Real-world risk-stratified cancer survivorship pathways.

Abstract

36 Background: Risk-stratified survivorship care pathways are critical for meeting needs of cancer survivors and the oncology workforce. To support a clinical trial evaluating a survivorship model that transitions low-risk survivors to a primary care physician (PCP)-led survivorship clinic within an integrated healthcare system, we captured data on real-time clinical risk stratification of low-risk patients potentially eligible between 6 and 36 months after treatment cessation. Methods: After oncology stakeholder input, we developed a screening algorithm to identify low-risk breast and colorectal cancer (CRC) survivors from the electronic medical record based on data from pathology, treatment, and utilization records. The algorithm identified patients meeting study eligibility criteria: adult stage 0-IIb breast cancer or stage I-II CRC patients diagnosed with first primary cancer, excluding those with treatments indicative of high-risk or metastatic disease, ongoing ovarian suppression or trastuzumab treatment (breast), neoadjuvant chemotherapy (breast), or enrollment in other cancer clinical trials. Next, the treating oncologist was asked to confirm or deny patient eligibility based on low-risk criteria; if denied, ineligibility reason was requested. Characteristics and proportions of low-risk patients confirmed/denied eligibility and reasons for ineligibility are summarized. Results: 530 patients were identified and evaluated: 488 breast and 42 CRC. Mean age was 61 years (SD: 11.6, range 23-95); 96% female; 22% had stage 0 disease (breast only), 51% stage I, and 28% stage II. By cancer type, 390 breast patients were deemed eligible (80%); 31 CRC patients were eligible (74%). A greater proportion of Asian and Black patients were categorized eligible vs. ineligible (13% vs. 9%, and 25% vs.14%, respectively), and a smaller proportion of Hispanic and White were categorized eligible (26% vs. 33%, and 31% vs. 42%, respectively). Reasons for ineligibility included: suspicious for recurrence (6%), new primary disease (3%), complex case/condition (36%), patient preference (34%), and other/none (22%). “Complex case/condition” included reasons such as intolerance of chemotherapy, patient declined chemotherapy and/or endocrine treatment (breast), co-occurring hematology disorder; “other/none” included reasons such as current pregnancy Lynch syndrome, and no reason. Conclusions: Oncologists confirmed eligibility for 80% of algorithm-identified low-risk patients for referral to the PCP-led survivorship clinic. Of those ineligible, patient preference and complex case/condition were the most common reasons reported for ineligibility. Consensus-based risk algorithms supported by clinician review can quickly and effectively perform case identification of low-risk patients who may be appropriately transitioned to other settings for survivorship care.