Reducing Delays in Cancer Care in sub-Saharan Africa

Research question Development and evaluation of an intervention to reduce delay in cancer treatment. Background

Cancer is the second largest cause of death in low- and middle-income countries (LMIC).(1) However, cancer outcomes remain much worse in LMIC than in high-income counties (HIC), largely due to delayed treatment.(2–5) This is reflected in a recent prioritisation exercise that identified early diagnosis as the most pressing topic for cancer research in LMIC.(6) The research that has been done mostly concerns delay in presentation to the formal health services.(7) Yet about half the delay between symptom and treatment initiation arises after first presentation.(8,9) It is this gap we aim to close. In so doing we will study the health system, examining how interventions impact the system (e.g., by creating new demand), and how the system impacts on interventions (e.g., by facilitating continuing professional education).

Our findings will provide insight into how health service improvements across different health providers can be applied to other conditions apart from the cancer referral pathway. Interventions

We shall develop, pilot and evaluate two interventions to reduce delay within the formal health sector. First, we will intervene in frontline primary care services to improve referral practice, and communication with patients. Second, we will partner with the voluntary sector to provide peer navigation support, particularly for the most vulnerable patients.

Sites and symptom clusters

Balancing cost and breadth of context, we will work in three sites that include different LMIC, different parts of Sub-Saharan Africa (SSA), different socio-cultural features, and a variegated urban and rural landscape: Oyo and Kano states (Nigeria) and Nairobi County (Kenya). We will study patients with symptom clusters for cancers: uterus, colon, breast, lung, stomach/oesophagus, bladder/prostate/kidney, and head/neck.

Evaluating the interventions

The interventions will have a formative function during piloting where qualitative and quantitative data will be used iteratively to refine the intervention. The two intervention types will then be rolled out over 200 primary care providers (clusters) in an independent evaluation (10) in the form of a factorial cluster randomised trial and multi-level process evaluation.

Outcomes from the clinic intervention include clinician knowledge and behaviour assessed in two ways: 1) vignettes and 2) standardised patient multi-component scores. Both interventions will also be assessed by following up relevant patients to compare time to histological diagnosis and treatment initiation.

A health systems approach

Throughout the study, we will examine how aspects of the health system interact with the intervention by observing the interventions as they are implemented, and by interviewing key policy and practice stakeholders, patients and patient supporters/voluntary sector.

We will model the resources required to scale the intervention and model cost-utility by modelling potential effects of observed outcomes on long-term quality-of-life and mortality. Timeline (months) Measurement tools 18; intervention development & pilot 26; evaluation 49; complete 54. Dissemination

Our applicants include policymakers from partner countries and together we will disseminate through continental and global clinical and policy networks. We will maintain our systematic reviews to locate our findings in the world literature.