Purpose: While various studies have highlighted the prognostic significance of pathologic complete response (pCR) after neoadjuvant chemotherapy (NAT), the impact of additional adjuvant therapy after pCR is not known.Experimental Design: PubMed was searched for studies with NAT for breast cancer and individual patient-level data was extracted for analysis using plot digitizer software. HRs, with 95% probability intervals (PI), measuring the association between pCR and overall survival (OS) or event-free survival (EFS), were estimated using Bayesian piece-wise exponential proportional hazards hierarchical models including pCR as predictor.Results: Overall, 52 of 3,209 publications met inclusion criteria, totaling 27,895 patients. Patients with a pCR after NAT had significantly better EFS (HR = 0.31; 95% PI, 0.24–0.39), particularly for triple-negative (HR = 0.18; 95% PI, 0.10–0.31) and HER2+ (HR = 0.32; 95% PI, 0.21–0.47) disease. Similarly, pCR after NAT was also associated with improved survival (HR = 0.22; 95% PI, 0.15–0.30). The association of pCR with improved EFS was similar among patients who received subsequent adjuvant chemotherapy (HR = 0.36; 95% PI, 0.19–0.67) and those without adjuvant chemotherapy (HR = 0.36; 95% PI, 0.27–0.54), with no significant difference between the two groups (P = 0.60).Conclusions: Achieving pCR following NAT is associated with significantly better EFS and OS, particularly for triple-negative and HER2+ breast cancer. The similar outcomes with or without adjuvant chemotherapy in patients who attain pCR likely reflects tumor biology and systemic clearance of micrometastatic disease, highlighting the potential of escalation/deescalation strategies in the adjuvant setting based on neoadjuvant response.See related commentary by Esserman, p. 2771

Purpose: Deviations from proportional hazards (DPHs), which may be more prevalent in the era of precision medicine and immunotherapy, can lead to underpowered trials or misleading conclusions. We used a meta-analytic approach to estimate DPHs across cancer trials, investigate associated factors, and evaluate data-analysis approaches for future trials. Experimental Design: We searched PubMed for phase III trials in breast, lung, prostate, and colorectal cancer published in a preselected list of journals between 2014 and 2016 and extracted individual patient-level data (IPLD) from Kaplan–Meier curves. We re-analyzed IPLD to identify DPHs. Potential efficiency gains, when DPHs were present, of alternative statistical methods relative to standard log-rank based analysis were expressed as sample-size requirements for a fixed power level. Results: From 152 trials, we obtained IPLD on 129,401 patients. Among 304 Kaplan–Meier figures, 75 (24.7%) exhibited evidence of DPHs, including eight of 14 (57%) KM pairs from immunotherapy trials. Trial type [immunotherapy, odds ratio (OR), 4.29; 95% confidence interval (CI), 1.11–16.6], metastatic patient population (OR, 3.18; 95% CI, 1.26–8.05), and non-OS endpoints (OR, 3.23; 95% CI, 1.79–5.88) were associated with DPHs. In immunotherapy trials, alternative statistical approaches allowed for more efficient clinical trials with fewer patients (up to 74% reduction) relative to log-rank testing. Conclusions: DPHs were found in a notable proportion of time-to-event outcomes in published clinical trials in oncology and was more common for immunotherapy trials and non-OS endpoints. Alternative statistical methods, without proportional hazards assumptions, should be considered in the design and analysis of clinical trials when the likelihood of DPHs is high.

PURPOSE: Programmed cell death receptor ligand 1 (PD-L1) expression is the most studied biomarker to predict the efficacy of immune checkpoint inhibitors (ICIs), but its clinical significance is controversial. We estimated the distribution of PD-L1 expression scores (ie, tumor proportion score or combined proportion score) and the relationship between PD-L1 levels and ICIs’ impact on overall survival (OS). METHODS: We reconstructed, pooled, and analyzed individual-level data on 7,617 patients with cancer from 14 randomized clinical trials. The effects of ICIs were quantified using differences in 24-month restricted mean survival times (ΔRMSTs; ie, the increase in life expectancy truncated at 2 years associated with ICI therapy). In a simulation study, we compared standard randomized clinical trial designs with a trial design that leverages meta-analytic results like ours. RESULTS: Approximately 93% of patients had a PD-L1 expression ≤ 5% (66% of patients) or > 50% (27% of patients). OS improves with ICIs regardless of PD-L1 expression level, which predicts the benefits’ magnitude. For patients with non–small-cell lung cancer (NSCLC), ΔRMSTs ranged from 1.4 months (95% probability interval [PI], 0.7 to 2.2 months) for PD-L1 expression ≤ 1% to 4.1 months (95% PI, 3.2 to 5.2 months) for PD-L1 expression > 80%. For patients with non-NSCLC tumors, ΔRMSTs ranged from 0.8 months (95% PI, −0.1 to 1.7 months) to 2.3 months (95% PI, 1.3 to 4.4 months), again for PD-L1 expression levels of ≤ 1% and > 80%, respectively. Simulations suggested that designs tailored to meta-analytic results can detect the effects of ICIs in PD-L1 subgroups with higher probability (> 15%) than standard designs. CONCLUSION: The practice of dichotomizing the range of PD-L1 expression scores is inadequate for patient stratification. Meta-analytic estimates of the distribution of PD-L1 scores and subgroup-specific treatment effects can improve the designs of future trials of ICIs.

PURPOSE: The molecular drivers underlying mucinous tumor pathogenicity are poorly understood. GNAS mutations predict metastatic burden and treatment resistance in mucinous appendiceal adenocarcinoma. We investigated the pan-cancer clinicopathologic relevance of GNAS variants. METHODS: We assessed 58,043 patients with Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (IMPACT)–sequenced solid tumors to identify oncogenic variants, including GNAS , associated with mucinous tumor phenotype. We then performed comprehensive molecular analyses to compare GNAS- mutant (mut) and wild-type tumors across cancers. Gene expression patterns associated with GNAS- mut tumors were assessed in a The Cancer Genome Atlas cohort. Associations between GNAS variant status and peritoneal metastasis, first-line systemic therapy response, progression-free survival (PFS), and overall survival (OS) were determined using a propensity-matched subcohort of patients with metastatic disease. RESULTS: Mucinous tumors were enriched for oncogenic GNAS variants. GNAS was mutated in >1% of small bowel, cervical, colorectal, pancreatic, esophagogastric, hepatobiliary, and GI neuroendocrine cancers. Across these cancers, GNAS- mut tumors exhibited a generally conserved C-to-T mutation-high, aneuploidy-low molecular profile with co-occurring prevalent KRAS variants (65% of GNAS-mut tumors) and fewer TP53 alterations. GNAS- mut tumors exhibited recurrently comutated alternative tumor suppressors ( RBM10 , INPPL1 ) and upregulation of MAPK and cell surface modulators. GNAS- mut tumors demonstrate an increased prevalence of peritoneal metastases (odds ratio [OR], 1.7 [95% CI, 1.1 to 2.5]; P = .006), worse response to first-line systemic therapy (OR, 2.2 [95% CI, 1.3 to 3.8]; P = .003), and shorter PFS (median, 5.6 v 7.0 months; P = .047). In a multivariable analysis, GNAS mutated status was independently prognostic of worse OS (hazard ratio, 1.25 [95% CI, 1.01 to 1.56]; adjusted P = .04). CONCLUSION: Across the assessed cancers, GNAS- mut tumors exhibit a conserved molecular and clinical phenotype defined by mucinous tumor status, increased peritoneal metastasis, poor response to first-line systemic therapy, and worse survival.

We describe the long-term (1981–2008) dynamics of several physico-chemical and biological variables and how their changes may have influenced zooplankton structure in Lake Maggiore (Italy). Data was available for the 1981–1992 and 1995–2008 periods. Standardized time-series for temperature and total phosphorus (TP), chlorophyll-a, phytoplankton density (cel m⁻³), and cell size (µm³), as well as zooplankton structure (Copepoda, Cladocera, and Rotifera density, ind m⁻³) were smoothed using penalized B-splines and analyzed using Functional Principal Components (FPCs) to assess their dominant modes of variation. The first four FPCs explained 55% of 1981–1992 and 65% of 1995–2008 overall variation. Results showed that temperature fluctuated during the study period, particularly during 1988–1992 with a general tendency to increase. TP showed a declining trend with some reversions in the pattern observed in the years 1992, 1999, and 2000. Phytoplankton estimators and chlorophyll-a concentration showed a variable trend along the study period. Zooplankton groups also had a variable trend along the study period with a general increase in density of large carnivorous (mainly Bythotrephes longimanus) and a decrease of large herbivorous (mainly Daphnia), and a similar increase in the ratio of raptorial to microphagous rotifers. Our results suggest that the lake experienced a strong trophic change associated with oligotrophication, followed by pronounced climate-induced changes during the latter period. TP concentration was strongly associated with changes in abundance of some zooplankton taxa.