Nomograms and risk score models for predicting survival in rectal cancer patients with neoadjuvant therapy

BACKGROUND Colorectal cancer is a common digestive cancer worldwide.As a comprehensive treatment for locally advanced rectal cancer(LARC),neoadjuvant therapy(NT)has been increasingly used as the standard treatment for clinical stage II/III rectal cancer.However,few patients achieve a complete pathological response,and most patients require surgical resection and adjuvant therapy.Therefore,identifying risk factors and developing accurate models to predict the prognosis of LARC patients are of great clinical significance.AIM To establish effective prognostic nomograms and risk score prediction models to predict overall survival(OS)and disease-free survival(DFS)for LARC treated with NT.METHODS Nomograms and risk factor score prediction models were based on patients who received NT at the Cancer Hospital from 2015 to 2017.The least absolute shrinkage and selection operator regression model were utilized to screen for prognostic risk factors,which were validated by the Cox regression method.Assessment of the performance of the two prediction models was conducted using receiver operating characteristic curves,and that of the two nomograms was conducted by calculating the concordance index(C-index)and calibration curves.The results were validated in a cohort of 65 patients from 2015 to 2017.RESULTS Seven features were significantly associated with OS and were included in the OS prediction nomogram and prediction model:Vascular_tumors_bolt,cancer nodules,yN,body mass index,matchmouth distance from the edge,nerve aggression and postoperative carcinoembryonic antigen.The nomogram showed good predictive value for OS,with a C-index of 0.91(95%CI:0.85,0.97)and good calibration.In the validation cohort,the C-index was 0.69(95%CI:0.53,0.84).The risk factor prediction model showed good predictive value.The areas under the curve for 3-and 5-year survival were 0.811 and 0.782.The nomogram for predicting DFS included ypTNM and nerve aggression and showed good calibration and a C-index of 0.77(95%CI:0.69,0.85).In the validation cohort,the C-index was 0.71(95%CI:0.61,0.81).The prediction model for DFS also had good predictive value,with an AUC for 3-year survival of 0.784 and an AUC for 5-year survival of 0.754.CONCLUSION We established accurate nomograms and prediction models for predicting OS and DFS in patients with LARC after undergoing NT.

A good prognostic predictor for liver transplantation recipients with benign end-stage liver cirrhosis

BACKGROUND： Post-transplant model for predicting mortality（PMPM, calculated as-5.359＋1.988×ln（serum creatinine [mg/d L]）＋1.089×ln（total bilirubin [mg/d L]）） score has been proved to be a simple and accurate model for predicting the prognosis after liver transplantation（LT） in a single center study. Here we aim to verify this model in a large cohort of patients.METHODS： A total of 2727 patients undergoing LT with endstage liver cirrhosis from January 2003 to December 2010 were included in this retrospective study. Data were collected from the China Liver Transplant Registry（CLTR）. PMPM score was calculated at 24-h and 7-d following LT. According to the PMPM score at 24-h, all patients were divided into the low-risk group（PMPM score ≤-1.4, n=2509） and the high-risk group（PMPM score 〉-1.4, n=218）. The area under receiver operator characteristic curve（AUROC） was calculated for evaluating the prognostic accuracy.RESULTS： The 1-, 3-, and 5-year patient survival rates in the low-risk group were significantly higher than those in the high-risk group（90.23%, 88.01%, and 86.03% vs 63.16%, 59.62%, and 56.43%, respectively, P〈0.001）. In the high-risk group, 131 patients had a decreased PMPM score（≤-1.4） at 7-d, and their cumulative survival rate was significantly higher than the other 87 patients with sustained high PMPM score（〉-1.4）（P〈0.001）. For predicting 3-month mortality, PMPM score showed a much higher AUROC than post-transplant MELD score（P〈0.05）.CONCLUSION： PMPM score is a simple and effective tool to predict short-term mortality after liver transplantation in patients with benign liver diseases, and an indicator for prompt salvaging treatment as well.

Predictive scores for mortality in full-term infants with necrotizing enterocolitis: experience of a tertiary hospital in Southwest China

Background: Although many risk factors for mortalityof necrotizing enterocolitis (NEC) were investigated,most of them were obtained from preterm infants, andfew works focused on the prognostic risk factors in fullterminfants. This study aimed to identify risk factors anddevelop a prediction score model for mortality in fulltermneonates with NEC.Methods: The risk factors were analyzed retrospectivelyby bivariate and multivariate logistic regression analysis in153 full-term neonates with NEC, who were hospitalizedin Children's Hospital of Chongqing Medical Universityfrom 2000 to 2013. A prediction score model was developedaccording to the regression coeffi cients of risk factors.Results: The mortality of the infants was 19.6%(30/153). The non-survivors had a younger age of diagnosisand advanced stage of NEC (P<0.05). They had a higherprevalence of respiratory failure, intestinal perforation,peritonitis and other complications, compared with thesurvivors (P<0.05). On the day of diagnosis, the nonsurvivorswere more likely to have abnormal laboratoryindicators than survivors (P<0.05). Age at diagnosis [oddsratio (OR)=0.91, 95% confidence interval (CI)=0.836-0.99], respiratory failure (OR=2.76, 95% CI=1.10-6.92),and peritonitis (OR=26.36, 95% CI=7.52-173.92) hadsignificant independent contributions to death. A scoremodel predicting death was developed, and the area underthe receiver operating characteristic curve was 0.869 (95%CI=0.803-0.935). All infants with scores ≥8 died.Conclusions: Younger age at diagnosis, peritonitis,and respiratory failure might be risk factors for themortality of full-term infants with NEC. Infants with apredictive score of 8 were at high risk for death.