UNLOCKING CHRONIC LYMPHOCYTIC LEUKEMIA (CLL) DISEASE STAGE IN REAL-WORLD DATA: CLINICAL NOTES AS THE PRIMARY SOURCE OF RAI AND BINET STAGING INFORMATION USING NORSTELLALINQ

Author(s)

Isabella Even-Chen, BA1, ilan behm, MPH2, Shefali Patel, MS3, Rahul Das, PhD4, Atharva Manjrekar, MS5, Juan Diego Irizarry-Cole, PhD1, Allison Perry, PhD1.
1Norstella, New York, NY, USA, 2Norstella, Englewood, CO, USA, 3Norstella, Ferndale, MI, USA, 4Norstella, Yardley, PA, USA, 5Norstella, West Hartford, CT, USA.
OBJECTIVES: To demonstrate that Rai and Binet staging in CLL are absent from claims and structured EHR fields and are accessible only through human-in-the-loop large language model (LLM) extracted clinical notes, and to characterize the treated CLL population for whom stage-stratified analyses are enabled by note-derived data.
METHODS: Using NorstellaLinQ’s US real-world linked open claims, structured EHR, and clinical notes (January 2019-September 2025), 204,756 incident CLL patients were identified. Structured claims and EHR fields were assessed for CLL staging data (Rai or Binet). LLM-extracted clinical notes were used to extract staging and mutation status for IGHV, TP53, and del(17p). Treatment patterns were characterized for the LLM-extracted-staged subpopulation and compared to the unstaged remainder. Staging is not a coded field; clinical notes represent the only available data source.
RESULTS: Rai and Binet classifications were absent from billng claims and structured EHR fields across the incident CLL population. LLM-extracted clinical notes identified staging documentation for 6,523 patients (4,833 early-stage; 1,690 late-stage) and biomarker status for 3,612, populations otherwise not assessable from structured data alone. Late-stage patients initiated treatment substantially earlier (51% within 90 days vs 24% of early-stage patients) and had longer average BTKi line 1 durations (484 days vs 381 days). LLM-extracted-staged patients showed higher rates of later-line therapy and BTKi rechallenging relative to the unstaged remainder.
CONCLUSIONS: CLL disease stage is not a coded variable in claims or structured EHR but can be recovered from unstructured clinical documentation. LLM-extracted staging unlocks analyses entirely inaccessible from structured data alone, establishing a methodological case for its integration as a prerequisite for rigorous CLL RWE supporting HTA and coverage decisions.

Conference/Value in Health Info

2026-11, ISPOR Europe 2026, Vienna, Austria

Value in Health, Volume 29, Issue 12S

Code

CO67

Topic

Clinical Outcomes, Epidemiology & Public Health, Real World Data & Information Systems

Disease

Oncology

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