Metabolic Syndrome, Gastric Cancer Mortality and Competing Risk Survival Analysis

Competing and Noncompeting Risk Models for Predicting Kidney Allograft Failure

Background

Prognostic models are becoming increasingly relevant in clinical trials as potential surrogate end points and for patient management as clinical decision support tools. However, the effect of competing risks on model performance remains poorly investigated. We aimed to carefully assess the performance of competing risk and noncompeting risk models in the context of kidney transplantation, where allograft failure and death with a functioning graft are two competing outcomes.

Methods

We included 11,046 kidney transplant recipients enrolled in ten countries. We developed prediction models for long-term kidney graft failure prediction, without accounting (i.e., censoring) and accounting for the competing risk of death with a functioning graft, using Cox, Fine–Gray, and cause-specific Cox regression models. To this aim, we followed a detailed and transparent analytical framework for competing and noncompeting risk modeling and carefully assessed the models' development, stability, discrimination, calibration, overall fit, clinical utility, and generalizability in external validation cohorts and subpopulations. More than 15 metrics were used to provide an exhaustive assessment of model performance.

Results

Among 11,046 recipients in the derivation and validation cohorts, 1497 (14%) lost their graft and 1003 (9%) died with a functioning graft after a median follow-up postrisk evaluation of 4.7 years (interquartile range, 2.7–7.0). The cumulative incidence of graft loss was similarly estimated by Kaplan–Meier and Aalen–Johansen methods (17% versus 16% in the derivation cohort). Cox and competing risk models showed similar and stable risk estimates for predicting long-term graft failure (average mean absolute prediction error of 0.0140, 0.0138, and 0.0135 for Cox, Fine–Gray, and cause-specific Cox models, respectively). Discrimination and overall fit were comparable in the validation cohorts, with concordance index ranging from 0.76 to 0.87. Across various subpopulations and clinical scenarios, the models performed well and similarly, although in some high-risk groups (such as donors older than 65 years), the findings suggest a trend toward moderately improved calibration when using a competing risk approach.

Conclusions

Competing and noncompeting risk models performed similarly in predicting long-term kidney graft failure.

Development and Validation of a Nomogram Based on Metabolic Risk Score for Assessing Lymphovascular Space Invasion in Patients with Endometrial Cancer

OBJECTIVE

This study assessed the predictive value of the metabolic risk score (MRS) for lymphovascular space invasion (LVSI) in endometrial cancer (EC) patients.

METHODS

We included 1076 patients who were diagnosed with EC between January 2006 and December 2020 in Peking University People's Hospital. All patients were randomly divided into the training and validation cohorts in a ratio of 2:1. Data on clinicopathological indicators were collected. Univariable and multivariable logistic regression analysis was used to define candidate factors for LVSI. A backward stepwise selection was then used to select variables for inclusion in a nomogram. The performance of the nomogram was evaluated by discrimination, calibration, and clinical usefulness.

RESULTS

Independent predictors of LVSI included differentiation grades (G2: OR = 1.800, 95% CI: 1.050-3.070, p = 0.032) (G3: OR = 3.49, 95% CI: 1.870-6.520, p < 0.001), histology (OR = 2.723, 95% CI: 1.370-5.415, p = 0.004), MI (OR = 4.286, 95% CI: 2.663-6.896, p < 0.001), and MRS (OR = 1.124, 95% CI: 1.067-1.185, p < 0.001) in the training cohort. A nomogram was established to predict a patient's probability of developing LVSI based on these factors. The ROC curve analysis showed that an MRS-based nomogram significantly improved the efficiency of diagnosing LVSI compared with the nomogram based on clinicopathological factors (p = 0.0376 and p = 0.0386 in the training and validation cohort, respectively). Subsequently, the calibration plot showed a favorable consistency in both groups. Moreover, we conducted a decision curve analysis, showing the great clinical benefit obtained from the application of our nomogram. However, our study faced several limitations. Further external validation and a larger sample size are needed in future studies.

CONCLUSION

MRS-based nomograms are useful for predicting LVSI in patients with EC and may facilitate better clinical decision-making.

Pancreatic cancer incidence and mortality trends: a population-based study

Objectives To analyze trends in pancreatic cancer incidence and mortality in Latin American countries. Methods An ecological study with incidence data from the International Agency for Research on Cancer and mortality data from the World Health Organization. The trend of incidence by Joinpoint regression, the variation of the annual average and the 95% confidence interval were analyzed. Results There were increasing trends in incidence in Brazil, in males, aged 40-59 years, and reduction in Costa Rica. In females, there was stability in all age groups. The mortality rates increased in the elderly in Brazil (AAPC: 1.09%; 95% CI: 0.76; 1.42), Peru (AAPC: 1.76%; 95% CI: 0.36; 3.17) and El Salvador (AAPC: 2.88%; 95% CI: 0.38; 5.43), while in Mexico, there was a reduction. In females, this rate increased in Brazil (AAPC: 1.38%; 95% CI: 1.07; 1.69), Peru (AAPC: 2.25%; 95% CI: 0.68; 3.85), Chile (AAPC: 3.62%; 95% CI:1.96; 5.31), Nicaragua (AAPC: 2.51%; 95% CI: 0.36; 4.71) and Paraguay (AAPC: 1.17%; 95% CI: 0.37; 1.98) and a downward trend was observed in Colombia and Ecuador. Conclusions Pancreatic cancer had a higher incidence in the elderly population of both sexes and an increase of the mortality trend in females was noted.

Potential impact of Helicobacter pylori-related metabolic syndrome on upper and lower gastrointestinal tract oncogenesis

Both Helicobacter pylori infection and metabolic syndrome present significant global public health burdens. Metabolic syndrome is closely related to insulin resistance, the major underlying mechanism responsible for metabolic abnormalities, and Helicobacter pylori infection has been proposed to be a contributing factor. There is growing evidence for a potential association between Helicobacter pylori infection and insulin resistance, metabolic syndrome and related morbidity, including abdominal obesity, type 2 diabetes mellitus, dyslipidemia, hypertension, all of which increase mortality related to cardio-cerebrovascular disease, neurodegenerative disorders, nonalcoholic fatty liver disease and malignancies. More specifically, insulin resistance, metabolic syndrome and hyperinsulinemia have been associated with upper and lower gastrointestinal tract oncogenesis. Apart from cardio-cerebrovascular, degenerative diseases and nonalcoholic fatty liver disease, a number of studies claim that Helicobacter pylori infection is implicated in metabolic syndrome-related Barrett's esophagus and esophageal adenocarcinoma development, gastric and duodenal ulcers and gastric oncogenesis as well as lower gastrointestinal tract oncogenesis. This review summarizes evidence on the potential impact of Helicobacter pylori-related metabolic syndrome on gastroesophageal reflux disease-Barrett's esophagus-esophageal adenocarcinoma, gastric atrophy-intestinal metaplasia-dysplasia-gastric cancer and colorectal adenoma-dysplasia-colorectal cancer sequences. Helicobacter pylori eradication might inhibit these oncogenic processes, and thus further studies are warranted.

Prediction of three lipid derivatives for postoperative gastric cancer mortality: the Fujian prospective investigation of cancer (FIESTA) study

BACKGROUND

As we previously reported, the presence of preoperative metabolic syndrome can predict the significant risk of gastric cancer mortality. As a further extension, we evaluated the prediction of three lipid derivatives generated from triglycerides (TG), total cholesterol (TC), high- and low-density lipoprotein cholesterol (HDLC and LDLC) at baseline for postoperative gastric cancer mortality by prospectively analysing 3012 patients. The three lipid derivatives included the ratio of TC minus HDLC to HDLC known as atherogenic index (AI), the ratio of TG to HDLC abbreviated as THR and the ratio of LDLC to HDLC abbreviated as LHR.

METHODS

Gastric cancer patients who received gastrectomy between January 2000 and December 2010 were consecutively recruited from Fujian Cancer Hospital. Follow-up assessment was implemented annually before December 2015.

RESULTS

Finally, there were 1331 deaths from gastric cancer and 1681 survivors, with a median follow-up time of 44.05 months. 3012 patients were evenly randomized into the derivation group and the validation group, and both groups were well balanced at baseline. Overall adjusted estimates in the derivation group were statistically significant for three lipid derivatives (hazard ratio [HR]: 1.20, 1.17 and 1.19 for AI, THR and LHR, respectively, all P < 0.001), and were reproducible in the validation group. The risk prediction of three lipid derivatives was more obvious in males than females, in patients with tumor-node-metastasis stage I-II than stage III-IV, in patients with intestinal-type than diffuse-type gastric cancer, in patients with normal weight than obesity, and in patients without hypertension than with hypertension, especially for AI and LHR, and all results were reproducible. Calibration and discrimination statistics showed good reclassification performance and predictive accuracy when separately adding three lipid derivatives to baseline risk model. A prognostic nomogram was accordingly built based on significant attributes to facilitate risk assessment, with a good prediction capability.

CONCLUSIONS

Our results indicate that preoperative lipid derivatives, especially AI and LHR, are powerful predictors of postoperative gastric cancer mortality, with more obvious prediction in patients of male gender or with tumor-node-metastasis stage I-II or intestinal-type gastric cancer, and in the absence of obesity or hypertension before gastrectomy.

Baseline Metabolic Risk Score and Postsurgical Esophageal Cancer-Specific Mortality: The Fujian Prospective Investigation of Cancer (FIESTA) Study

Backgrounds: Compelling evidence has emerged to support a close relationship between metabolic syndrome and esophageal cancer (EC). Aims: Using five baseline metabolism-related markers, we constructed a metabolic risk score (MRS), aiming to test whether MRS can improve the prediction of postsurgical EC-specific mortality over traditional demographic and clinicopathologic characteristics. Methods: Total 2535 EC patients who received three-field lymphadenectomy were enrolled from January 2000 to December 2010, and they were followed up until December 2015. Results: All EC patients were randomly split into derivation group (n=1512, 60%) and validation group (n=1014, 40%). MRS was generated in derivation group by adopting the Framingham 'points' system and shrinkage method, and it ranged from -9 to 17. EC-specific mortality risk increased with the increase of MRS, and adjusted estimates were more obvious in patients with upper tertile (MRS>6) than patients with lower MRS (≤2) in either derivation (hazard ratio [HR]=2.28, 95% confidence interval [CI]: 1.90-2.73, P<0.001) or validation group (HR=2.11, 95% CI: 1.66-2.67, P<0.001) or both groups (HR=2.37, 95% CI: 1.95-2.88, P<0.001). In Kaplan-Meier curve, cumulative survival rates differed significantly across tertiles of MRS. Further analysis indicated that MRS can improve classification accuracy and discriminatory ability over clinicopathologic parameters. Conclusions: Our findings supported the usefulness of baseline MRS in predicting the prognosis of postsurgical EC-specific mortality.

An in-depth prognostic analysis of baseline blood lipids in predicting postoperative colorectal cancer mortality: The FIESTA study

BACKGROUND

Dyslipidaemia is key to colorectal carcinogenesis, and the prediction of baseline triglycerides (TG), total cholesterol (TC), high- and low-density lipoprotein cholesterol (HDLC and LDLC) for postsurgical colorectal cancer mortality has not been researched.

OBJECTIVES

We attempted to re-analyse the FIESTA database to assess the prognostic value of three informative lipid derivatives - AI (atherogenic index: (TC - HDLC)/HDLC), THR (TG/HDLC) and LHR (LDLC/HDLC) in predicting colorectal cancer mortality.

METHODS

Based on the FIESTA database, 1318 patients received radical resection from 2000 to 2008, with the latest follow-up completed in December 2015. Median follow-up time was 58.6 months.

RESULTS

Total 1318 patients were randomly evenly divided into the derivation and validation groups. Overall, baseline AI and LHR were associated with the significantly increased risk of colorectal cancer mortality in both derivation (hazard ratio (HR): 1.41 and 1.35, respectively) and validation (HR: 1.37 and 1.32, respectively) groups (all P < 0.001). The predictive performance of AI and LHR was remarkably enhanced in patients with female gender, former/current smoking, colon cancer, early stage, positive vein tumor embolus, normal weight, preoperative hypertension or diabetes comorbidities. Calibration/discrimination analyses revealed that adding AI or LHR to the traditional model had a better fit in both groups. A prognostic nomogram was finally constructed with good predictive accuracy and discriminative capability (C-index = 0.814, P < 0.001).

CONCLUSION

We consolidated the prognostic superiority of AI and LHR in predicting colorectal cancer mortality over TNM stage.