Health-financing reforms in southeast Asia: challenges in achieving universal coverage.

In this sixth paper of the Series, we review health-financing reforms in seven countries in southeast Asia that have sought to reduce dependence on out-of-pocket payments, increase pooled health finance, and expand service use as steps towards universal coverage. Laos and Cambodia, both resource-poor countries, have mostly relied on donor-supported health equity funds to reach the poor, and reliable funding and appropriate identification of the eligible poor are two major challenges for nationwide expansion. For Thailand, the Philippines, Indonesia, and Vietnam, social health insurance financed by payroll tax is commonly used for formal sector employees (excluding Malaysia), with varying outcomes in terms of financial protection. Alternative payment methods have different implications for provider behaviour and financial protection. Two alternative approaches for financial protection of the non-poor outside the formal sector have emerged-contributory arrangements and tax-financed schemes-with different abilities to achieve high population coverage rapidly. Fiscal space and mobilisation of payroll contributions are both important in accelerating financial protection. Expanding coverage of good-quality services and ensuring adequate human resources are also important to achieve universal coverage. As health-financing reform is complex, institutional capacity to generate evidence and inform policy is essential and should be strengthened

Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization

Despite their promise, circulating tumor DNA (ctDNA)-based assays for multi-cancer early detection face challenges in test performance, due mostly to the limited abundance of ctDNA and its inherent variability. To address these challenges, published assays to date demanded a very high-depth sequencing, resulting in an elevated price of test. Herein, we developed a multimodal assay called SPOT-MAS (screening for the presence of tumor by methylation and size) to simultaneously profile methylomics, fragmentomics, copy number, and end motifs in a single workflow using targeted and shallow genome-wide sequencing (~0.55×) of cell-free DNA. We applied SPOT-MAS to 738 non-metastatic patients with breast, colorectal, gastric, lung, and liver cancer, and 1550 healthy controls. We then employed machine learning to extract multiple cancer and tissue-specific signatures for detecting and locating cancer. SPOT-MAS successfully detected the five cancer types with a sensitivity of 72.4% at 97.0% specificity. The sensitivities for detecting early-stage cancers were 73.9% and 62.3% for stages I and II, respectively, increasing to 88.3% for non-metastatic stage IIIA. For tumor-of-origin, our assay achieved an accuracy of 0.7. Our study demonstrates comparable performance to other ctDNA-based assays while requiring significantly lower sequencing depth, making it economically feasible for population-wide screening