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BackgroundThe cumulative, health system-wide survival benefit of immune checkpoint inhibitors (ICIs) is unclear, particularly among real-world patients with limited life expectancies and among subgroups poorly represented on clinical trials. We sought to determine the health system-wide survival impact of ICIs.MethodsWe identified all patients receiving PD-1/PD-L1 or CTLA-4 inhibitors from 2010 to 2023 in the national Veterans Health Administration (VHA) system (ICI cohort) and all patients who received non-ICI systemic therapy in the years before ICI approval (historical control). ICI and historical control cohorts were matched on multiple cancer-related prognostic factors, comorbidities, and demographics. The effect of ICI on overall survival was quantified with Cox regression incorporating matching weights. Cumulative life-years gained system-wide were calculated from the difference in adjusted 5-year restricted mean survival times.ResultsThere were 27,322 patients in the ICI cohort and 69,801 patients in the historical control cohort. Among ICI patients, the most common cancer types were NSCLC (46%) and melanoma (10%). ICI demonstrated a large OS benefit in most cancer types with heterogeneity across cancer types (NSCLC: adjusted HR [aHR] 0.56, 95% confidence interval [CI] 0.54-0.58, p

PurposeReal world evidence is crucial to understanding the diffusion of new oncologic therapies, monitoring cancer outcomes, and detecting unexpected toxicities. In practice, real world evidence is challenging to collect rapidly and comprehensively, often requiring expensive and time-consuming manual case-finding and annotation of clinical text. In this Review, we summarise recent developments in the use of artificial intelligence to collect and analyze real world evidence in oncology.MethodsWe performed a narrative review of the major current trends and recent literature in artificial intelligence applications in oncology.ResultsArtificial intelligence (AI) approaches are increasingly used to efficiently phenotype patients and tumors at large scale. These tools also may provide novel biological insights and improve risk prediction through multimodal integration of radiographic, pathological, and genomic datasets. Custom language processing pipelines and large language models hold great promise for clinical prediction and phenotyping.ConclusionsDespite rapid advances, continued progress in computation, generalizability, interpretability, and reliability as well as prospective validation are needed to integrate AI approaches into routine clinical care and real-time monitoring of novel therapies.

BACKGROUND: One year of adjuvant durvalumab following concurrent chemoradiotherapy significantly improves progression-free survival (PFS) and overall survival (OS) for patients with stage III non-small cell lung cancer (NSCLC). However, the optimal length of adjuvant therapy has not been determined. METHODS: We identified patients with stage III NSCLC treated with definitive chemoradiation and adjuvant durvalumab from November 2017 to April 2021 from the United States Veterans Affairs system. Predictors of early durvalumab discontinuation were evaluated with Cox proportional hazards regression. The effect of differing durations of durvalumab treatment (up to 6, 9, and 12 months) on PFS and OS were compared with a marginal structural model and time-dependent Cox modelling. RESULTS: We included 1006 patients with stage III non-small cell lung cancer who received concurrent chemoradiotherapy and at least one dose of adjuvant durvalumab. The median duration of durvalumab treatment was 7 months (interquartile range 2.8-11.5) and 31% completed the intended durvalumab course. The most common reasons for early discontinuation were tumour progression (22%), immune-related adverse events (15%), and non-immune-related toxicity (6.0%), Marginal structural models suggested similar PFS for 9 months versus 12 months of durvalumab treatment and inferior PFS for 6 months versus 12 months. CONCLUSIONS: A substantial proportion of patients undergoing adjuvant durvalumab discontinue therapy early due to toxicity, and shorter durvalumab treatment durations may provide similar disease control to 12 months of therapy. Prospective randomised controlled studies are needed to characterise the optimal durvalumab treatment duration in locally advanced NSCLC patients.

One year of durvalumab following concurrent chemoradiotherapy improves progression-free (PFS) and overall survival (OS) for patients with stage III non-small cell lung cancer (NSCLC). However, the real-world efficacy of durvalumab has not been determined. We conducted a multi-center observational cohort study across the Veterans Health Administration, including patients with stage III NSCLC who received concurrent chemoradiotherapy and durvalumab, compared to patients who received concurrent chemoradiotherapy alone. Kaplan-Meier and Cox regression approaches were used to identify factors associated with PFS and OS. We calculated a hazard ratio and efficacy-effectiveness factor to compare OS of veterans to the referenced clinical trial population. A total of 1006 patients with stage III NSCLC who received concurrent chemoradiotherapy and at least one dose of durvalumab from November 2017 to April 2021 were compared to 989 patients who received concurrent chemoradiotherapy alone from January 2015 to December 2016. Adjuvant durvalumab was associated with higher PFS (HR 0.62, 95% CI 0.55-0.70, p < 0.001) and OS (HR 0.57, 95% CI 0.50-0.66, p < 0.001). OS was shorter in veterans compared to PACIFIC (HR 1.24, 95% CI 1.03-1.48, p = 0.02: EE gap 0.73). OS of veterans with stage III NSCLC treated with adjuvant durvalumab is improved compared to a modern comparator but is reduced compared to the PACIFIC population.

Current cell-free DNA (cfDNA) next generation sequencing (NGS) precision oncology workflows are typically limited to targeted and/or disease-specific applications. In advanced cancer, disease burden and cfDNA tumor content are often elevated, yielding unique precision oncology opportunities. We sought to demonstrate the utility of a pan-cancer, rapid, inexpensive, whole genome NGS of cfDNA approach (PRINCe) as a precision oncology screening strategy via ultra-low coverage (~0.01x) tumor content determination through genome-wide copy number alteration (CNA) profiling. We applied PRINCe to a retrospective cohort of 124 cfDNA samples from 100 patients with advanced cancers, including 76 men with metastatic castration-resistant prostate cancer (mCRPC), enabling cfDNA tumor content approximation and actionable focal CNA detection, while facilitating concordance analyses between cfDNA and tissue-based NGS profiles and assessment of cfDNA alteration associations with mCRPC treatment outcomes. Therapeutically relevant focal CNAs were present in 42 (34%) cfDNA samples, including 36 of 93 (39%) mCRPC patient samples harboring AR amplification. PRINCe identified pre-treatment cfDNA CNA profiles facilitating disease monitoring. Combining PRINCe with routine targeted NGS of cfDNA enabled mutation and CNA assessment with coverages tuned to cfDNA tumor content. In mCRPC, genome-wide PRINCe cfDNA and matched tissue CNA profiles showed high concordance (median Pearson correlation = 0.87), and PRINCe detectable AR amplifications predicted reduced time on therapy, independent of therapy type (Kaplan-Meier log-rank test, chi-square = 24.9, p < 0.0001). Our screening approach enables robust, broadly applicable cfDNA-based precision oncology for patients with advanced cancer through scalable identification of therapeutically relevant CNAs and pre-/post-treatment genomic profiles, enabling cfDNA- or tissue-based precision oncology workflow optimization.

Metastasis is the primary cause of cancer mortality, and cancer frequently metastasizes to the liver. It is not clear whether liver immune tolerance mechanisms contribute to cancer outcomes. We report that liver metastases diminish immunotherapy efficacy systemically in patients and preclinical models. Patients with liver metastases derive limited benefit from immunotherapy independent of other established biomarkers of response. In multiple mouse models, we show that liver metastases siphon activated CD8.sup.+ T cells from systemic circulation. Within the liver, activated antigen-specific Fas.sup.+CD8.sup.+ T cells undergo apoptosis following their interaction with FasL.sup.+CD11b.sup.+F4/80.sup.+ monocyte-derived macrophages. Consequently, liver metastases create a systemic immune desert in preclinical models. Similarly, patients with liver metastases have reduced peripheral T cell numbers and diminished tumoral T cell diversity and function. In preclinical models, liver-directed radiotherapy eliminates immunosuppressive hepatic macrophages, increases hepatic T cell survival and reduces hepatic siphoning of T cells. Thus, liver metastases co-opt host peripheral tolerance mechanisms to cause acquired immunotherapy resistance through CD8.sup.+ T cell deletion, and the combination of liver-directed radiotherapy and immunotherapy could promote systemic antitumor immunity. Liver metastases reduce clinical and preclinical immune-checkpoint inhibitor efficacy through hepatic siphoning of circulating activated CD8.sup.+ T cells, but therapeutic benefit can be improved by combining immunotherapy with liver-directed radiotherapy., Author(s): Jiali Yu [sup.1] [sup.2] , Michael D. Green [sup.2] [sup.3] [sup.4] , Shasha Li [sup.1] [sup.2] [sup.5] , Yilun Sun [sup.3] [sup.6] , Sara N. Journey [sup.7] , Jae [...]

We assessed the efficacy, tolerability, and cost-effectiveness of a novel neoadjuvant regimen comprising docetaxel-cyclophosphamide alternating with epirubicin-cisplatin (ddDCEP) administered biweekly for 16 weeks in 116 patients with early triple-negative breast cancer. This regimen achieved a high pathological complete response (ypT0/TisN0) rate of 55.2% and favorable survival outcomes (30-month event-free survival, 91.2%; overall survival, 97%). Febrile neutropenia was observed in 4.3% of patients, and 98% completed at least six of eight cycles. ddDCEP was more cost-effective than contemporary carboplatin-based regimens. This novel approach offers an economically viable and effective alternative to current chemoimmunotherapy regimens, and merits further investigation. [ABSTRACT FROM AUTHOR]