for ATC. These nomograms have proved useful for accurately assessing patient prognoses and allowing more-individualized follow-up strategies, thereby reducing the mortality.

Establishment of a nomogram model for prediction of postoperative heterochronous liver metastasis in young and middle-aged patients with rectal cancer

BACKGROUND

The incidence of rectal cancer is increasing year by year. Radical surgery is often used for the treatment of rectal cancer in clinical practice, but postoperative liver metastasis has become an important reason for the increase in mortality. Therefore, establishing a model to predict the trend of metachronous liver metastasis has become a research focus. Nomogram model has been widely used in the medical field, but there has been no widely accepted nomogram model available for prediction of metachronous liver metastasis after rectal cancer surgery.

AIM

To constuct a nomogram model based on the risk factors for postoperative metachronous liver metastasis in young and middle-aged patients with rectal cancer, and to evaluate the performance of the model for predicting the risk of postoperative metachronous liver metastasis, so as to provide some guidance for clinical prevention and treatment.

METHODS

A total of 120 young and middle-aged patients with rectal cancer admitted to our hospital from March 2019 to February 2022 were selected as research subjects to observe the incidence of postoperative heterochronous liver metastasis. Univariate and multivariate Logistic regression analyses were performed to identify the risk factors for postoperative heterochronous liver metastasis and to construct a nomogram model. ROC curve, decision curve, and correction curve analyses were used to verify the value of nomogram model for the prediction of postoperative heterochronous liver metastasis.

RESULTS

The incidence of anomalous liver metastasis 1 year after surgery was 23.33% in 120 young and middle-aged patients with rectal cancer. Low differentiation, lymph node metastasis, depth of invasion (T3/T4), margin width of primary cancer < 2 cm, high expression of peripheral blood telomerase reverse transcriptase (hTERT), and elevated serum levels of carcinoembryonic antigen (CEA), vascular endothelial growth factor (VEGF), lemur tyrosine kinase-3 (LMTK3), squamous cell carcinoma-associated antigen (SCC-Ag), and axon-guided factor-1 (Netrin-1) were identified to be risk factor for postoperative hetero-chronic liver metastasis (P < 0.05). The C-index and area under the curve of the nomogram model were 0.860 and 0.957, respectively, and the net benefit value was high (P < 0.05).

CONCLUSION

Low differentiation, lymph node metastasis, depth of invasion (T3/T4), margin width of primary cancer < 2 cm, high expression of hTERT in peripheral blood, and elevated levels of serum CEA, VEGF, LMTK3, SC-AG and Netrin-1 are risk factors for postoperative xenotemporal liver metastasis in young and middle-aged patients with rectal cancer. Based on the above risk factors, a nomogram model has been established to predict postoperative heterochronous liver metastasis in such patients.

Prediction models for overall and cancer-specific survival in patients with metastatic early-onset colorectal cancer: a population-based study

PURPOSE

Metastatic early-onset colorectal cancer (EO-CRC) is on the rise, yet there is a dearth of predictive models for this disease. Therefore, it is crucial to develop a nomogram to aid in the early detection and management of metastatic colorectal cancer in young patients.

METHODS

We retrieved data from the SEER database on patients with metastatic colorectal cancer aged 50 or younger between 2010 and 2017. The data were randomly allocated in a 7:3 ratio to training and validation cohorts, and univariate and multivariate Cox regression analyses were used to identify independent prognostic factors for overall survival (OS) and cancer-specific survival (CSS) at 1, 3, and 5 years. The nomograms were developed based on these factors, and their discriminatory and calibration capabilities were validated. Using the nomogram risk scores, patients were stratified into low-risk and high-risk groups.

RESULTS

The study included 2470 patients with metastatic EO-CRC. Univariate and multivariate Cox regression analysis identified 12 independent risk factors that were included in the nomogram. The training cohort had a consistency index (C-index) of 0.71, while the validation cohort had a C-index of 0.70, demonstrating good predictive accuracy. Calibration plots showed a high level of consistency between the observed and predicted values, with overlapping plots along the diagonal. The decision curve analysis (DCA) revealed that the nomogram had a high clinical application value.

CONCLUSIONS

The novel nomograms were created to predict the prognosis of patients with metastatic EO-CRC, which can aid clinicians in developing more effective treatment strategies and contribute to more accurate prognostic assessments.

Individualized conditional survival nomograms for stage I-III early onset colorectal cancer patients

OBJECTIVE

Conditional survival accounts for the time already survived after surgery and provides additional survival information. The aim was to assess conditional survival in stages I-III early onset colorectal cancer patients and to create nomograms predicting the conditional overall survival and cancer-specific survival after surgery.

METHODS

A total of 7058 patients who underwent surgical resection of early onset colorectal cancer were identified from surveillance, epidemiology and end results database. The formula used for conditional survival calculation was conditional survival(x|y) = S(x + y)/S(x), where S(x) represents the survival at x years. Conditional survival nomograms were then developed to predict the 5-year conditional overall survival and cancer-specific survival.

RESULTS

The 5-year overall survival and cancer-specific survival after surgery increases gradually with additional survival time. Race, tumour site, grade, histology, T stage, N stage, lymph node ratio, preoperative carcinoma embryonic antigen level and perineural invasion status were independent predictors of cancer-specific survival, while age and sex were another two independent risk factors for overall survival. The nomograms based on these factors were successfully developed to predict 5-year overall survival and cancer-specific survival given 1-4 years already survived.

CONCLUSION

The probability of achieving postoperative 5-year overall survival and cancer-specific survival for early onset colorectal cancer increases gradually with additional time survived. The developed nomograms are fairly valuable and informative in facilitating clinical treatment and follow-up schemes.

Nomogram predicting the cancer-specific survival of early-onset colorectal cancer patients with synchronous liver metastasis: a population-based study

PURPOSE

This research aimed to explore prognostic factors for early-onset colorectal cancer (EO-CRC) patients with liver metastasis (LM) and develop nomogram for predicting cancer-specific survival (CSS) probability quantitatively.

METHODS

Our study included 4368 EO-CRC patients with LM registered in the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2017. Potential prognostic factors for EO-CRC patients with LM were identified by multivariable Cox regression analysis. Prognostic nomogram was subsequently constructed based on these prognostic factors. The discriminative ability, calibration, and clinical usefulness of the nomogram were assessed by the area under the receiver operating characteristic (ROC) curves (AUC), calibration curves, and decision curve analysis (DCA).

RESULTS

In the training cohort, marital status, primary tumor location, histopathological grade, T stage, number of metastatic organs, carcinoembryonic antigen (CEA), perineural invasion (PI), surgery of primary site, chemotherapy, radiation therapy, and metastatic lymph nodes ratio (LNR) were prognostic factors for cancer-specific mortality of EO-CRC patients with LM. The 1-, 2-, and 3-year AUC values of the prognostic nomogram were 0.777, 0.781, and 0.788, respectively. Calibration curves indicated acceptable agreement between nomogram-predicted survival and actual observed survival at 1, 2, and 3 years. DCA curves exhibited good positive net benefits in the prognostic model in most threshold probabilities at different time points. All of these results were reproducible in the validation cohort.

CONCLUSIONS

This study identified prognostic factors for EO-CRC patients with LM and developed a prognostic nomogram with good performance and clinical usability, which may help clinicians make better treatment decisions.

Preoperative C-reactive protein to prealbumin ratio is independently associated with prognosis in patients with resectable colorectal cancer

BACKGROUND

Increasing attention has been drawn the prognostic value of inflammatory indices for colorectal cancer (CRC). However, the prognostic value of the preoperative C-reactive protein to prealbumin ratio (CPAR) in CRC remains unclear.

METHODS

A retrospective study was conducted with 794 patients who had CRC and underwent radical surgical resection. The predictive performance of the inflammatory indices was analyzed and compared using the area under the time-dependent receiver operating characteristic curve. A competing risk regression model and Cox proportional hazard model were used to analyze the effects of CPAR on disease-free survival (DFS) and overall survival (OS), respectively.

RESULTS

Patients with high CPAR (>7.25) had poor survival outcome. The CPAR had the best predictive performance among all inflammatory indices, and was significantly associated with several characteristics of tumor invasion, including histological grade, tumor stage, and tumor size. Multivariate analysis showed that high CPAR was independently associated with poor DFS (subdistribution hazard ratio = 2.28, 95% confidence interval [CI]: 1.74-2.82) and OS (hazard ratio = 1.78, 95% CI: 1.60-1.96).

CONCLUSION

Preoperative CPAR assessment could serve as an effective and reliable tool for prognostic prediction in patients with resectable CRC.

Development and validation of a nomogram to predict overall survival in young non-metastatic rectal cancer patients after curative resection: a population-based analysis

PURPOSE

This study aimed to establish and validate a nomogram for predicting overall survival (OS) in young non-metastatic rectal cancer (RC) patients after curative resection.

METHODS

Young RC patients (under 50 years of age) from 2010 to 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Those patients randomly assigned to a training cohort and a validation cohort at a ratio of 7:3. The independent prognostic factors for OS were identified by univariate and multivariate Cox regression analysis. A nomogram model was built based on the independent prognostic variables and was evaluated by concordance index (C-index), receiver operating characteristics (ROC) curves, calibration plot, and decision curve analysis (DCA).

RESULTS

A total number of 3026 young RC patients were extracted from SEER database. OS nomogram was constructed based on race, histological type, tumor grade, T stage, N stage, carcinoembryonic antigen (CEA) level, and number of lymph nodes (LN) examined. C-index, ROC curves, calibration plot, and DCA curves presented satisfactory performance of the above nomogram in predicting the prognosis of young non-metastatic RC patients after curative resection. The nomogram can identify three subgroups of patients at different risks, which showed different prognostic outcomes both in the training cohort and validation cohort.

CONCLUSION

We successfully established a reliable and insightful nomogram to predict OS for young non-metastatic RC patients after curative resection. The nomogram may provide accurate prognosis prediction to guide individualized follow-up and treatment plans.

Nomogram to predict contralateral breast cancer risk in breast cancer survivors: A SEER-based study

The main purpose of this study was to build a prediction model for patients with contralateral breast cancer (CBC) using competing risks methodology. The aim is to help clinicians predict the probability of CBC in breast cancer (BC) survivors.We reviewed data from the Surveillance, Epidemiology, and End Results database of 434,065 patients with BC. Eligible patients were used to quantify the association between the development of CBC and multiple characteristics of BC patients using competing risk models. A nomogram was also created to facilitate clinical visualization and analysis. Finally, the stability of the model was verified using concordance index and calibration plots, and decision curve analysis was used to evaluate the clinical utility of the model by calculating the net benefit.Four hundred thirty-four thousand sixty-five patients were identified, of whom 6944 (1.6%) developed CBC in the 10 years follow-up. The 10-year cumulative risk of developing CBC was 2.69%. According to a multivariate competing risk model, older patients with invasive lobular carcinoma who had undergone unilateral BC surgery, and whose tumor was better differentiated, of smaller size and ER-negative/PR-positive, had a higher risk of CBC. The calibration plots illustrated an acceptable correlation between the prediction by nomogram and actual observation, as the calibration curve was closed to the 45° diagonal line. The concordance index for the nomogram was 0.65, which indicated it was well calibrated for individual risk of CBC. Decision curve analysis produced a wide range of risk thresholds under which the model we built would yield a net benefit.BC survivors remain at high risk of developing CBC. Patients with CBC have a worse clinical prognosis compared to those with unilateral BC. We built a predictive model for the risk of developing CBC based on a large data cohort to help clinicians identify patients at high risk, which can then help them plan individualized surveillance and treatment.

A Competing Risk Nomogram for Predicting Cancer-Specific Death of Patients With Maxillary Sinus Carcinoma

Objectives

Herein, we purposed to establish and verify a competing risk nomogram for estimating the risk of cancer-specific death (CSD) in Maxillary Sinus Carcinoma (MSC) patients.

Methods

The data of individuals with MSC used in this study was abstracted from the (SEER) Surveillance, Epidemiology, and End Results data resource as well as from the First Affiliated Hospital of Nanchang University (China). The risk predictors linked to CSD were identified using the CIF (cumulative incidence function) along with the Fine-Gray proportional hazards model on the basis of univariate analysis coupled with multivariate analysis implemented in the R-software. After that, a nomogram was created and verified to estimate the three- and five-year CSD probability.

Results

Overall, 478 individuals with MSC were enrolled from the SEER data resource, with a 3- and 5-year cumulative incidence of CSD after diagnosis of 42.1% and 44.3%, respectively. The Fine-Gray analysis illustrated that age, histological type, N stage, grade, surgery, and T stage were independent predictors linked to CSD in the SEER-training data set (n = 343). These variables were incorporated in the prediction nomogram. The nomogram was well calibrated and it demonstrated a remarkable estimation accuracy in the internal validation data set (n = 135) abstracted from the SEER data resource and the external validation data set (n = 200). The nomograms were well-calibrated and had a good discriminative ability with concordance indexes (c-indexes) of 0.810, 0.761, and 0.755 for the 3- and 5-year prognosis prediction of MSC-specific mortality in the training cohort, internal validation, and external validation cohort, respectively.

Conclusions

The competing risk nomogram constructed herein proved to be an optimal assistant tool for estimating CSD in individuals with MSC.

A Diagnostic Nomogram for Predicting the Risk of Anastomotic Leakage in Elderly Patients With Rectal Cancer: A Single-center Retrospective Cohort Study

BACKGROUND

Laparoscopic resection for rectal cancer has been gaining popularity over the past 2 decades. Whether elderly patients had more benefits from laparoscopy-assisted anterior resection (LAR) need further investigation when comparing with open anterior resection (OAR).

OBJECTIVES

This study aimed to evaluate the clinical outcomes and prognosis of LAR in elderly patients (65 y and above) with rectal cancer and investigate the factors associated with the anastomotic leakage (AL). Besides, the study sought to create a nomogram for precise prediction of AL after anterior resection for rectal cancer.

MATERIALS AND METHODS

A total of 343 rectal cancer patients over 65 years old who underwent LAR or OAR at a single center between January 2013 to January 2021 were retrospectively reviewed. Univariate analysis was conducted to explore potential risk factors for AL, and a nomogram for AL was created based on the multivariate logistic regression model.

RESULTS

A total of 343 patients were included in this study, 271 patients in LAR group and 72 patients in OAR group. Most of the variables were comparable between the 2 groups. The mean operative time was longer in the LAR group than that in the OAR group (191.66±58.33 vs. 156.85±53.88 min, P<0.0001). The LAR group exhibited a significantly lower intraoperative blood loss than the OAR group (85.17±50.03 vs. 131.67±79.10 mL; P<0.0001). Moreover, laparoscopic surgery resulted in shorter postoperative hospital stay, lower rates of diverting stoma and receiving sphincter sparing surgery in comparison with open surgery. The overall rates of complications were 25.1% and 40.3% in the LAR and OAR groups (P=0.011), respectively. And the reoperation rates in the OAR group (0%) was lower than in the LAR group (1.5%), but the difference did not reach statistical significance (P=0.300). Sex, location of tumor, diverting stoma and combined organ resection were identified as independent risk factors for AL based on multivariate analysis. Such factors were selected to develop a nomogram. After a median follow-up of 37.0 months, our study showed no significant difference in overall survival or disease free survival between the 2 groups for treatment of rectal cancer.

CONCLUSIONS

This study suggests that LAR is an alternative minimally invasive surgical procedure in patients above 65 years with better short-term outcomes and acceptable long-term outcomes compared with OAR. In addition, our nomogram has satisfactory accuracy and clinical utility may benefit for clinical decision-making.

Nomograms for Differentiated Thyroid Carcinoma Patients Based on the Eighth AJCC Staging and Competing Risks Model

Background

Differentiated thyroid carcinoma (DTC) patients have a long survival period and good prognosis, so they are easily affected by competing risk events. The purpose of this study was to use the competing risks model to identify prognostic factors for cause-specific death (CSD) and death due to other causes (DOC) in patients with DTC.

Methods

Our screening process identified 34 585 DTC patients in the Surveillance, Epidemiology, and End Results database and randomly divided them into a training cohort and a validation cohort. We used the Fine and Gray subdistribution hazards model to establish the CSD and DOC nomograms. The distinguishing ability and consistency of the nomograms were evaluated using the consistency indexes and calibration plots.

Results

Our analysis of a competing risks model revealed that pathological grade, tumor size, histological type, American Joint Committee on Cancer (AJCC)-8 stage, surgery status, adjuvant radiotherapy status, adjuvant chemotherapy status, and log odds of positive lymph nodes are prognostic factors for CSD, and age at diagnosis, year of diagnosis, sex, pathological grade, tumor size, AJCC-8 stage, surgery status, adjuvant radiotherapy status, and lymph node ratio are prognostic factors for DOC. The 1-year, 3-year, and 5-year concordance indexes in the validation cohorts were 0.942, 0.931, and 0.913 for the CSD nomogram and 0.813, 0.746, and 0.776 for the DOC nomogram. The calibration plots showed good consistency in both nomograms.

Conclusions

Our nomograms can be used as a tool to help clinicians individually predict the probability of CSD and DOC in DTC patients at 1 year, 3 years, and 5 years, which has certain guiding value in clinical applications.

Association of chemotherapy with survival in stage II colon cancer patients who received radical surgery: a retrospective cohort study

BACKGROUND

It remains controversial whether patients with Stage II colon cancer would benefit from chemotherapy after radical surgery. This study aims to assess the real effectiveness of chemotherapy in patients with stage II colon cancer undergoing radical surgery and to construct survival prediction models to predict the survival benefits of chemotherapy.

METHODS

Data for stage II colon cancer patients with radical surgery were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Propensity score matching (1:1) was performed according to receive or not receive chemotherapy. Competitive risk regression models were used to assess colon cancer cause-specific death (CSD) and non-colon cancer cause-specific death (NCSD). Survival prediction nomograms were constructed to predict overall survival (OS) and colon cancer cause-specific survival (CSS). The predictive abilities of the constructed models were evaluated by the concordance indexes (C-indexes) and calibration curves.

RESULTS

A total of 25,110 patients were identified, 21.7% received chemotherapy, and 78.3% were without chemotherapy. A total of 10,916 patients were extracted after propensity score matching. The estimated 3-year overall survival rates of chemotherapy were 0.7% higher than non- chemotherapy. The estimated 5-year and 10-year overall survival rates of non-chemotherapy were 1.3 and 2.1% higher than chemotherapy, respectively. Survival prediction models showed good discrimination (the C-indexes between 0.582 and 0.757) and excellent calibration.

CONCLUSIONS

Chemotherapy improves the short-term (43 months) survival benefit of stage II colon cancer patients who received radical surgery. Survival prediction models can be used to predict OS and CSS of patients receiving chemotherapy as well as OS and CSS of patients not receiving chemotherapy and to make individualized treatment recommendations for stage II colon cancer patients who received radical surgery.

Prognostic Significance of Preoperative Lymphocyte-to-C-Reactive Protein Ratio in Patients with Non-Metastatic Colorectal Cancer

Background

The inflammatory indexes are attracting increasing attention as a prognostic predictor for colorectal cancer (CRC). However, the prognostic value of the preoperative lymphocyte-to-C-reactive protein ratio (LCR) in patients with non-metastatic CRC remains to be established.

Methods

A total of 955 patients from 2010 to 2014 at a single center were included. Receiver operating characteristic curves (ROC) were generated to define the optimal cutoff value of the inflammatory indexes, and the areas under the curve (AUC) were calculated to compare the predictive value among the inflammatory indexes. The Fine and Gray competing risk regression model and Cox proportional hazard model were used to determine the prognostic factors for cancer-specific survival (CSS) and overall survival (OS) by using sub-distribution hazard ratio (SHR) and hazard ratio (HR) as size effects, respectively.

Results

A ratio of 6500 was defined as the optimal cutoff value for LCR for dividing CRC patients into the high (> 6500, n = 528) and low (≤ 6500, n = 427) LCR groups. The LCR had the highest value of prognostic prediction among all inflammation-based scores. Low LCR was significant correlated with several clinicopathological features of tumor invasion and development. The patients with low LCR had poorer CSS and OS as compared to those with high LCR. Multivariate analyses showed that low LCR was independently associated with worse OS (HR = 0.61, 95% CI: 0.53-0.70) and CSS (SHR = 0.55, 95% CI: 0.43-0.71).

Conclusion

Preoperative LCR can be a useful biomarker for prognostic prediction in non-metastatic CRC patients with a better predictive value than other inflammatory indexes.