A genomic signature for accurate classification and prediction of clinical outcomes in cancer patients treated with immune checkpoint blockade immunotherapy.

Tumor mutational burden (TMB) is associated with clinical response to immunotherapy, but application has been limited to a subset of cancer patients. We hypothesized that advanced machine-learning and proper modeling could identify mutations that classify patients most likely to derive clinical benefits. Training data: Two sets of public whole-exome sequencing (WES) data for metastatic melanoma. Validation data: One set of public non-small cell lung cancer (NSCLC) data. Least Absolute Shrinkage and Selection Operator (LASSO) machine-learning and proper modeling were used to identify a set of mutations (biomarker) with maximum predictive accuracy (measured by AUROC). Kaplan-Meier and log-rank methods were used to test prediction of overall survival. The initial model considered 2139 mutations. After pruning, 161 mutations (11%) were retained. An optimal threshold of 0.41 divided patients into high-weight (HW) or low-weight (LW) TMB groups. Classification for HW-TMB was 100% (AUROC = 1.0) on melanoma learning/testing data; HW-TMB was a prognostic marker for longer overall survival. In validation data, HW-TMB was associated with survival (p = 0.0057) and predicted 6-month clinical benefit (AUROC = 0.83) in NSCLC. In conclusion, we developed and validated a 161-mutation genomic signature with "outstanding" 100% accuracy to classify melanoma patients by likelihood of response to immunotherapy. This biomarker can be adapted for clinical practice to improve cancer treatment and care.

Uterus at a price: Disability insurance and hysterectomy.

Taiwanese Labor, Government Employee, and Farmer Insurance programs provide 5 to 6 months of salary to enrollees who undergo hysterectomies or oophorectomies before their 45th birthday. These programs create incentives for more and earlier treatments, referred to as inducement and timing effects. Using National Health Insurance data between 1997 and 2011, we estimate these effects on surgery hazards by difference-in-difference and bunching-smoothing polynomial methods. For Government Employee and Labor Insurance, inducement is 11-12% of all hysterectomies, and timing 20% of inducement. For oophorectomies, both effects are insignificant. Enrollees' behaviors are consistent with rational choices. Each surgery qualifies an enrollee for the same benefit, but oophorectomy has more adverse health consequences than hysterectomy. Induced hysterectomies increase benefit payments and surgical costs, at about the cost of a mammogram and 5 pap smears per enrollee.

End-Of-Life Medical Spending In Last Twelve Months Of Life Is Lower Than Previously Reported.

Although end-of-life medical spending is often viewed as a major component of aggregate medical expenditure, accurate measures of this type of medical spending are scarce. We used detailed health care data for the period 2009-11 from Denmark, England, France, Germany, Japan, the Netherlands, Taiwan, the United States, and the Canadian province of Quebec to measure the composition and magnitude of medical spending in the three years before death. In all nine countries, medical spending at the end of life was high relative to spending at other ages. Spending during the last twelve months of life made up a modest share of aggregate spending, ranging from 8.5 percent in the United States to 11.2 percent in Taiwan, but spending in the last three calendar years of life reached 24.5 percent in Taiwan. This suggests that high aggregate medical spending is due not to last-ditch efforts to save lives but to spending on people with chronic conditions, which are associated with shorter life expectancies.