Moving on After Breast Cancer Trial for Depressed Breast Cancer Survivors in Pakistan

Breast cancer is the most common cancer among women worldwide, and many survivors experience comorbid mental health conditions such as depression and anxiety, which can significantly worsen health outcomes and increase mortality. This large-scale trial in Pakistan aims to evaluate the clinical and cost-effectiveness of a three-stage adaptive intervention to manage depression among breast cancer survivors. Using a Sequential, Multiple Assignment, Randomised Trial (SMART) design, the study will recruit 26,372 participants aged 18 and above who have completed initial breast cancer treatment (surgery and/or chemotherapy or radiotherapy). Participants will be identified through primary care units, outpatient departments, oncology clinics in public hospitals, and charitable organisations across Pakistan. Depression will be screened using the Patient Health Questionnaire PHQ-9, with diagnosis confirmed by the Structured Clinical Interview Schedule of DSM (SCID). Those randomised to the intervention arm will receive adaptive interventions: starting with low-intensity guided self-help, followed by a high-intensity cognitive behavioural therapy-based programme called "Moving On After Breast Cancer Plus" (Moving on ABC Plus), and for non-responders, an additional pharmacological component will be introduced. Participants in both adaptive intervention and enhance usual care groups will be assessed at multiple time points-baseline, 6, 18, 30, and 48 weeks post-randomisation-using validated tools to measure depression (primary outcome), and anxiety, self-esteem, intrusive thoughts, health-related quality of life, satisfaction with services, and health resource use (secondary outcomes). The study will also include qualitative interviews and focus groups discussions with patients, caregivers, healthcare providers, and policymakers to identify barriers and facilitators to implementation and ensure the intervention is both contextually appropriate and scalable.