Post-diagnosis adiposity and colorectal cancer prognosis: A Global Cancer Update Programme (CUP Global) systematic literature review and meta-analysis

The adiposity influence on colorectal cancer prognosis remains poorly characterised. We performed a systematic review and meta-analysis on post-diagnosis adiposity measures (body mass index [BMI], waist circumference, waist-to-hip ratio, weight) or their changes and colorectal cancer outcomes. PubMed and Embase were searched through 28 February 2022. Random-effects meta-analyses were conducted when at least three studies had sufficient information. The quality of evidence was interpreted and graded by the Global Cancer Update Programme (CUP Global) independent Expert Committee on Cancer Survivorship and Expert Panel. We reviewed 124 observational studies (85 publications). Meta-analyses were possible for BMI and all-cause mortality, colorectal cancer-specific mortality, and cancer recurrence/disease-free survival. Non-linear meta-analysis indicated a reverse J-shaped association between BMI and colorectal cancer outcomes (nadir at BMI 28 kg/m2). The highest risk, relative to the nadir, was observed at both ends of the BMI distribution (18 and 38 kg/m2), namely 60% and 23% higher risk for all-cause mortality; 95% and 26% for colorectal cancer-specific mortality; and 37% and 24% for cancer recurrence/disease-free survival, respectively. The higher risk with low BMI was attenuated in secondary analyses of RCTs (compared to cohort studies), among studies with longer follow-up, and in women suggesting potential methodological limitations and/or altered physiological state. Descriptively synthesised studies on other adiposity-outcome associations of interest were limited in number and methodological quality. All the associations were graded as limited (likelihood of causality: no conclusion) due to potential methodological limitations (reverse causation, confounding, selection bias). Additional well-designed observational studies and interventional trials are needed to provide further clarification.

The mortality risk in patients with early onset colorectal cancer: the role of comorbidities

The global incidence of early-onset colorectal cancer (EO-CRC) is increasing. Although the mortality rate is relatively stable, some comorbidities have been associated with a higher mortality rate. This study estimated the mortality risk in patients with EO-CRC with various comorbidities using real-world data to identify the high-risk group using Cox proportional regression for overall and cancer-specific mortality. The incidence rate of EO-CRC significantly increased from 6.04 per 100,000 population in 2007 to 12.97 per 100,000 population in 2017. The five-year overall mortality rate was 101.50 per 1000 person year and the cancer-specific mortality rate was 94.12 per 1000 person year. Patients with cerebrovascular disease (CVD) had a higher mortality risk (hazard ratio (HR): 1.68; 95% confidence interval (CI): 1.25-2.28; p=0.0007). After subgroup analyses based on age, sex, clinical stage, and treatment type, patients with CVD had a higher overall mortality risk compared to non-CVD patients, except for patients undergoing surgery and chemotherapy. Patients with chronic kidney disease had a higher mortality risk in the early clinical stages (HR: 2.31; 95% CI: 1.08-4.96; p=0.0138). Patients who underwent radiotherapy had a higher overall mortality risk (HR: 1.38; 95% CI: 1.04-1.85; p=0.0285) than those without liver disease. Identifying specific comorbidity mortality risks in patients with EO-CRC allows for risk stratification when screening target groups and may lower disease mortality.

The prognostic impact of BMI on colorectal cancer is stratified by tumor location

Purpose

Recent studies have revealed the contrasting prognostic roles of body mass index (BMI) and tumor location in colorectal cancer (CRC). Given that right- and left-sided CRC may exhibit inverse effects on outcome and body weight, the present study aimed to examine whether the prognostic value of BMI and tumor location could be reciprocally stratified.

Methods

This prospective, observational study recruited 4,086 patients diagnosed with stage III CRC from five independent clinical centers in China. The association of patients’ outcomes with BMI and tumor location was evaluated hierarchically by Kaplan–Meier and Cox proportional-hazards models.

Results

Although BMI was not associated with overall outcome, the association was significantly modified by tumor location. Among left-sided tumors, obesity and overweight were significantly associated with adverse overall survival (OS) and disease-specific survival (DSS). In contrast, among right-sided tumors, overweight was significantly associated with more favorable OS and DSS compared with the normal-weight group. The association of survival with tumor location did not reach statistical significance. However, hierarchical analysis by BMI revealed that left-sided tumors were associated with more favorable outcomes in the normal-weight group, while there was no statistically significant difference in the overweight or obese group.

Conclusions

BMI and tumor location may have opposing effects on CRC prognosis, when stratified by each other, after adjusting for other known prognostic factors. These findings are the first to show the interactive prognostic impact of BMI and tumor location, which could be relevant to the stratification of patient management.

Pre-Treatment Computed Tomography Radiomics for Predicting the Response to Neoadjuvant Chemoradiation in Locally Advanced Rectal Cancer: A Retrospective Study

Background and Purpose

Computerized tomography (CT) scans are commonly performed to assist in diagnosis and treatment of locally advanced rectal cancer (LARC). This study assessed the usefulness of pretreatment CT-based radiomics for predicting pathological complete response (pCR) of LARC to neoadjuvant chemoradiotherapy (nCRT).

Materials and Methods

Patients with LARC who underwent nCRT followed by total mesorectal excision surgery from July 2010 to December 2018 were enrolled in this retrospective study. A total of 340 radiomic features were extracted from pretreatment contrast-enhanced CT images. The most relevant features to pCR were selected using the least absolute shrinkage and selection operator (LASSO) method and a radiomic signature was generated. Predictive models were built with radiomic features and clinico-pathological variables. Model performance was assessed with decision curve analysis and was validated in an independent cohort.

Results

The pCR was achieved in 44 of the 216 consecutive patients (20.4%) in this study. The model with the best performance used both radiomics and clinical variables including radiomic signatures, distance to anal verge, lymphocyte-to-monocyte ratio, and carcinoembryonic antigen. This combined model discriminated between patients with and without pCR with an area under the curve of 0.926 and 0.872 in the training and the validation cohorts, respectively. The combined model also showed better performance than models built with radiomic or clinical variables alone.

Conclusion

Our combined predictive model was robust in differentiating patients with and without response to nCRT.

Prediction of Survival Rate and Chemotherapy Effect by an Immune Score Model in Colorectal Cancer

Colorectal cancer is the third most common cancer and the second leading cause of cancer-related deaths. Immune cells in the tumor microenvironment play an important role in the development of tumors. In this study, CIBERSORT was used to estimate the subset of the immune cells using bulk gene expression data (i.e., TCGA, GEO, and cBioPortal databases). 1,087 samples were included in the analysis. The results revealed that among the 22 immune cell subsets that were evaluated, resting and activated NK cells, macrophage M1 and M2, and resting mast cells are associated with significant improvements in patient survival of colorectal cancer. The 15-year survival rates for the training cohort showed 49.1% and 32.5%, respectively, for the low- and high-risk groups. Likewise, the validation and entire cohorts showed 77.3% versus 47.2% and 65.3% versus 46.5%, respectively, for the low- and high-risk groups. Also, the prognostic immune score in predicting the chemotherapy effects showed that the low-risk group had a better survival superiority over the high-risk group, whether patients received chemotherapy or not. The gene set enrichment analysis showed that the low-risk group was highly enriched in pathways or processes related to immune response. The immune checkpoint assessment revealed significantly higher mRNA expressions of CTLA4 in the lower risk group than in the higher risk group. Altogether, this study offers information that could improve the prognosis of colorectal cancer.