Building Treatment Algorithms Around Biomarker-Driven Therapies

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The integration of biomarker-driven therapies into treatment algorithms requires individualized approaches considering multiple patient and disease factors. Elisa Krill-Jackson, MD, emphasized distinguishing between primary and secondary endocrine resistance, noting that patients with long disease-free intervals after adjuvant therapy often respond well to less-intensive approaches, sometimes even single-agent hormonal therapy without CDK4/6 inhibitors. The assessment includes disease burden (visceral vs bone only), pace of progression, and duration of remission to guide treatment intensity decisions.

Future treatment algorithms will incorporate emerging agents, particularly oral SERDs that may provide fulvestrant-equivalent efficacy without requiring painful monthly injections. Krill expressed enthusiasm for oral SERD approval beyond ESR1-mutated patients, as these agents demonstrated comparable efficacy to fulvestrant in nonmutated patients while improving convenience and quality of life. The evolving landscape suggests movement toward oral combination regimens that maintain efficacy while reducing treatment burden.

The treatment algorithm philosophy emphasizes matching treatment intensity to disease characteristics while preserving future options. Patients with rapidly progressive, bulky visceral disease require immediate implementation of most effective combinations, such as the inavolisib triplet, whereas those with indolent disease can proceed with sequential approaches using doublets followed by additional hormonal therapy lines. The commitment to continued hormonal therapy as long as clinically appropriate, including potential PIK3CA inhibitor rechallenge after chemotherapy in previously unexposed patients, reflects the expanding therapeutic options available. Success requires comprehensive utilization of all available agents throughout the patient’s treatment journey, emphasizing the importance of strategic sequencing and biomarker-guided selection to optimize long-term outcomes.