Childhood cancer survival rates are not equal for all, with disparities existing both between and within low- and middle-income countries and high-income countries, particularly among ethnic minorities and children with migrant backgrounds. Factors such as cultural misunderstandings, language barriers and limited support networks can lead to delays in diagnosis and treatment challenges, which can result in poor health outcomes. Social determinants of health (SDoH), such as housing insecurity and poverty, may worsen these disparities. This protocol outlines a systematic review to examine childhood cancer survival in children with migrant backgrounds compared with non-migrants and to explore the SDoH associated with these survival outcomes.

We will search MEDLINE (PubMed), Scopus, Web of Science, and Embase for relevant studies, with secondary searches of grey literature. Two reviewers will screen for observational studies, including longitudinal cohort, case–control, cross-sectional and registry-based studies, that report childhood cancer survival outcomes (eg, survival rates, HRs) for both migrant and non-migrant populations. A narrative synthesis will explore SDoH and their association with survival outcomes. If data allow, we will perform random-effects meta-analyses to estimate pooled survival outcomes. Subgroup analyses will examine factors such as geographic region, migration status and type of cancer.

Understanding factors contributing to childhood cancer survival disparities in migrant populations is critical for informing the development of targeted strategies to address them, ensuring all children, regardless of their migration status, have an equitable opportunity for effective care and improved outcomes.

Ethical approval is not required for this study as it is based on previously published data and does not involve primary data collection. We will publish the results in peer-reviewed journals and present at academic conferences.

CRD42024547239.

The importance of conducting qualitative research alongside clinical trials of complex healthcare interventions is well established. There are various ways in which these two methodologies can be combined in mixed-methods research, including integrating data and/or results from the qualitative and quantitative strands during analysis, using techniques such as joint displays. The potential benefits of integration during data analysis include understanding intervention mechanisms, reasons for variation in outcomes, ways of tailoring interventions to individuals and barriers and facilitators to implementation. However, integration during data analysis may rarely be undertaken in practice, and the extent to which integration can provide valuable insights appears to be underappreciated in the field.

In this review, we aim to summarise current methods of integrating qualitative and quantitative raw data and/or results during analysis in clinical trials of complex healthcare interventions, and the yield of these different methods. Our specific research questions focus on (1) which integration techniques are used; (2) whether the results meet the study authors’ aims and/or answer their research questions; (3) the insights obtained and/or meta-inferences generated from these techniques (classified as either global or specific, and as relational, predictive, causal, comparative or elaborative); (4) any relationship between these insights and/or meta-inferences and the integration technique used and (5) the quality of these studies.

We will systematically search MEDLINE, Embase, PsycINFO, CENTRAL, CINAHL, Scopus and Web of Science, and manually search reference lists. We will include studies if they integrate, during data analysis, raw data and/or results from a clinical (randomised, non-randomised or single-arm) trial and an embedded or subsequent associated qualitative study of a complex, non-pharmaceutical healthcare intervention (where the effects on a health outcome were measured). Two independent reviewers will screen titles, abstracts and full texts and perform data extraction. We will develop a descriptive account of the data, including mapping the key characteristics of included studies and narratively reporting our findings in relation to each of our research questions. We will explore how integration was undertaken, what insights were obtained and/or meta-inferences generated, and whether and how these relate to the type of integration technique used.

This study does not require ethical approval. We intend to publish our findings in a peer-reviewed open-access journal and to present our findings at national and/or international conferences.

This protocol was registered with Open Science Framework on 22 October 2025 (ref osf.io/yxtb9).