Chromosomal chaos and tumor immunity: Cancer immunotherapy produces durable clinical responses in only a subset of patients. Identification of tumor characteristics that correlate with responses could lead to predictive biomarkers and shed light on causal mechanisms. Davoli et al. found that human tumors with extensive aneuploidy—i.e., that display a highly abnormal number of chromosomes and chromosomal segments—express fewer markers of the immune cells responsible for tumor destruction. In a retrospective analysis of clinical trial data, they found that melanoma patients with highly aneuploid tumors were less likely to benefit from immune checkpoint blockade therapy than patients whose tumors had a more normal karyotype. Thus, aneuploidy appears to enhance the ability of tumors to evade the immune system. Science , this issue p. 10.1126/science.aaf8399

In a longitudinal clinical study to compare two groups, the primary end point is often the time to a specific event (eg, disease progression, death). The hazard ratio estimate is routinely used to empirically quantify the between-group difference under the assumption that the ratio of the two hazard functions is approximately constant over time. When this assumption is plausible, such a ratio estimate may capture the relative difference between two survival curves. However, the clinical meaning of such a ratio estimate is difficult, if not impossible, to interpret when the underlying proportional hazards assumption is violated (ie, the hazard ratio is not constant over time). Although this issue has been studied extensively and various alternatives to the hazard ratio estimator have been discussed in the statistical literature, such crucial information does not seem to have reached the broader community of health science researchers. In this article, we summarize several critical concerns regarding this conventional practice and discuss various well-known alternatives for quantifying the underlying differences between groups with respect to a time-to-event end point. The data from three recent cancer clinical trials, which reflect a variety of scenarios, are used throughout to illustrate our discussions. When there is not sufficient information about the profile of the between-group difference at the design stage of the study, we encourage practitioners to consider a prespecified, clinically meaningful, model-free measure for quantifying the difference and to use robust estimation procedures to draw primary inferences.

Purpose: Hereditary factors play an important role in colorectal cancer (CRC) risk, yet the prevalence of germline cancer susceptibility gene mutations in patients with CRC unselected for high-risk features (eg, early age at diagnosis, personal/family history of cancer or polyps, tumor microsatellite instability [MSI], mismatch repair [MMR] deficiency) is unknown. Patients and Methods: We recruited 1,058 participants who received CRC care in a clinic-based setting without preselection for age at diagnosis, personal/family history, or MSI/MMR results. All participants underwent germline testing for mutations in 25 genes associated with inherited cancer risk. Each gene was categorized as high penetrance or moderate penetrance on the basis of published estimates of the lifetime cancer risks conferred by pathogenic germline mutations in that gene. Results: One hundred five (9.9%; 95% CI, 8.2% to 11.9%) of 1,058 participants carried one or more pathogenic mutations, including 33 (3.1%) with Lynch syndrome (LS). Twenty-eight (96.6%) of 29 available LS CRCs demonstrated abnormal MSI/MMR results. Seventy-four (7.0%) of 1,058 participants carried non-LS gene mutations, including 23 (2.2%) with mutations in high-penetrance genes (five APC, three biallelic MUTYH, 11 BRCA1/2, two PALB2, one CDKN2A, and one TP53), 15 of whom lacked clinical histories suggestive of their underlying mutation. Thirty-eight (3.6%) participants had moderate-penetrance CRC risk gene mutations (19 monoallelic MUTYH, 17 APC*I1307K, two CHEK2). Neither proband age at CRC diagnosis, family history of CRC, nor personal history of other cancers significantly predicted the presence of pathogenic mutations in non-LS genes. Conclusion: Germline cancer susceptibility gene mutations are carried by 9.9% of patients with CRC. MSI/MMR testing reliably identifies LS probands, although 7.0% of patients with CRC carry non-LS mutations, including 1.0% with BRCA1/2 mutations.

Non–placebo-controlled trials of erythropoiesis-stimulating agents (ESAs) comparing lower and higher hemoglobin targets in patients with chronic kidney disease indicate that targeting of a lower hemoglobin range may avoid ESA-associated risks. However, target-based strategies are confounded by each patient's individual hematopoietic response. We assessed the relationship among the initial hemoglobin response to darbepoetin alfa after two weight-based doses, the hemoglobin level achieved after 4 weeks, the subsequent darbepoetin alfa dose, and outcomes in 1872 patients with chronic kidney disease and type 2 diabetes mellitus who were not receiving dialysis. We defined a poor initial response to darbepoetin alfa (which occurred in 471 patients) as the lowest quartile of percent change in hemoglobin level (<2%) after the first two standardized doses of the drug. Patients who had a poor initial response to darbepoetin alfa had a lower average hemoglobin level at 12 weeks and during follow-up than did patients with a better hemoglobin response (a change in hemoglobin level ranging from 2 to 15% or more) (P<0.001 for both comparisons), despite receiving higher doses of darbepoetin alfa (median dose, 232 μg vs. 167 μg; P<0.001). Patients with a poor response, as compared with those with a better response, had higher rates of the composite cardiovascular end point (adjusted hazard ratio, 1.31; 95% confidence interval [CI], 1.09 to 1.59) or death (adjusted hazard ratio, 1.41; 95% CI, 1.12 to 1.78). A poor initial hematopoietic response to darbepoetin alfa was associated with an increased subsequent risk of death or cardiovascular events as doses were escalated to meet target hemoglobin levels. Although the mechanism of this differential effect is not known, these findings raise concern about current target-based strategies for treating anemia in patients with chronic kidney disease. (Funded by Amgen; ClinicalTrials.gov number, NCT00093015.)

Suppose that we are interested in establishing simple but reliable rules for predicting future t-year survivors through censored regression models. In this article we present inference procedures f...