Clinical Calculator Based on Molecular and Clinicopathologic Characteristics Predicts Recurrence Following Resection of Stage I-III Colon Cancer.

PURPOSE: Clinical calculators and nomograms have been endorsed by the American Joint Committee on Cancer (AJCC), as they provide the most individualized and accurate estimate of patient outcome. Using molecular and clinicopathologic variables, a third-generation clinical calculator was built to predict recurrence following resection of stage I-III colon cancer. METHODS: Prospectively collected data from 1,095 patients who underwent colectomy between 2007 and 2014 at Memorial Sloan Kettering Cancer Center were used to develop a clinical calculator. Discrimination was measured with concordance index, and variability in individual predictions was assessed with calibration curves. The clinical calculator was externally validated with a patient cohort from Washington University's Siteman Cancer Center in St Louis. RESULTS: The clinical calculator incorporated six variables: microsatellite genomic phenotype; AJCC T category; number of tumor-involved lymph nodes; presence of high-risk pathologic features such as venous, lymphatic, or perineural invasion; presence of tumor-infiltrating lymphocytes; and use of adjuvant chemotherapy. The concordance index was 0.792 (95% CI, 0.749 to 0.837) for the clinical calculator, compared with 0.708 (95% CI, 0.671 to 0.745) and 0.757 (0.715 to 0.799) for the staging schemes of the AJCC manual's 5th and 8th editions, respectively. External validation confirmed robust performance, with a concordance index of 0.738 (95% CI, 0.703 to 0.811) and calibration plots of predicted probability and observed events approaching a 45° diagonal. CONCLUSION: This third-generation clinical calculator for predicting cancer recurrence following curative colectomy successfully incorporates microsatellite genomic phenotype and the presence of tumor-infiltrating lymphocytes, resulting in improved discrimination and predictive accuracy. This exemplifies an evolution of a clinical calculator to maintain relevance by incorporating emerging variables as they become validated and accepted in the oncologic community.

Changes in alcohol and cigarette consumption in response to medical and recreational cannabis legalization: Evidence from U.S. state tax receipt data.

BACKGROUND: Whether medical or recreational cannabis legalization impacts alcohol or cigarette consumption is a key question as cannabis policy evolves, given the adverse health effects of these substances. Relatively little research has examined this question. The objective of this study was to examine whether medical or recreational cannabis legalization was associated with any change in state-level per capita alcohol or cigarette consumption. METHODS: Dependent variables included per capita consumption of alcohol and cigarettes from all 50 U.S. states, estimated from state tax receipts and maintained by the Centers for Disease Control and National Institute for Alcohol Abuse and Alcoholism, respectively. Independent variables included indicators for medical and recreational legalization policies. Three different types of indicators were separately used to model medical cannabis policies. Indicators for the primary model were based on the presence of active medical cannabis dispensaries. Secondary models used indicators based on either the presence of a more liberal medical cannabis policy ("non-medicalized") or the presence of any medical cannabis policy. Difference-in-difference regression models were applied to estimate associations for each type of policy. RESULTS: Primary models found no statistically significant associations between medical or recreational cannabis legalization policies and either alcohol or cigarette sales per capita. In a secondary model, both medical and recreational policies were associated with significantly decreased per capita cigarette sales compared to states with no medical cannabis policy. However, post hoc analyses demonstrated that these reductions were apparent at least two years prior to policy adoption, indicating that they likely result from other time-varying characteristics of legalization states, rather than cannabis policy. CONCLUSION: We found no evidence of a causal association between medical or recreational cannabis legalization and changes in either alcohol or cigarette sales per capita.