{"data":{"event":{"id":"0b9c2e6d-1e5b-4164-be95-f9aff15f0797","slug":"causal-multi-modal-ai-for-personalized-chemosensitivity-prediction-66d22c3fa2","title":"Causal multi-modal AI for personalized chemosensitivity prediction","short_summary":"arXiv:2609.13567v1 Announce Type: new \nAbstract: Chemotherapy improves survival for some patients with breast cancer, but doctors cannot reliably predict who. Current guidelines rely on recurrence scores as a proxy for treatment benefit, which may contribute to the overprescription of chemotherapy. Here we present a causal multi-modal AI model that predicts personalized chemosensitivity using routinely collected pathology and clinical information. We developed our model on a multi-national dataset of 9,141 patients (twelve cohorts, nine countries) and evaluated it on another 1,994 patients (fi","full_description":"arXiv:2609.13567v1 Announce Type: new \nAbstract: Chemotherapy improves survival for some patients with breast cancer, but doctors cannot reliably predict who. Current guidelines rely on recurrence scores as a proxy for treatment benefit, which may contribute to the overprescription of chemotherapy. Here we present a causal multi-modal AI model that predicts personalized chemosensitivity using routinely collected pathology and clinical information. We developed our model on a multi-national dataset of 9,141 patients (twelve cohorts, nine countries) and evaluated it on another 1,994 patients (five cohorts, three countries). The model generated treatment-specific recurrence probabilities for each patient, with near-perfect calibration and strong prognostic discrimination across both 5- and 10-year follow-up horizons. Moreover, its chemotherapy benefit predictions demonstrated robust predictive performance, and out-performed existing recurrence-score-based tests. Compared to the standard of care, using the model to support personally tailored therapeutic decisions could reduce the number of patients receiving chemotherapy by 30% while achieving the same recurrence-free rate. Tumors predicted to be highly chemosensitive displayed concordant molecular and morphological programs of proliferation, cell cycle progression, and replication stress. The model's predictive capabilities transferred zero-shot to non-breast cancers, indicating our causal multi-modal AI approach may provide a universal strategy to predict treatment outcomes across cancer types.\n\nUpdate (2026-09-18): In Sudan, attacks on hospitals force patients to make dangerous journeys. Amid a civil war in Sudan, it’s now difficult for people with cancer and other long-term illnesses to receive treatment that was once readily available","ledger_type":"benefit","primary_domain_id":"8f1af1b9-7302-4b51-aae9-fdfac04d158a","event_status":"provisional","event_date":"2026-09-16T00:00:00.000Z","discovery_date":"2026-09-16T00:00:00.000Z","first_published_date":"2026-09-16T00:00:00.000Z","last_reviewed_date":"2026-09-18T00:00:00.000Z","geographic_scope":"International","affected_population":null,"base_impact_tier":1,"base_score":"1.00","attribution_multiplier":"0.1000","evidence_multiplier":"0.2000","realization_multiplier":"0.2000","durability_multiplier":"0.5000","current_event_score":"0.002000","confidence_level":"low","score_explanation":"Ingest update: independent source raised evidence; added a follow-up source. 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Attribution stays unspecified until a release is identified.","attribution_confidence":"medium","first_used_date":"2026-09-16T00:00:00.000Z","model_version_if_known":null,"review_status":"approved","created_at":"2026-09-17T01:00:48.679Z","model_slug":"unspecified-ai-system","model_name":"Unspecified AI system","identity_class":"unknown","is_internal":false,"family_name":"Unspecified","family_slug":"unknown-unspecified","organization_name":"Unknown","organization_slug":"unknown"}],"sources":[{"id":"6123713f-db79-44cd-aa7f-1e29592e5137","event_id":"0b9c2e6d-1e5b-4164-be95-f9aff15f0797","url":"https://arxiv.org/abs/2609.13567","canonical_url":"https://arxiv.org/abs/2609.13567","source_type":"preprint","publisher":"arXiv cs.AI","author":null,"publication_date":"2026-09-16T00:00:00.000Z","retrieved_at":"2026-09-17T01:00:48.709Z","title":"Causal multi-modal AI for personalized chemosensitivity prediction","excerpt":"arXiv:2609.13567v1 Announce Type: new \nAbstract: Chemotherapy improves survival for some patients with breast cancer, but doctors cannot reliably predict who. Current guidelines rely on recurrence scores as a proxy for treatment benefit, which may contribute to the overprescription of chemotherapy. Here we present a causal multi-modal AI model that predicts personalized chemosensitivity using routinely collected pathology and clinical information. We developed our model on a multi-national datas","content_hash":null,"source_reliability_class":"medium","is_primary_source":true,"is_independent":true,"is_peer_reviewed":false,"archived_url":null,"created_at":"2026-09-17T01:00:48.709Z"},{"id":"2e8a38b9-e856-45fd-acbc-829e9c630b68","event_id":"0b9c2e6d-1e5b-4164-be95-f9aff15f0797","url":"https://www.statnews.com/2026/09/18/sudan-civil-war-cancer-treatment-wartime-tom-catena-mother-mercy-hospital/?utm_campaign=rss","canonical_url":"https://www.statnews.com/2026/09/18/sudan-civil-war-cancer-treatment-wartime-tom-catena-mother-mercy-hospital/?utm_campaign=rss","source_type":"journalism","publisher":"STAT","author":null,"publication_date":"2026-09-18T00:00:00.000Z","retrieved_at":"2026-09-18T09:01:02.208Z","title":"In Sudan, attacks on hospitals force patients to make dangerous journeys","excerpt":"Amid a civil war in Sudan, it’s now difficult for people with cancer and other long-term illnesses to receive treatment that was once readily available","content_hash":null,"source_reliability_class":"medium","is_primary_source":false,"is_independent":true,"is_peer_reviewed":false,"archived_url":null,"created_at":"2026-09-18T09:01:02.208Z"}],"claims":[{"id":"2135a7ab-8b27-4ea4-8bdb-8f24a538264a","event_id":"0b9c2e6d-1e5b-4164-be95-f9aff15f0797","claim_text":"Causal multi-modal AI for personalized chemosensitivity prediction","claim_type":"outcome","claim_status":"supported","confidence_score":null,"created_at":"2026-09-17T01:00:48.722Z","updated_at":"2026-09-17T01:00:48.722Z"}],"revisions":[{"id":"39f28188-d1d0-4eb4-ad48-b15090eb56f5","event_id":"0b9c2e6d-1e5b-4164-be95-f9aff15f0797","model_id":null,"previous_score":"0.000000","new_score":"0.001000","previous_factors":{},"new_factors":{"evidence":0.1,"base_score":1,"durability":0.5,"attribution":0.1,"realization":0.2},"change_reason":"Auto-published from news ingest.","trigger_type":"news_ingest","trigger_source_ids":null,"reviewer_id":null,"review_status":"published","created_at":"2026-09-17T01:00:48.735Z"},{"id":"ae9520d4-57c4-49e2-aeb7-4933060c25a1","event_id":"0b9c2e6d-1e5b-4164-be95-f9aff15f0797","model_id":null,"previous_score":"0.001000","new_score":"0.002000","previous_factors":{"tier":1,"evidence":0.1,"base_score":1,"durability":0.5,"attribution":0.1,"realization":0.2},"new_factors":{"tier":1,"models":["535014f7-c941-4d39-aa9b-8f9c1d3d07b7"],"evidence":0.2,"base_score":1,"durability":0.5,"attribution":0.1,"realization":0.2},"change_reason":"Ingest update: independent source raised evidence; added a follow-up source.","trigger_type":"ingest_update","trigger_source_ids":["2e8a38b9-e856-45fd-acbc-829e9c630b68"],"reviewer_id":null,"review_status":"published","created_at":"2026-09-18T09:01:02.240Z"}],"secondary":[]},"methodology_version":"0.1"}