ArticleScientific reports2026
Exploration of real-world outcomes in patients with previously treated HR+/HER2- and triple negative metastatic breast cancer.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
10 authors.
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Abstract
Curated electronic health records offer valuable insights into real-world outcomes for patients with advanced tumors. We described real-world treatment effectiveness among patients with HR+/HER2- metastatic breast cancer (mBC) and metastatic triple-negative breast cancer (mTNBC) using ConcertAI Patient360™ Breast Cancer dataset. Patients initiating therapies selected based on literature review and data availability in the metastatic setting between January 1, 2016, and November 30, 2021, were included. Real-world response rate (rwRR), progression-free survival (rwPFS), overall survival (rwOS), time-to-next treatment (rwTTNT), and time-to-discontinuation (rwTTD) were assessed. Three HR+/HER2- mBC cohorts included 292 patients treated with palbociclib + fulvestrant, 274 patients treated with fulvestrant monotherapy, and 381 patients treated with paclitaxel-based therapy; the mTNBC cohort included 247 chemotherapy-treated patients. Median rwOS in three HR+/HER2- cohorts ranged from 15.6 to 32.3 months and was 13 months in mTNBC; median rwPFS ranged from 5.6 to 8.6 months, and 4.4 months, respectively. The alignment between several real-world and clinical trial endpoints is encouraging and supports the utility of real-world data in contextualizing outcomes, though interpretation may be influenced by data completeness and variability in clinical documentation. These insights are particularly relevant for populations with persistent unmet clinical needs.
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