A report from Charles River Associates, commissioned by BeOne Medicines USA and published in September 2026, documents ongoing disparities in the treatment of chronic lymphocytic leukemia (CLL). The analysis reveals that minority patients and those in rural areas receive guideline-recommended therapies far less often than white patients, with chemotherapy remaining the default option despite its inferior outcomes. These gaps stem from provider education deficits, geographic barriers, and limited patient awareness, rather than insurance design alone.
Kirsten Axelsen, the study’s lead author and a consultant at Charles River Associates, attributes the overuse of chemotherapy to systemic failures. While insurance coverage may contribute, the root causes lie in provider knowledge gaps, uneven awareness of treatment options, and structural obstacles such as limited access to specialists. The consequences are severe: patients denied targeted therapies experience shorter survival rates, more adverse effects, and heavier burdens on caregivers and work capacity.
AI’s double-edged sword in CLL care
The report also examines how artificial intelligence is transforming both patient decision-making and insurer prior authorization processes. CLL patients increasingly rely on AI-powered tools for treatment information, but this trend carries risks. Axelsen points to cases where patients arrived at oncology appointments demanding unproven treatments like ivermectin or requesting chemotherapy breaks, likely due to misinformation from unreliable online sources. On the insurer side, AI-driven denials raise concerns about clinician oversight. When coverage decisions depend solely on fragmented or incomplete AI-generated data, providers lack the ability to challenge rejections based on patient-specific clinical details.
The report warns that payers and policymakers are unprepared for the next generation of CLL therapies, including BTK degraders and bispecific antibodies. These treatments, though more effective, come with higher costs and require routine biomarker testing—a practice not yet standardized in most medical settings. While states like Florida, Texas, California, and New Jersey have made progress in mandating coverage for biomarker tests or reducing step therapy barriers, awareness among physicians and patients remains inconsistent.
Policy gaps leave disparities unaddressed
Upcoming state-level reports, due in the coming weeks, will evaluate how policy changes translate into real-world care. Early findings indicate that even when barriers are removed, such as copay waivers for testing, disparities persist due to provider and patient unfamiliarity with available options. The report’s recommendations for AI in care decisions stress transparency and human oversight. Health plans using AI for prior authorization must disclose when automated systems influence coverage denials, as many insurers currently lack clear policies on how AI factors into claims decisions. Without this disclosure, patients may incorrectly assume denials reflect medical necessity rather than data gaps or flawed AI interpretations.
Structured pathways for providers to challenge AI-driven denials are essential, according to the findings. The report describes cases where oncologists could not overturn rejections for biomarker testing or targeted therapies because insurers offered no formal appeals process tied to patient-specific clinical details. One example involved a hematologist treating a rural patient whose coverage for a genetic test was denied after an AI flagged the patient’s age as a risk factor, despite the test being critical for identifying eligibility for a newer therapy. The provider had no way to explain the patient’s symptoms or prior treatment failures, which would have justified the test under guideline recommendations.
Biomarker testing is identified as the most urgent priority for health plans. States with mandates for CLL-related genetic screening, such as Florida’s copay-free requirement, show uneven adoption among physicians. Axelsen notes that even where policies exist, many doctors remain unaware of relevant biomarkers or how to order tests. Patients, meanwhile, often lack knowledge that testing could determine eligibility for more effective treatments.
