Delays in cancer diagnosis for patients with non-specific symptoms (NSSs) lead to poorer outcomes. Rapid Diagnostic Clinics (RDCs) expedite care, but most NSS patients do not have cancer, highlighting the need for better risk stratification. This study aimed to develop biomarker-based clinical prediction scores to differentiate high-risk and low-risk NSS patients, enabling more targeted diagnostics.

Retrospective and prospective cohort study.

Secondary care RDC in London.

Adult patients attending an RDC between December 2016 and September 2023 were included. External validation used data from another RDC.

The primary outcome was a cancer diagnosis. Biomarker-based risk scores were developed using Latent Class Analysis (LCA) and Least Absolute Shrinkage and Selection Operator (LASSO). Model performance was assessed using logistic regression, receiver operating characteristic curves (AUROC) and decision curve analysis.

Among 5821 RDC patients, LCA identified high white cell count, low haemoglobin, low albumin, high serum lambda light chain, high neutrophil-to-lymphocyte ratio, high serum kappa light chain (SKLC), high erythrocyte sedimentation rate (ESR), high C-reactive protein (CRP) and high neutrophils as cancer risk markers. LASSO selected high platelets, ESR, CRP, SKLC, alkaline phosphatase and lactate dehydrogenase. Each one-point increase in score predicted higher odds of cancer (LCA: AOR 1.19, 95% CI 1.16 to 1.23; LASSO: AOR 1.29, 95% CI 1.25 to 1.34). Scores ≥2 predicted significantly higher cancer odds (LCA: AOR 3.79, 95% CI 2.91 to 4.95; LASSO: AOR 3.44, 95% CI 2.66 to 4.44). Discrimination was good (AUROC: LCA 0.74; LASSO 0.73). External validation in 573 patients confirmed predicted increases in cancer risk per one-point LASSO score rise (AOR 1.28, 95% CI 1.15 to 1.42), with a borderline increase for LCA (AOR 1.16, 95% CI 1.06 to 1.27).

Biomarker-based scores effectively identified NSS patients at higher cancer risk. LCA captured a broader biomarker range, offering higher sensitivity, while LASSO achieved higher specificity with fewer markers. These scores may also help detect severe benign conditions, improving RDC triage. Further validation is needed before broader clinical implementation.

Global health initiatives (GHIs) have played a significant role in expanding access to healthcare worldwide, particularly in maternal health. For instance, many regions in sub-Saharan Africa have seen a notable rise in the availability of skilled birth attendants. However, despite these gains in access, maternal mortality rates in low-income and middle-income countries within the African Region remain alarmingly high. Although GHIs have invested heavily in maternal health, there is limited evidence regarding their effects on the quality of maternal healthcare, an essential factor influencing maternal outcomes. The WHO has developed quality standards for maternal and newborn care to guide all stakeholders in delivery of care for mothers. These include evidence-based practices for managing childbirth complications, efficient health information systems, appropriate referral mechanisms, respectful and dignified treatment of patients, emotional support, well-trained and motivated healthcare providers and a conducive physical environment. These standards serve as a framework for improving and assessing the quality of maternal and newborn services. Despite significant funding and technical guidance aimed at enhancing care quality, there remains a lack of robust data on how GHIs have influenced the quality of maternal health services. To address this evidence gap, we conducted a scoping review to gather and analyse existing evidence on the effects of GHIs on maternal care quality in Sub-Saharan Africa. This report presents the findings from that review.

This study followed the enhanced six-stage framework for scoping reviews developed by Arksey and O’Malley. We included both peer-reviewed and grey literature such as reports and policy documents that addressed the impact of GHIs on maternal health services in sub-Saharan Africa between 2010 and 2024. Sources in all languages were considered. A defined set of inclusion and exclusion criteria guided the screening process. The selected studies underwent qualitative synthesis and descriptive analysis and were visually represented where appropriate. This review is reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines.

The search yielded only five quantitative studies, depicting the limited evidence on this critical subject. The studies showed that GHIs had varied effects on quality of care for mothers. These effects included improved readiness of facilities to provide care, improved prenatal-postnatal processes, increased provider knowledge, active management of labour and a decrease in mortality rates in some instances such as Uganda and Zambia. However, there was limited or no improvement in clinical practices, patient experiences and satisfaction with care. Additionally, the studies did not focus on the multidimensional aspects of quality of care as guided by WHO’s comprehensive standards for quality of maternal health services, highlighting a major gap identified throughout this review.

While the limited studies available showed some improvements in specific care quality indicators, there remain significant gaps in the knowledge around how GHIs affect care quality comprehensively. Additionally, the identified studies highlighted significant challenges as a key gap to achieving the intended outcomes and sustaining the gains made during programme implementation. To have a more in-depth understanding of GHIs and their impact on quality of care, it is important to align programme implementation and assessments with comprehensive frameworks such as WHO’s multidimensional quality model. Further, there is a need to adopt iterative, context-sensitive interventions that provide a comprehensive approach to quality of care. The information gathered will be used to inform subsequent studies on the effects of GHIs on quality of care of maternal health services in Uganda and contribute to the development of maternal healthcare policies.