Multivariate Prognostic Models for Patients with Stages I and Ii Colon Carcinoma: a Strobe-Compliant Retrospective Cohort Study.

Background: Colorectal cancer is the most frequent gastrointestinal malignancy worldwide. The value of adjuvant treatment is controversial in Stages I and II. Objective: The aim of this study was to construct post-operative prognostic models applicable to patients with stages I-II colon carcinoma (CC). Methods: This is a retrospective cohort study of patients with Stage I-II CC treated over a 25-year period. Exposure was defined as clinical, histopathological, and immunohistochemical factors (including CDX2 and MUC2 expression). Patients were randomly allocated to either a "modeling set" or a "validation set". Factors associated with recurrence, disease-free survival (DFS), and overall survival (OS) were defined in the "modeling set". Their performances were tested in the "validation set". Results: From a total of 556 recruited patients, 339 (61%) were allocated to the "modeling set" and 217 (39%) to the "validation set". Three models explaining recurrence, DFS, and OS were described. Tumor location in the left colon (Hazards ratio [HR] = 1.57; 95% Confidence interval [CI] 0.99-2.48), lymphocyte (HR = 0.46; 96% CI 0.27-0.88) and monocyte (HR = 0.99; 95% CI 0.99-1) counts, neutrophil/platelet ratio (HR = 1.3; 95% CI 0.74-2.3, and HR = 2.3; 95% CI 1.3-4.1; for second and third category, respectively), albumin/monocyte ratio (HR = 0.43; 95% CI 0.21-0.87), and microscopic residual disease after surgery (HR = 8.7; 95% CI 3.1-24) were independently associated with OS. T classification and expression of CDX2 and/or MUC2 were not independently associated with recurrence or prognosis. Conclusion: These models are simple and readily available, and distinguish the risk and prognosis in patients with CC stages I and II; these models require cheaper processes than the use of more sophisticated molecular biology techniques. They may guide either the need for adjuvant therapy versus post-operative surveillance only, as well as aid in the design of clinical trials.

Long-term PM2.5 exposure before diagnosis is associated with worse outcome in breast cancer.

PURPOSE: Increasingly epidemiological evidence supports that environmental factors are associated with breast cancer (BC) outcomes after a BC diagnosis. Although evidence suggests that air pollution exposure is associated with higher mortality in women with BC, studies investigating potential mechanisms have been lacking. METHODS: We evaluated women with BC (N = 151) attended at the National Cancer Institute-Mexico from 2012 to 2015. We calculated 1-year average exposures to particulate matter < 2.5 µm (PM2.5) at home address before diagnosis. We used linear and logistic regression models to determine the associations between PM2.5 exposure and BC aggressiveness (tumor size, molecular phenotype). RESULTS: Average annual PM2.5 exposure of this population was 23.0 µg/m3 [standard deviation (SD)]: 1.90 µg/m3]. PM2.5 levels were positively correlated with tumor size at diagnosis (r = 0.22; p = 0.007). Multivariable linear models had a similar inference [risk ratio (RR): 1.32; 95% confidence interval (95% CI): 1.04, 1.674]. We did not observe differences in this association by age or menopause status. Further, women with triple-negative BC (TNBC) had significantly higher PM2.5 levels compared with other phenotypes (p = 0.015). Multivariable-adjusted logistic regression models assessing the association between PM2.5 and tumor size had a similar inference (RR 1.41; 95% CI 1.05, 1.89) overall for all ages and also for women who were ≤ 50 years old at diagnosis (RR 1.63; 95% CI 1.036, 2.57). CONCLUSIONS: Our findings suggest a significant association between long-term PM2.5 exposure and BC aggressiveness based on tumor size and phenotype, as well as a worse outcome.

Multivariate Prognostic Models for Patients with Stages I and Ii Colon Carcinoma: a Strobe-Compliant Retrospective Cohort Study

ABSTRACT Background: Colorectal cancer is the most frequent gastrointestinal malignancy worldwide. The value of adjuvant treatment is controversial in Stages I and II. Objective: The aim of this study was to construct post-operative prognostic models applicable to patients with stages I-II colon carcinoma (CC). Methods: This is a retrospective cohort study of patients with Stage I-II CC treated over a 25-year period. Exposure was defined as clinical, histopathological, and immunohistochemical factors (including CDX2 and MUC2 expression). Patients were randomly allocated to either a "modeling set" or a "validation set". Factors associated with recurrence, disease-free survival (DFS), and overall survival (OS) were defined in the "modeling set". Their performances were tested in the "validation set". Results: From a total of 556 recruited patients, 339 (61%) were allocated to the "modeling set" and 217 (39%) to the "validation set". Three models explaining recurrence, DFS, and OS were described. Tumor location in the left colon (Hazards ratio [HR] = 1.57; 95% Confidence interval [CI] 0.99-2.48), lymphocyte (HR = 0.46; 96% CI 0.27-0.88) and monocyte (HR = 0.99; 95% CI 0.99-1) counts, neutrophil/platelet ratio (HR = 1.3; 95% CI 0.74-2.3, and HR = 2.3; 95% CI 1.3-4.1; for second and third category, respectively), albumin/monocyte ratio (HR = 0.43; 95% CI 0.21-0.87), and microscopic residual disease after surgery (HR = 8.7; 95% CI 3.1-24) were independently associated with OS. T classification and expression of CDX2 and/or MUC2 were not independently associated with recurrence or prognosis. Conclusion: These models are simple and readily available, and distinguish the risk and prognosis in patients with CC stages I and II; these models require cheaper processes than the use of more sophisticated molecular biology techniques. They may guide either the need for adjuvant therapy versus post-operative surveillance only, as well as aid in the design of clinical trials.