This manuscript examines the synergistic potential of prospective real-world/time data/evidence (RWTD/E) and randomized controlled trials (RCTs) to enrich healthcare research and operational insights, with a particular focus on its impact within the sarcoma field. Through exploring RWTD/E’s capability to provide real-world/time, granular patient data, it offers an enriched perspective on healthcare outcomes and delivery, notably in the complex arena of sarcoma care. Highlighting the complementarity between RWTD/E’s expansive real-world/time scope and the structured environment of RCTs, this paper showcases their combined strength, which can help to foster advancements in personalized medicine and population health management, exemplified through the lens of sarcoma treatment. The manuscript further outlines methodological innovations such as target trial emulation and their significance in enhancing the precision and applicability of RWTD/E, underscoring the transformative potential of these advancements in sarcoma care and beyond. By advocating for the strategic incorporation of prospective RWTD/E into healthcare frameworks, it aims to create an evidence-driven ecosystem that significantly improves patient outcomes and healthcare efficiency, with sarcoma care serving as a pivotal domain for these developments.

The central vein sign (CVS) is a supportive imaging biomarker for multiple sclerosis (MS), but its manual assessment on susceptibility-weighted imaging with phase enhancement (SWIp) is time-consuming and reader-dependent. Existing automated methods rely on multi-contrast volumetric data and prerequisite lesion masks. We study a deliberately different formulation: a structured end-to-end pipeline operating on a single axial SWIp sequence with sparse slice-wise annotations and no prerequisite volumetric mask, combining anatomical tiling, tiled lesion detection, cross-slice reconstruction of lesion identity, and two complementary branches that independently assess the same lesion crops—direct CVS classification (Pathway A) and vein-presence gating, vein segmentation, and geometric centrality (Pathway B). A cohort of 64 clinical studies annotated by four readers was merged into a consolidated reference. The main contribution is an explicit decomposition of where such a pipeline fails. On an eight-study evaluation, the pipeline recovered 78 of 111 reference lesions (70.3%); lesion-level F1 was 0.667 for Pathway A and 0.706 for Pathway B, rising to 0.785 and 0.818 when restricted to detected lesions, and a paired test found no significant difference between the pathways ($p=1.00$). Detection is therefore the binding constraint, and a threshold sweep shows the associated overcounting of CVS-positive lesions is not separable from it by detector confidence alone. All operating thresholds were selected on these same eight studies, which were acquired on a single scanner, so the figures are single-centre development-set estimates rather than measures of clinical performance and are likely optimistic. Larger-cohort, acquisition-diverse independent evaluation is required before clinical use.

Background: Estimating the effect of preoperative radiotherapy in grade 3 (G3) soft tissue sarcoma (STS) is difficult because treatment reflects clinical risk. We estimated whether local recurrence risk among treated patients would differ under surgery alone. Methods: We retrospectively analyzed a multicentre registry of 151 surgically treated G3 patients without chemotherapy; 99 received preoperative radiotherapy and 52 underwent surgery alone. Propensity score weighting targeted the average treatment effect among treated patients (ATT). The primary weighted interventional Bayesian network (BN) adjusted for age, metastasis, tumor size, depth, body location, and whoops surgery. Logistic regression and BN conditioning and intervention were reference analyses. Differential follow-up was assessed using a weighted Aalen–Johansen analysis. Results: Local recurrence occurred in 31 patients (20.5%). Weighting reduced the maximum absolute standardized mean difference from 0.866 to 0.139. Median bootstrap ATT estimates were $+3.3$ percentage points for conventional logistic regression, $+5.2$ for weighted logistic regression, and $+1.37$ for the weighted interventional BN. At 1 year, the weighted Aalen–Johansen risk difference was $+0.83$ percentage points, with a wide 95% confidence interval spanning benefit and harm. Conclusions: The weighted interventional BN produced a near-null estimate, but modest benefit or harm remained plausible. Treatment effect estimates were sensitive to the assumed causal structure, limiting definitive conclusions about radiotherapy benefit. Given the modest sample, limited treatment overlap, differential follow-up, and residual confounding, causal interpretation should remain cautious. These findings do not support changing established indications for preoperative radiotherapy, but this framework provides a transparent approach to evaluating treatment strategies in rare cancers.