Risk stratification in gastric cancer lung metastasis: Utilizing an overall survival nomogram and comparing it with previous staging

BACKGROUND Gastric cancer(GC)is prevalent and aggressive,especially when patients have distant lung metastases,which often places patients into advanced stages.By identifying prognostic variables for lung metastasis in GC patients,it may be po-ssible to construct a good prediction model for both overall survival(OS)and the cumulative incidence prediction(CIP)plot of the tumour.AIM To investigate the predictors of GC with lung metastasis(GCLM)to produce nomograms for OS and generate CIP by using cancer-specific survival(CSS)data.METHODS Data from January 2000 to December 2020 involving 1652 patients with GCLM were obtained from the Surveillance,epidemiology,and end results program database.The major observational endpoint was OS;hence,patients were se-parated into training and validation groups.Correlation analysis determined va-rious connections.Univariate and multivariate Cox analyses validated the independent predictive factors.Nomogram distinction and calibration were performed with the time-dependent area under the curve(AUC)and calibration curves.To evaluate the accuracy and clinical usefulness of the nomograms,decision curve analysis(DCA)was performed.The clinical utility of the novel prognostic model was compared to that of the 7th edition of the American Joint Committee on Cancer(AJCC)staging system by utilizing Net Reclassification Improvement(NRI)and Integrated Discrimination Improvement(IDI).Finally,the OS prognostic model and Cox-AJCC risk stratification model modified for the AJCC system were compared.RESULTS For the purpose of creating the OS nomogram,a CIP plot based on CSS was generated.Cox multivariate regression analysis identified eleven significant prognostic factors(P<0.05)related to liver metastasis,bone metastasis,primary site,surgery,regional surgery,treatment sequence,chemotherapy,radiotherapy,positive lymph node count,N staging,and time from diagnosis to treatment.It was clear from the DCA(net benefit>0),time-de-pendent ROC curve(training/validation set AUC>0.7),and calibration curve(reliability slope closer to 45 degrees)results that the OS nomogram demonstrated a high level of predictive efficiency.The OS prediction model(New Model AUC=0.83)also performed much better than the old Cox-AJCC model(AUC difference between the new model and the old model greater than 0)in terms of risk stratification(P<0.0001)and verification using the IDI and NRI.CONCLUSION The OS nomogram for GCLM successfully predicts 1-and 3-year OS.Moreover,this approach can help to ap-propriately classify patients into high-risk and low-risk groups,thereby guiding treatment.

Risk factors,prognostic predictors,and nomograms for pancreatic cancer patients with initially diagnosed synchronous liver metastasis

BACKGROUND Liver metastasis(LM)remains a major cause of cancer-related death in patients with pancreatic cancer(PC)and is associated with a poor prognosis.Therefore,identifying the risk and prognostic factors in PC patients with LM(PCLM)is essential as it may aid in providing timely medical interventions to improve the prognosis of these patients.However,there are limited data on risk and prognostic factors in PCLM patients.AIM To investigate the risk and prognostic factors of PCLM and develop corresponding diagnostic and prognostic nomograms.METHODS Patients with primary PC diagnosed between 2010 and 2015 were reviewed from the Surveillance,Epidemiology,and Results Database.Risk factors were identified using multivariate logistic regression analysis to develop the diagnostic mode.The least absolute shrinkage and selection operator Cox regression model was used to determine the prognostic factors needed to develop the prognostic model.The performance of the two nomogram models was evaluated using receiver operating characteristic(ROC)curves,calibration plots,decision curve analysis(DCA),and risk subgroup classification.The Kaplan-Meier method with a logrank test was used for survival analysis.RESULTS We enrolled 33459 patients with PC in this study.Of them,11458(34.2%)patients had LM at initial diagnosis.Age at diagnosis,primary site,lymph node metastasis,pathological type,tumor size,and pathological grade were identified as independent risk factors for LM in patients with PC.Age>70 years,adenocarcinoma,poor or anaplastic differentiation,lung metastases,no surgery,and no chemotherapy were the independently associated risk factors for poor prognosis in patients with PCLM.The C-index of diagnostic and prognostic nomograms were 0.731 and 0.753,respectively.The two nomograms could accurately predict the occurrence and prognosis of patients with PCLM based on the observed analysis results of ROC curves,calibration plots,and DCA curves.The prognostic nomogram could stratify patients into prognostic groups and perform well in internal validation.CONCLUSION Our study identified the risk and prognostic factors in patients with PCLM and developed corresponding diagnostic and prognostic nomograms to help clinicians in subsequent clinical evaluation and intervention.External validation is required to confirm these results.

Development and validation of a prognostic nomogram for colorectal cancer after surgery

BACKGROUND A nomogram is a diagram that aggregates various predictive factors through multivariate regression analysis,which can be used to predict patient outcomes intuitively.Lymph node(LN)metastasis and tumor deposit(TD)conditions are two critical factors that affect the prognosis of patients with colorectal cancer(CRC)after surgery.At present,few effective tools have been established to predict the overall survival(OS)of CRC patients after surgery.AIM To screen out suitable risk factors and to develop a nomogram that predicts the postoperative OS of CRC patients.METHODS Data from a total of 3139 patients diagnosed with CRC who underwent surgical removal of tumors and LN resection from 2010 to 2015 were collected from the Surveillance,Epidemiology,and End Results program.The data were divided into a training set(n=2092)and a validation set(n=1047)at random.The Harrell concordance index(C-index),Akaike information criterion(AIC),and area under the curve(AUC)were used to assess the predictive performance of the N stage from the American Joint Committee Cancer tumor-node-metastasis classification,LN ratio(LNR),and log odds of positive lymph nodes(LODDS).Univariate and multivariate analyses were utilized to screen out the risk factors significantly correlating with OS.The construction of the nomogram was based on Cox regression analysis.The C-index,receiver operating characteristic(ROC)curve,and calibration curve were employed to evaluate the discrimination and prediction abilities of the model.The likelihood ratio test was used to compare the sensitivity and specificity of the final model to the model with the N stage alone to evaluate LN metastasis.RESULTS The predictive efficacy of the LODDS was better than that of the LNR based on the C-index,AIC values,and AUC values of the ROC curve.Seven independent predictive factors,namely,race,age at diagnosis,T stage,M stage,LODDS,TD condition,and serum carcinoembryonic antigen level,were included in the nomogram.The C-index of the nomogram for OS prediction was 0.8002(95%CI:0.7839-0.8165)in the training set and 0.7864(95%CI:0.7604-0.8124)in the validation set.The AUC values of the ROC curve predicting the 1-,3-,and 5-year OS were 0.846,0.841,and 0.825,respectively,in the training set and 0.823,0.817,and 0.835,respectively,in the validation test.Great consistency between the predicted and actual observed OS for the 1-,3-,and 5-year OS in the training set and validation set was shown in the calibration curves.The final nomogram showed a better sensitivity and specificity than the nomogram with N stage alone for evaluating LN metastasis in both the training set(-4668.0 vs-4688.3,P<0.001)and the validation set(-1919.5 vs-1919.8,P<0.001)through the likelihood ratio test.CONCLUSION The nomogram incorporating LODDS,TD,and other risk factors showed great predictive accuracy and better sensitivity and specificity and represents a potential tool for therapeutic decision-making.

Critical prognostic value of the log odds of negative lymph nodes/tumor size in rectal cancer patients

BACKGROUND The number of negative lymph nodes(NLNs)and tumor size are associated with prognosis in rectal cancer patients undergoing surgical resection.However,little is known about the prognostic significance of the NLN count after adjusting for tumor size.AIM To assess the prognostic impact of the log odds of NLN/tumor size(LONS)in rectal cancer patients.METHODS Data of patients with stage I–III rectal cancer were extracted from the Surveillance,Epidemiology,and End Results Program database.These patients were randomly divided into a training cohort and a validation cohort.Univariate and multivariate Cox regression analyses were used to determine the prognostic value of the LONS.The optimal cutoff values of LONS were calculated using the"X-tile"program.Stratified analysis of the effect of LONS on cancer-specific survival(CSS)and overall survival(OS)were performed.The Kaplan-Meier method with the log-rank test was used to plot the survival curve and compare the survival data among the different groups.RESULTS In all,41080 patients who met the inclusion criteria were randomly divided into a training cohort(n=28775,70%)and a validation cohort(n=12325,30%).Univariate and multivariate analyses identified the continuous variable LONS as an independent prognostic factor for CSS[training cohort:Hazard ratio(HR)=0.47,95%confidence interval(CI):0.44–0.51,P<0.001;validation cohort:HR=0.46,95%CI:0.41-0.52,P<0.001]and OS(training cohort:HR=0.53,95%CI:0.49-0.56,P<0.001;validation cohort:HR=0.52,95%CI:0.42-0.52,P<0.001).The Xtile program indicated that the difference in CSS was the most significant for LONS of-0.8,and the cutoff value of-0.4 can further distinguish patients with a better prognosis in the high LONS group.Stratified analysis of the effect of the categorical variable LONS on CSS and OS revealed that LONS was also an independent predictor,independent of pN stage,pT stage,tumor-node-metastasis stage,site,age,sex,the number of examined lymph nodes,race,preoperative radiotherapy and carcinoembryonic antigen level.CONCLUSION LONS is associated with improved survival of rectal cancer patients independent of other clinicopathological factors.

Prognostic impact of tumor deposits on overall survival in colorectal cancer:Based on Surveillance, Epidemiology, and End Results database

BACKGROUND In colorectal cancer, tumor deposits(TDs) are considered to be a prognostic factor in the current staging system, and are only considered in the absence of lymph node metastases(LNMs). However, this definition and the subsequent prognostic value based on it is controversial, with various hypotheses. TDs may play an independent role when it comes to survival and addition of TDs to LNM count may predict the prognosis of patients more accurately.AIM To assess the prognostic impact of TDs and evaluate the effect of their addition to the LNM count.METHODS The patients are derived from the Surveillance, Epidemiology, and End Results database. A prognostic analysis regarding impact of TDs on overall survival(OS) was performed using Cox regression model, and other covariates associating with OS were adjusted. The effect of addition of TDs to LNM count on N restaging was also evaluated. The subgroup analysis was performed to explore the different profile of risk factors between patients with and without TDs.RESULTS Overall, 103755 patients were enrolled with 14131(13.6%) TD-positive and 89624(86.4%) TD-negative tumors. TD-positive patients had worse prognosis compared with TD-negative patients, with 3-year OS rates of 47.3%(95%CI, 46.5%-48.1%) and 77.5%(95%CI, 77.2%-77.8%, P < 0.0001), respectively. On multivariable analysis, TDs were associated poorer OS(hazard ratio, 1.35;95%CI, 1.31-1.38;P < 0.0001). Among TD-positive patients, the number of TDs had a linear negative effect on disease-free survival and OS. After reclassifying patients by adding TDs to the LNM count, 885 of 19 965(4.4%) N1 patients were restaged as p N2, with worse outcomes than patients restaged as p N1(3-year OS rate: 78.5%, 95%CI, 77.9%-79.1% vs 63.2%, 95%CI, 60.1%-66.5%, respectively;P < 0.0001).CONCLUSION TDs are an independent prognostic factor for OS in colorectal cancer. The addition of TDs to LNM count improved the prognostic accuracy of tumor, node and metastasis staging.