Treatment Decision Making at Diagnosis for Children Presenting With Advanced Cancer in Low- and Middle-Income...

Although most children diagnosed with cancer live in low- and middle-income countries (LMICs), research exploring decision making in these settings remains sparse. When children present with advanced cancer in LMICs, local centers may lack resources to provide treatment required to achieve cure. Existing treatment guidelines often do not account for contextual and resource variations influencing decision making. This qualitative study sought to understand physician approaches to treatment decision making for children presenting with advanced cancer at diagnosis in LMICs.

Semistructured interviews were conducted with 36 physicians caring for children with cancer across all world regions and representing diverse income levels. Interviews were conducted in English, audio-recorded, and transcribed. Inductive content analysis focused on decision-making approaches.

Most participants were female (n = 24; 67%), older than 36 years (n = 32; 89%), and practiced at centers caring for >100 new childhood cancer cases annually (n = 26; 72%) in lower-middle-income countries (n = 20; 55%). A spectrum of cancers were reported as advanced at diagnosis, with no single diagnosis predominating. Physicians generally recommended four treatment approaches (eg, curative-intent, non-curative-intent, referral, or limited chemotherapy trial), resulting in seven outcome pathways based on whether a family accepted, challenged, or declined the proposed treatment. Four decision-making approaches (eg, physician-led, family-led, participatory, or externally influenced) informed determinations of goals of care focused on optimizing prognostic outcomes, providing individualized care, and committing to treating all children, irrespective of differences in patient/family circumstances.

Physicians caring for children with cancer in LMICs navigate complex treatment decision making, considering diverse treatment paths and goals. Pragmatic, evidence-based interventions are needed to guide decision making, flexible to local constraints.