Msaouel, Pavlos

e16535 Background: RMC is a rare and highly aggressive malignancy that predominantly affects young individuals with sickle hemoglobinopathies. Due to its rarity, no validated prognostic models exist to guide clinical decision-making. We aimed to develop and internally validate a prognostic model for patients with RMC using routinely available clinical and laboratory variables. Methods: We analyzed a single-institution cohort of patients with RMC. Candidate variables were identified based on biological plausibility and represented in a directed acyclic graph. Missing data were handled via multiple imputation by chained equations ( m = 50). Variables were ranked using elastic net Cox regression ( α = 0.5, λ = λ min ) with stability selection derived from 100 bootstrap resamples per imputed dataset. Predictors achieving > 60% selection frequency were retained for a nested parsimony analysis. Bootstrap internal validation ( B = 2000) estimated optimism-corrected discrimination and calibration performance, with the calibration slope applied as global shrinkage to penalize final coefficients for overfitting. Clinical utility was evaluated via decision curve analysis (DCA) at 18- and 24-month horizons. Results: Among 180 patients (median age 29; IQR 23–37), 142 deaths occurred with a median follow-up of 12.4 months. The final model included four predictors (Table). The optimism-corrected c-index was 0.667 (optimism = 0.009), and the calibration slope was 0.964, indicating minimal overfitting. Calibration plots showed excellent predicted-observed agreement at 12, 18, 24, and 36 months. DCA showed net benefit across threshold probabilities of 10%–75% at 18 months and 10%–80% at 24 months compared to default strategies. In sensitivity analysis, inclusion of TP53 mutation status improved discrimination ( c -index 0.686) and model fit ( ΔAIC −10.6). An interactive web-based risk calculator was developed to facilitate clinical implementation. Conclusions: This study presents the first internally validated prognostic model for RMC, demonstrating acceptable discrimination and excellent calibration using routinely available variables. By stratifying patients into distinct risk groups, this model may inform treatment intensity—guiding escalation to multi-agent regimens or sequential chemotherapy cycling in high-risk patients, while identifying lower-risk patients who may benefit from de-escalation strategies such as metastasis-directed therapy for oligometastatic disease or consideration of cytoreductive nephrectomy. External validation is warranted. Variable Time Ratio 95% CI p value ECOG performance status 0.64 0.53–0.77 <0.001 Distal (non-retroperitoneal) lymph node metastases 0.69 0.52–0.92 0.011 Neutrophil-to-lymphocyte ratio 0.98 0.94–1.02 0.25 Corrected calcium (mg/dL) 0.77 0.56–1.06 0.10 Sensitivity Analysis Only TP53 Mutation 0.63 0.36-1-10 0.10

PURPOSE We tested the hypothesis that adding metastasis-directed therapy (MDT) to standard-of-care (SOC) systemic therapy improves progression-free survival (PFS) among patients with oligometastatic disease. METHODS EXTEND was a multicenter randomized phase II trial. Patients with 1-5 metastases were randomly assigned to MDT + SOC versus SOC in one of the six baskets (breast, pancreas, kidney, two prostate baskets, and an other basket) with basket-specific stratification and powering. PFS, the primary end point, was prespecified in the per-protocol set within each basket, across all baskets, and across all baskets excluding the prostate baskets. Exploratory end points included circulating tumor DNA (ctDNA) and immune profiling. RESULTS From 2018 through 2023, 521 patients were screened, 350 were randomly assigned, and 334 were analyzed per protocol (MDT + SOC, n = 166; SOC, n = 168). Radiotherapy was used as MDT for 98% of metastases (370/379). Overall, after a median follow-up of 53 months, PFS was improved with MDT + SOC (hazard ratio [HR], 0.54 [95% CI, 0.41 to 0.72], P < .001). Similarly, PFS was improved when excluding the prostate baskets (HR, 0.60 [95% CI, 0.40 to 0.89]). Within each basket, PFS superiority was identified for the pancreas, prostate, and other baskets, whereas the breast and kidney baskets were inconclusive. At enrollment, detectable ctDNA correlated with shorter PFS and survival; by contrast, ctDNA clearance 3 months postenrollment correlated with improved survival. MDT + SOC-induced systemic immune activation was most pronounced among baskets demonstrating PFS superiority. CONCLUSION The phase II EXTEND trial supports the addition of MDT to SOC for oligometastatic disease. Histology-specific efficacy signals were identified for phase III testing. Translational insights suggest the potential for optimizing the definition of oligometastasis using ctDNA and point to systemic immune responses as a possible mechanism of benefit from MDT.

PURPOSE Most oncology trials define superiority according to dichotomized P value thresholds, which are frequently misinterpreted. Posterior probability, however, directly estimates the probability of the hypothesis at hand. Here, we reanalyze a large collection of modern phase III trials and benchmark posterior probability versus the standard trial interpretation based on statistical significance. METHODS Outcomes from 194,129 patients were manually reconstructed from the primary end points of 230 phase III, superiority-design oncology trials. Posterior probabilities of treatment effect were then calculated across multiple priors and several effect sizes of clinical relevance, including minimum clinically important difference (MCID) defined as hazard ratio (HR) < 0.8 per ASCO criteria or HR < 0.64 per European Society of Medical Oncology (ESMO) criteria. RESULTS All trials interpreted as superior using P value thresholds had probabilities >90% for achieving at least marginal benefits (HR < 1). However, only 62% of positive trials (74/120) had >90% probabilities of achieving the ASCO MCID (HR < 0.8), even under an enthusiastic prior, including 70% of trials (57/82) leading to regulatory approval. Only 30% of positive trials (36/120) had >90% probability of achieving the ESMO MCID (HR < 0.64). Conversely, 24% of trials (26/110) interpreted as not superior had >90% probability of achieving marginal benefits (HR < 1), even under a skeptical prior. CONCLUSION Bayesian models, although often in agreement with statistical significance thresholds, add considerable unique interpretative value for a subset of phase III oncology trials. Posterior probability may provide a solution for overcoming the discrepancies between refuting the null hypothesis and detecting clinically relevant effects.

160 Background: To our knowledge, no tools are available to guide care in oligometastatic prostate cancer (omPC). Here, we leveraged individual patient-level data pooled from 8 randomized trials in the X-Met collaboration to construct CEREBRO, a tool for predicting patient-specific responses to various treatment scenarios. Methods: Patients with omPC from the STOMP, ORIOLE, SABR COMET, EXTEND continuous ADT, EXTEND intermittent ADT, ARTO, RADIOSA, and RAVENS trials were included. 6 patients (1%) with missing data were excluded. Treatment scenarios were defined as active surveillance (AS), metastasis-directed therapy (MDT), systemic therapy (ST), or MDT+ST. To account for varying baseline hazards, Weibull models were fit for overall survival (OS); progression-free survival (PFS); and castration-resistance free survival (CRFS) for patients with hormone-sensitive disease. Endpoint definitions were harmonized per X-Met framework. Results: Of 600 patients included (treatment scenarios: AS=50; MDT=153; ST=172; MDT+ST=225), 405 (67%) had hormone-sensitive omPC. With median follow-up of 38 months, median PFS, CRFS, and OS of all patients were 18, 70, and 84 months. In order of relative contribution, inputs for predicting outcomes were: treatment scenario, stage, prostate-specific antigen annotated by ADT status, metachronous vs synchronous presentation, imaging type, number of metastases, hormone sensitivity, and age. The model for each endpoint showed robust fit, calibration, superiority against the null model (per the likelihood ratio test), and risk stratification (Table). Median PFS times for model-defined low-, intermediate-, and high-risk strata were 46 months, 18 months, and 7 months ( p <0.0001). In addition, the PFS and OS models also showed strong discrimination via c index and a large interval of risk probabilities with additive clinical utility per decision-curve analysis (Table). A public webpage will be made available to facilitate prospective trial stratification, patient counseling for patient-specific outcome predictions for each potential treatment scenario, and forecasts comparing outcomes between treatment scenarios. Conclusions: CEREBRO is a high-performance tool, trained on robust prospective data from 8 randomized trials with routinely collected clinical variables, for predicting risk and treatment outcomes in omPC. Given the uncertainties in optimal timing of MDT and combination with ST, this tool has been built to facilitate current decision making. External validation is planned. Model summary. Endpoint C index (95% CI) Calibration Likelihood ratio p Risk strata p Net clinical utility observed between thresholds PFS 0.72 (0.70-0.75) 1.04 <0.0001 <0.0001 0.2-1.0 CRFS 0.63 (0.60-0.70) 1.01 0.02 0.004 0.2-0.5 OS 0.81 (0.76-0.86) 1.01 <0.0001 <0.0001 0.05-1.0

498 Background: Radiotherapy-based metastasis-directed therapy (MDT) has emerged as a viable treatment paradigm for oligometastatic clear cell renal cell carcinoma (ccRCC). However, the optimal integration of MDT with frontline immune checkpoint inhibition (ICI) is unclear, especially in light of the M1 NED subgroup analysis of KEYNOTE-564 suggestive of a larger benefit from adjuvant pembrolizumab. Here, we sought to compare the effects of MDT with or without pembrolizumab on clinical and translational outcomes among patients with oligometastatic ccRCC enrolled on two prospective phase II trials. Methods: We undertook an exploratory cohort study of two prospective, single-arm, investigator-initiated phase II trials. The RAPPORT trial (NCT02855203) assigned 30 patients to radiotherapy-based MDT followed by pembrolizumab 200 mg Q3W for eight cycles (MDT+ICI cohort). The MD Anderson trial (NCT03575611) assigned 121 patients to serial MDT (which was almost exclusively radiotherapy-based) without systemic therapy (MDT cohort). For both trials, eligibility criteria consisted of 1 to 5 ccRCC metastatic lesions amenable to MDT. For the present analysis, the primary endpoint was progression-free survival (PFS), prospectively defined by RECIST v1.1 and analyzed using Cox regression. Peripheral blood flow cytometry obtained at baseline, end of MDT in both cohorts (after 1 cycle of ICI in the MDT+ICI cohort), and after completion of all treatment in both cohorts (3 months in the MDT alone cohort and 12 months in the MDT+ICI cohort) was compared using adjusted linear mixed effect models. Results: A total of 150 patients were included for analysis (MDT+ICI: 30; MDT: 120). Median follow-up time was 34 months (MDT+ICI: 28; MDT: 36). At enrollment, the MDT+ICI cohort had a larger number of metastases (median 3 vs 1). Adjusted for prognostic factors, median PFS was 28 months after MDT+ICI and 17 months after MDT (HR, 0.57; 95% CI: 0.31 to 0.998; P = 0.049). Induction of activated systemic CD8 + T cells (ICOS + ) was observed in both cohorts following MDT; however, this increase was greater in the MDT+ICI cohort. Moreover, there was evidence of decreased systemic CD8 + T cell immunosuppression (CD73 + ) following treatment cessation in the MDT+ICI group. Conclusions: To our knowledge, this is the largest prospective analysis of MDT for ccRCC in the ICI era. The addition of maintenance ICI to MDT may improve clinical outcomes in patients with oligometastatic ccRCC. Greater immunomodulatory signals were observed with MDT+ICI, providing a mechanistic link to the clinical benefits. The ASTROs trial (NCT06004336) randomizing patients with oligometastatic ccRCC to MDT with or without pembrolizumab has been initiated to test the hypotheses generated by the present study. Clinical trial information: NCT02855203 and NCT03575611 .

Abstract Background In randomized clinical trials (RCTs), anticipating control arm outcomes is important for power calculations and enrollment goals. Unexpected overperformance of the control arm can underpower RCTs. The objective of this study was to estimate the prevalence of control arm overperformance in phase 3 oncology RCTs. Methods The authors conducted a meta‐epidemiological study of two‐arm, superiority‐design, phase 3 oncology RCTs. They reviewed articles/publications and protocols for power calculations, justification, and outcomes. Control arm performance was measured as the ratio of observed control arm outcomes relative to pretrial estimates, and overperformance was defined as a 10% improvement. Results In total, 385 RCTs met inclusion criteria. The primary end point was overall survival (OS) in 134 RCTs (35%). Of 311 RCTs (81%) that provided a pretrial estimate for control arm performance, 138 RCTs (44%) cited a justification for the estimate. Greater than expected control arm performance was associated with lower odds of meeting the primary end point (adjusted odds ratio, 0.989; 95% confidence interval, 0.981–0.998; p = 0.015). Of 244 RCTs that were evaluable for control arm performance, 104 (43%) exhibited overperformance. RCTs that used OS as a primary end point were more likely to exhibit control arm overperformance compared with RCTs that used other primary end points (56% vs. 33%; adjusted odds ratio, 2.43; 95% confidence interval, 1.42–4.15; p = .001). Conclusions Control arm overperformance is common in phase 3 oncology RCTs and is associated with trial outcomes, suggesting an effect on study power. Because overperformance appears to be especially prevalent when OS is the primary end point, the effects of postprogression therapies on OS may be underappreciated. Alternative strategies for designing trials should be considered for reliable estimation of treatment effects.

Abstract In phase 3 oncology clinical trials, identifying and understanding potential sources of differential censoring (DC), which describes censoring imbalance between treatment arms, in overall survival (OS) endpoints is vital to reduce bias and misinterpretation of OS benefit. Among 322 trials, 34 (11%) trials exhibited DC overrepresented in the control arm (DCC). Compared to trials without DC or those with DC overrepresented in the experimental arm (DCE), trials with DCC showed higher rates of OS benefit (56% vs. 32%; odds ratio [OR] = 2.26, 95% CI = 1.04 to 4.90; P = .04) and were associated with patient withdrawal (median 8.0% vs. 3.8%; P = .0002), lack of double blinding (15% vs. 48%, OR = 0.19, 95% CI = 0.06 to 0.56; P = .003), and better global quality of life in the experimental arm (32% vs. 13%, OR = 3.01, 95% CI = 1.26 to 7.19; P = .01). OS DCC is a prominent challenge that requires rigorous trial design and comprehensive patient and mortality follow-up to reduce bias in interpreting OS benefit.

ABSTRACT Background Blinding mitigates bias in randomized trials and may be especially crucial for surrogate endpoints, such as progression‐free survival (PFS). Here, we characterize utilization of and factors associated with blinding in Phase III oncology trials with PFS primary endpoints. Methods Two‐arm, superiority‐design trials investigating systemic therapy were identified in May 2024 from ClinicalTrials.gov with no date limitation. Trials were required to have a PFS primary endpoint. The study outcomes were the presence of double‐blind designs and blinded independent central review (BICR) for the primary endpoint. Ninety‐five percent credible intervals for binary outcomes were estimated from beta distributions, and multivariable logistic regressions explored associations with trial‐level features. Results After screening, 237 trials were included, enrolling 127,518 patients. A double‐blind design was used in 105 trials (44%, 95% CrI 38%–51%). BICR was used in 111 trials (47%, 95% CrI 41%–53%), including 39 double‐blind trials (16%, 95% CrI 12%–22%). Trials with BICR had higher odds of meeting the primary endpoint (OR 1.84; 95% CI 1.06–3.18; p = 0.03). The PFS assessor identity (central vs. local) or blinding status was not reported in 50 trials (26%, 95% CrI 16%–27%). Trials that met prespecified significance criteria for PFS were more likely to report whether PFS assessors were blinded/unblinded and central/local (OR, 3.05; 95% Cl: 1.60–5.81; p = 0.0007). Conclusions Despite the importance of double blinding in combination with BICR for reducing bias, only a few trials blinded physicians, patients, and primary endpoint assessors. This meta‐epidemiological study illuminates the prevalence of potential assessment biases affecting PFS in Phase III oncology and secondarily emphasizes the need for improved methodology reporting.