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

Objectives To investigate the clinical significance of numeric and morphologic peripheral blood (PB) changes in coronavirus disease 2019 (COVID-19)–positive patients in predicting the outcome, as well as to compare these changes between critically ill COVID-19–positive and COVID-19–negative patients. Methods The study included 90 COVID-19–positive (51 intensive care unit [ICU] and 39 non-ICU) patients and 30 COVID-19–negative ICU patients. We collected CBC parameters (both standard and research) and PB morphologic findings, which were independently scored by two hematopathologists. Results All patients with COVID-19 demonstrated striking numeric and morphologic WBC changes, which were different between mild and severe disease states. More severe disease was associated with significant neutrophilia and lymphopenia, which was intensified in critically ill patients. Abnormal WBC morphology, most pronounced in monocytes and lymphocytes, was associated with more mild disease; the changes were lost with disease progression. Between COVID-19–positive and COVID-19–negative ICU patients, significant differences in morphology-associated research parameters were indicative of changes due to the severe acute respiratory syndrome coronavirus 2 virus, including higher RNA content in monocytes, lower RNA content in lymphocytes, and smaller hypogranular neutrophils. Conclusions Hospitalized patients with COVID-19 should undergo a comprehensive daily CBC with manual WBC differential to monitor for numerical and morphologic changes predictive of poor outcome and signs of disease progression.

Highlights d Endogenous glucocorticoid signaling shapes CD8 + T cell differentiation in tumors d The glucocorticoid receptor transactivates IL-10 and checkpoint receptor expression d Tumor monocyte-macrophage lineage cells produce glucocorticoid d Glucocorticoid signaling in CD8 + T cells reduces immune checkpoint blockade efficacy

The clinical trials landscape for GBM is characterized by long development times, inadequate dissemination of information, suboptimal go/no-go decision making, and low patient participation.

BACKGROUND Waldenström macroglobulinemia (WM) is preceded by asymptomatic WM (AWM), for which the risk of progression to overt disease is not well defined. METHODS We studied 439 patients with AWM, who were diagnosed and observed at Dana-Farber Cancer Institute between 1992 and 2014. RESULTS During the 23-year study period, with a median follow-up of 7.8 years, 317 patients progressed to symptomatic WM (72%). Immunoglobulin M 4,500 mg/dL or greater, bone marrow lymphoplasmacytic infiltration 70% or greater, β2-microglobulin 4.0 mg/dL or greater, and albumin 3.5 g/dL or less were all identified as independent predictors of disease progression. To assess progression risk in patients with AWM, we trained and cross-validated a proportional hazards model using bone marrow infiltration, immunoglobulin M, albumin, and beta-2 microglobulin values as continuous measures. The model divided the cohort into three distinct risk groups: a high-risk group with a median time to progression (TTP) of 1.8 years, an intermediate-risk group with a median TTP of 4.8 years, and a low-risk group with a median TTP of 9.3 years. We validated this model in two external cohorts, demonstrating robustness and generalizability. For clinical applicability, we made the model available as a Web page application ( www.awmrisk.com ). By combining two cohorts, we were powered to identify wild type MYD88 as an independent predictor of progression (hazard ratio, 2.7). CONCLUSION This classification system is positioned to inform patient monitoring and care and, for the first time to our knowledge, to identify patients with high-risk AWM who may need closer follow-up or benefit from early intervention.

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.

Chimeric antigen receptor (CAR) T-cells have emerged as an efficacious modality in patients with non-Hodgkin lymphoma (NHL) and multiple myeloma (MM). Clonal hematopoiesis of indeterminate potential (CHIP), a state in which mutations in hematopoietic cells give rise to a clonal population of cells, is more common in patients exposed to cytotoxic therapies, has been shown to influence inflammatory immune programs, and is associated with an adverse prognosis in patients with NHL and MM receiving autologous transplantation. We therefore hypothesized that CHIP could influence clinical outcomes in patients receiving CAR T-cell therapy. In a cohort of 154 patients with NHL or MM receiving CAR T-cells, we found that CHIP was present in 48% of patients and associated with increased rates of complete response and cytokine release syndrome severity, but only in patients younger than age 60 years. Despite these differences, CHIP was not associated with a difference in progression-free or overall survival, regardless of age. Our data suggest that CHIP can influence CAR T-cell biology and clinical outcomes, but, in contrast to autologous transplantation, CHIP was not associated with worse survival and should not be a reason to exclude individuals from receiving this potentially life-prolonging treatment.

PURPOSE Adequately prioritizing the numerous therapies and biomarkers available in late-stage testing for patients with glioblastoma (GBM) requires an efficient clinical testing platform. We developed and implemented INSIGhT (Individualized Screening Trial of Innovative Glioblastoma Therapy) as a novel adaptive platform trial (APT) to develop precision medicine approaches in GBM. METHODS INSIGhT compares experimental arms with a common control of standard concurrent temozolomide and radiation therapy followed by adjuvant temozolomide. The primary end point is overall survival. Patients with newly diagnosed unmethylated GBM who are IDH R132H mutation negative and with genomic data available for biomarker grouping are eligible. At the initiation of INSIGhT, three experimental arms (neratinib, abemaciclib, and CC-115), each with a proposed genomic biomarker, are tested simultaneously. Initial randomization is equal across arms. As the trial progresses, randomization probabilities adapt on the basis of accumulating results using Bayesian estimation of the biomarker-specific probability of treatment impact on progression-free survival. Treatment arms may drop because of low probability of treatment impact on overall survival, and new arms may be added. Detailed information on the statistical model and randomization algorithm is provided to stimulate discussion on trial design choices more generally and provide an example for other investigators developing APTs. CONCLUSION INSIGhT (NCT02977780) is an ongoing novel biomarker-based, Bayesian APT for patients with newly diagnosed unmethylated GBM. Our goal is to dramatically shorten trial execution timelines while increasing scientific power of results and biomarker discovery using adaptive randomization. We anticipate that trial execution efficiency will also be improved by using the APT format, which allows for the collaborative addition of new experimental arms while retaining the overall trial structure.