Immunotherapy: New Strategies for the Treatment of Gynecologic Malignancies.

Over the past decade, the ability of cancer cells to evade immune destruction has become recognized as one of the hallmarks of cancer. This understanding has paved the way for the development of novel therapeutic agents that can enhance activation of antitumor immune responses or reverse immunosuppressive mechanisms through which tumors escape immune-mediated rejection. The treatment of gynecologic cancers remains a therapeutic challenge, as these malignancies are often diagnosed in advanced stages, and many patients relapse despite appropriate management. Clinical trials have shown efficacy for various immunotherapeutic strategies, especially the use of tumor-targeting antibodies; enhancement of tumor antigen presentation, such as with vaccines and toll-like receptor agonists; and the targeting of immunosuppressive mechanisms, such as via checkpoint blockade. Emerging data on new and combination approaches currently under investigation provide a strong rationale for these approaches.

Concordance of Clinician-Documented and Imaging Response in Patients With Stage IV Non-Small Cell Lung Cancer Treated With First-Line Therapy.

Importance: In observational oncology studies of solid tumors, response to treatment can be evaluated based on electronic health record (EHR) documentation (clinician-assessed response [CAR]), an approach different from standardized radiologist-measured response (Response Evaluation Criteria in Solid Tumours [RECIST] 1.1). Objective: To evaluate the feasibility of an imaging response based on RECIST (IRb-RECIST) and the concordance between CAR and imaging response based on RECIST assessments, and investigate discordance causes. Design, Setting, and Participants: This cohort study used an EHR-derived, deidentified database that included patients with stage IV non-small cell lung cancer (NSCLC) diagnosed between January 1, 2011, to June 30, 2019, selected from 3 study sites. Data analysis was conducted in August, 2020. Exposures: Undergoing first-line therapy and imaging assessments of response to treatment. Main Outcomes and Measures: In this study, CAR assessments (referred to in prior publications as "real-world response" [rwR]) were defined as clinician-documented changes in disease burden at radiologic evaluation time points; they were abstracted manually and assigned to response categories. The RECIST-based assessments accommodated routine practice patterns by using a modified version of RECIST 1.1 (IRb-RECIST), with independent radiology reads. Concordance was calculated as the percent agreement across all response categories and across a dichotomous stratification (response [complete or partial] vs no response), unconfirmed or confirmed. Results: This study found that, in 100 patients evaluated for concordance, agreement between CAR and IRb-RECIST was 71% (95% CI, 61%-80%), and 74% (95% CI, 64%-82%) for confirmed and unconfirmed response, respectively. There were more responders using CAR than IRb-RECIST (40 vs 29 with confirmation; 64 vs 43 without confirmation). The main sources of discordance were the different use of thresholds for tumor size changes by RECIST vs routine care, and unavailable baseline or follow-up scans resulting in inconsistent anatomic coverage over time. Conclusions and Relevance: In this cohort study of patients with stage IV NSCLC, we collected routine-care imaging, showing the feasibility of response evaluation using IRb-RECIST criteria with independent centralized review. Concordance between CAR and centralized IRb-RECIST was moderate. Future work is needed to evaluate the generalizability of these results to broader populations, and investigate concordance in other clinical settings.

Characterization of a Real-World Response Variable and Comparison with RECIST-Based Response Rates from Clinical Trials in Advanced NSCLC.

INTRODUCTION: Effectiveness metrics for real-word research, analogous to clinical trial ones, are needed. This study aimed to develop a real-world response (rwR) variable applicable to solid tumors and to evaluate its clinical relevance and meaningfulness. METHODS: This retrospective study used patient cohorts with advanced non-small cell lung cancer from a nationwide, de-identified electronic health record (EHR)-derived database. Disease burden information abstracted manually was classified into response categories anchored to discrete therapy lines (per patient-line). In part 1, we quantified the feasibility and reliability of data capture, and estimated the association between rwR status and real-world progression-free survival (rwPFS) and real-world overall survival (rwOS). In part 2, we investigated the correlation between published clinical trial overall response rates (ORRs) and real-world response rates (rwRRs) from corresponding real-world patient cohorts. RESULTS: In part 1, 85.4% of patients (N = 3248) had at least one radiographic assessment documented. Median abstraction time per patient-line was 15.0 min (IQR 7.8-28.1). Inter-abstractor agreement on presence/absence of at least one assessment was 0.94 (95% CI 0.92-0.96; n = 503 patient-lines abstracted in duplicate); inter-abstractor agreement on best confirmed response category was 0.82 (95% CI 0.78-0.86; n = 384 with at least one captured assessment). Confirmed responders at a 3-month landmark showed significantly lower risk of death and progression in rwOS and rwPFS analyses across all line settings. In part 2, rwRRs (from 12 rw cohorts) showed a high correlation with trial ORRs (Spearman's ρ = 0.99). CONCLUSIONS: We developed a rwR variable generated from clinician assessments documented in EHRs following radiographic evaluations. This variable provides clinically meaningful information and may provide a real-world measure of treatment effectiveness.

Concordance of real-world versus conventional progression-free survival from a phase 3 trial of endocrine therapy as first-line treatment for metastatic breast cancer.

There is growing interest in leveraging real-world data to complement knowledge gained from randomized clinical trials and inform the design of prospective randomized studies in oncology. The present study compared clinical outcomes in women with metastatic breast cancer who received letrozole as first-line monotherapy in oncology practices across the United States versus patients in the letrozole-alone cohort of the PALOMA-2 phase 3 trial. The real-world cohort (N = 107) was derived from de-identified patient data from the Flatiron Health electronic health record database. The clinical trial cohort (N = 222) comprised postmenopausal women in the letrozole-alone arm of PALOMA-2. Patients in the real-world cohort received letrozole monotherapy per labeling and clinical judgment; patients in PALOMA-2 received letrozole 2.5 mg/d, continuous. Real-world survival and response rates were based on evidence of disease burden curated from clinician notes, radiologic reports, and pathology reports available in the electronic health record. Progression-free survival and objective response rate in PALOMA-2 were based on Response Evaluation Criteria in Solid Tumors v1.1. Concordance of survival and response rates were retrospectively assessed using inverse probability of treatment weighting-adjusted Cox regression analysis. Inverse probability of treatment weighting-adjusted Cox regression results showed similar median progression-free survival in the real-world and PALOMA-2 cohorts (18.4 and 16.6 months, respectively): the hazard ratio using real-world data as reference was 1.04 (95% CI, 0.69-1.56). No significant difference was observed in response rates: 41.8% in the real-world cohort vs 39.4% in the PALOMA-2 cohort (odds ratio using real-world data as reference: 0.91 [95% CI, 0.57-1.44]). These findings indicate that data abstracted from electronic health records with proper quality controls can yield meaningful information on clinical outcomes. These data increase confidence in the use of real-world assessments of progression and response as efficacy endpoints. Trial registration NCT01740427; Funding: Pfizer.

Lighting the fires within: the cell biology of autoinflammatory diseases.

Autoinflammatory diseases are characterized by seemingly unprovoked pathological activation of the innate immune system in the absence of autoantibodies or autoreactive T cells. Discovery of the causative mutations underlying several monogenic autoinflammatory diseases has identified key regulators of innate immune responses. Recent studies have highlighted the role of misfolding, oligomerization and abnormal trafficking of pathogenic mutant proteins in triggering autoinflammation, and suggest that more common rheumatic diseases may have an autoinflammatory component. This coincides with recent discoveries of new links between endoplasmic reticulum stress and inflammatory signalling pathways, which support the emerging view that autoinflammatory diseases may be due to pathological dysregulation of stress-sensing pathways that normally function in host defence.