Troy, Jesse D

PURPOSE Public reporting of health care outcomes can have unintended effects such as inappropriate risk aversion in patient selection. METHODS The center-specific survival analysis annually assigns all hematopoietic cell transplantation (HCT) centers in the United States a +1, −1, or 0 score for observed outcomes that are above, below, or within a center-specific predicted range of outcome. For each index year (2012-2016), centers receiving a −1 score after 0 scores in the preceding 2 years were compared with contemporaneous centers with as-predicted outcomes (0 score). Changes in the patient population characteristics in the 3 years before versus the 3 years after the index years were compared between the newly below-expected centers (NBCs) and the controls. A multivariate model adjusted for baseline patient population characteristics and center volume. RESULTS No differences in patient selection behavior were identified when comparing the NBCs with the controls across eight key patient population characteristics. For the statistically modeled (predicted) 1-year overall survival (OS), reflecting a holistic measure of centers' patient population risk, we observed no statistically significant difference in change (−0.23% [95% CI, −1.4 to 0.9]; P = .70). The observed OS increased in both NBCs and controls by 0.9% and 4.5%, respectively, without statistically significant difference in change. CONCLUSION Centers receiving a −1 score were not observed to deviate significantly from patient selection trends in the HCT field. These findings suggest that public reporting of HCT outcomes in the United States does not result in unintended bias against HCT for high-risk patients.

4558 Background: In the past 7 years, 4 immuno-oncology (IO) based combinations have been approved for mRCC. However, QOL data on these combinations are limited to trials in which collection and reporting was not standardized, which further limits cross trial comparisons. Real-world QOL data with multiple treatment regimens are needed to understand how these regimens are tolerated in practice. Methods: ODYSSEY is a multi-site, prospective observational study of 500 US pts with mRCC. Pts must have mRCC (any histology), no prior ST, and follow up at a PCORnet study site. Exclusion criteria include treatment for cancer except mRCC. The primary objective is to determine patterns of change in QOL and symptom burden of pts with mRCC. Minimally important differences (MID) are 3 points for FKSI-19 total score, 1 point for the FKSI-Disease Related Symptoms (DRS) subscale and 7 points for FACT-G. Results: As of 1/6/25, 392 pts were enrolled of whom 299 were managed with ST. Of pts on ST, 114 were treated with IO-IO, 108 with IO-TKI, 33 with IO alone, 27 with Other, and 18 with TKI alone. Median follow up for all pts is 8.8 months (IQR 2.9, 16.2). IO-IO pts are median age 64 yrs, 81% male, 84% white, 56% prior nephrectomy, 84% clear cell; IO-TKI pts median age 66 yrs, 76% male, 92% white, 43% prior nephrectomy, 66% clear cell; IMDC risk profiles are similar. IO-IO pts are more likely to be KPS 100; whereas, IO-TKI pts have a higher median number of metastatic sites and are more likely to have bone or liver metastasis. With median follow-up of 6.0 (IQR 1.8, 14.9) and 8.8 months (4.5, 17.8) in the IO-IO and IO-TKI cohorts, 17 (15%) and 21 (19%) pts had died with a median time to death of 5.4 (2.5, 6.4) and 5.7 months (4.4, 12.8), respectively. 20 (18%) and 16 (15%) pts on IO-IO and IO-TKI had discontinued therapy at a median of 3.0 (IQR 2.0, 4.0) and 6.4 months (2.4, 13.0), respectively. Rates of discontinuation for disease progression and toxicity are similar. Baseline PROs for pts on ST are shown in the Table (higher score indicates better QOL), with RCT data for reference (NA, not assessed). Conclusions: In our prospective multi-center ODYSSEY study, we demonstrate that real world pts treated with contemporary ST have worse baseline QOL than those enrolled on pivotal RCTs. One-third of IO-IO and IO-TKI pts died or discontinued therapy within 6 months of initiation. Our data on real world vs RCT differences in baseline QOL may partially explain the limitations of current IO combination regimens in practice and support development of alternative treatment approaches. Instrument, Mean (SD) ODYSSEYIO-IO(N=114) CheckMate214(N=425) ODYSSEYIO-TKI(N=108) KEYNOTE426(N=402) CheckMate9ER(N=323) CLEAR(N=351) FKSI-19 total 56.0 (12.5) 60.1 (9.8) 53.8 (11.8) NA 58.7 (10.6) NA FKSI-DRS 27.5 (6.3) 30.7 (4.5) 27.0 (5.8) 32 (4.2) 30.2 (5.2) 31.3 (4.4) FACT-G 82.4 (16.7) 82.6 (15.0) 78.5 (16.0) NA NA NA

4553 Background: AS is a recognized strategy in select pts with mRCC to maximize QOL and delay potential toxicity of systemic therapy (ST); however, only 2 prospective studies of AS in mRCC have been published: only 1 with patient-reported outcomes (PRO) and none in the IO-TKI era. Methods: ODYSSEY is a prospective observational study of 500 US pts with mRCC. Eligible pts must have mRCC (any histology), no prior ST, age ≥19. Pts were excluded if treated for non-mRCC cancers or if not followed at a PCORnet study site. Pts completed QOL surveys at baseline, by phone every 3 months for 2 years and then every 6 months until end of follow up. The primary objective is to determine patterns of change in QOL and symptom burden of pts with mRCC. Minimally important differences (MID) are 3 points for FKSI-19 total score, 1 point for the FKSI-Disease Related Symptoms (DRS) subscale and 7 points for FACT-G. Here we report baseline pt characteristics in AS pts compared to ST pts, and baseline QOL differences between these cohorts. Results: As of 1/6/25, 392 pts were enrolled of whom 299 were managed with ST, and 93 pts deferred ST; of these, 53 pts (57%) were classified as AS. Pts on AS are median age 68 yrs, 66% male, 94% white, 81% clear cell, 50% favorable risk, 44% intermediate risk. Compared with ST pts, AS pts were more likely to have undergone nephrectomy (91% vs 53%), favorable risk profile (50% vs 15%), pancreatic metastasis (15% vs 5%), and longer time since RCC diagnosis (median 58 vs 3.3 months); and less likely to have bone, brain, or liver metastasis. After median 8.8 months follow-up (IQR 2.9, 16.2), 2 pts (4%) on AS had died compared with 45 pts (15%) on ST. One pt (2%) on AS started first-line therapy and 45 pts (15%) discontinued ST. Mean baseline QOL (FKSI-19 total, DRS and FACT-G) for AS and ST ODYSSEY pts is shown in the Table (higher score indicates better QOL), with RCT data for reference (NA, not assessed). ODYSSEY pts on AS had higher QOL for all measures compared with ODYSSEY pts on ST. FSKI-DRS was the same or lower for pts on AS compared to the pivotal trials, while ODYSSEY pts on ST had both lower FKSI-19 total and DRS. Conclusions: In our large prospective cohort from ODYSSEY, pts on AS had higher median QOL scores than pts on ST, but similar to those included in RCTs. These results suggest that some RCT pts could have benefitted from AS. Further follow up is needed to determine long term outcomes in pts on AS and how they respond to deferred ST. Clinical trial information: NCT04919122 . Instrument, Mean (SD) ODYSSEY AS (N=53) ODYSSEY ST (N=299) ODYSSEY Difference, AS vs ST (95% CI) CheckMate 214 (N=425) KEYNOTE 426 (N=402) CheckMate 9ER (N=323) CLEAR (N=351) FKSI-19 total 63.4 (9.2) 56.3 (12.5) 7.0(4.0, 10.1) 60.1 (9.8) NA 58.7 (10.6) NA FKSI-DRS 30.8 (4.2) 27.9 (6.0) 2.9(1.5, 4.7) 30.7 (4.5) 32 (4.2) 30.2 (5.2) 31.3 (4.4) FACT-G 87.9 (14.0) 82.4 (16.7) 5.6(1.1, 10.0) 82.6 (15.0) NA NA NA

Collaborative quantitative scientists, including biostatisticians, epidemiologists, bioinformaticists, and data‐related professionals, play vital roles in research, from study design to data analysis and dissemination. It is imperative that academic health care centers (AHCs) establish an environment that provides opportunities for the quantitative scientists who are hired as staff to develop and advance their careers. With the rapid growth of clinical and translational research, AHCs are charged with establishing organizational methods, training tools, best practices, and guidelines to accelerate and support hiring, training, and retaining this staff workforce. This paper describes three essential elements for building and maintaining a successful unit of collaborative staff quantitative scientists in academic health care centers: (1) organizational infrastructure and management, (2) recruitment, and (3) career development and retention. Specific strategies are provided as examples of how AHCs can excel in these areas.

385 Background: Tyrosine kinase inhibitors (TKI) and immuno-oncology (IO) agents alone or in combination have revolutionized the landscape of management for untreated metastatic renal cell carcinoma (mRCC). Baseline quality of life (QOL) outside of interventional clinical trials and rationale for management decisions in mRCC are poorly understood. Methods: In this prospective observational study of 800 mRCC pts in the US, pts must: have a diagnosis of mRCC (any histology) with no prior systemic therapy (ST) for mRCC; be age ≥19 at informed consent; be able to comply with completion of PROs. Exclusion criteria include being treated for active malignancy other than mRCC or not intending to follow up at a study site within PCORnet. Pts undergo consent and baseline assessments by the study site team, with subsequent follow up by the central coordinating center. The primary objective is to determine distinct patterns of change in QOL and symptom burden of mRCC pts. A key secondary objective is to identify patterns of clinical management in the real world setting of mRCC across treatment regimens. Minimally important differences are defined as 3- and 7-points for FKSI-19 and FACT-G respectively. ClinicalTrials.gov ID: NCT04919122. Results: As of 9/1/2023, 173 pts have been enrolled (126 ST, 47 no ST [NST]): 75% male, 87% white, 73% clear cell, 52% intermediate risk and 47% poor risk. 47% had radical nephrectomy and 22% another solid tumor. ST pts as compared to NST pts were more likely to be poor risk (52% vs 16%); but differences in baseline pain were not significant. Of ST pts, 44 were treated with IO-IO (ipilimumab + nivolumab), 50 with IO-TKI (cabozantinib + nivolumab 38%, axitinib + pembrolizumab 38%, lenvatinib + pembrolizumab 24%) and 32 other (IO alone 34%, TKI alone 31%, investigational drug 25%). Reasons for NST included active surveillance (AS, 50%), other (21%), local therapy (13%). Mean differences between ST and NST for baseline FKSI-19 and FACT-G were 5.7 (95% CI: 1.2 – 10.2) and 3.3 (-2.6 – 9.3). There were no differences in pain or PROs between IO-IO and IO-TKI pts. Mean differences in FKSI-19 and FACT-G between AS vs IO-IO were 10.6 (4.8 – 16.4) and 8.6 (1.1 – 16.0); and vs IO-TKI were 11.0 (4.9 – 17.0) and 10.3 (3.5 – 17.1). On physician surveys, primary reasons for treatment selection were (in order of % selected): complete response (CR), prolonged survival (OS), prognostic factors (Px), treatment-free interval for IO-IO; versus delaying progression (PFS), OS, CR, Px for IO-TKI. Conclusions: Our data suggest differences in baseline QoL in pts treated with ST vs NST, as well as AS vs IO-IO or IO-TKI, in the real world. Reasons for selection of ST regimen differed among combination regimen classes. Completion of ODYSSEY will clarify baseline and longitudinal differences in pain and PROs among management strategies and give novel insights into the rationale for real world management of untreated pts with mRCC. Clinical trial information: NCT04919122 .

Introduction Public reporting of outcomes drives healthcare improvement in many fields, including hematopoietic cell transplantation (HCT), although with possible unintended consequences. The Center for International Blood & Marrow Transplant Research (CIBMTR) publishes an annual Center-Specific Survival Analysis (CSA), which compares HCT centers' observed 1-year overall survival (OS) with their statistically modeled expected 1-year OS, with 95% confidence intervals (CI). Centers with OS within their 95% CI receive a 0 score, indicating as expected outcomes. Those with OS below / above their 95% CI receive a -1 / +1 score, indicating below / above expected OS, respectively. After a -1 report, centers may change their patient selection criteria, causing unintentional systematic exclusion of patient populations who could benefit from HCT. We analyzed how the CSA report influences patient selection practices among centers receiving a -1 score. Methods Centers receiving a -1 report between 2012 and 2016 that had ‘as expected’ survival in the preceding 2 years were classified as newly below expected OS centers (NBCs). The year of their -1 report was used as the index year. Centers with ‘as expected’ OS in the 3 years before and after each index year were identified as control centers, reflecting expected evolution of patient selection in the HCT field. The patient population variables analyzed are shown in Table 1. The difference in patient population characteristics in the 3 years before vs the 3 years after the index years defined the change in patient selection behavior at the NBCs and the controls. A multivariate model adjusting for baseline patient population characteristics and center size was used to compare the change in patient population from before and after the index year in the NBCs and that of the controls. The difference in differences (ΔinΔ) were calculated as ΔNBC - ΔControl. A significance threshold of p<0.01 was used to account for multiple testing. Results After adjusting for overall trends, center size, and baseline patient population characteristics, no differences in patient selection behavior meeting the pre-specified threshold for statistical significance were identified when comparing the NBCs (n=24 centers) with the controls (n=195 centers). In the 3 years following the index years, 4,150 and 25,013 patients were transplanted at NBCs and controls, respectively. The proportion of patients receiving reduced intensity or non-myeloablative conditioning regimens decreased 4.1% in NBCs and increased 5.0% in controls, for a net difference of -9.1% (95% CI: -16.7% to -1.6%, p=0.02). All other patient characteristic proportions changed in the same direction at NBCs and controls, albeit to varying degrees (Table 1). In some high-risk characteristics, (e.g. HCT-CI > 3), a greater increase was seen at NBCs vs controls (ΔinΔ 2.1% 95% CI: -2.8% to 6.9%, p=0.40). In others, (e.g. age 60+ years), a greater increase was seen at controls vs NBCs (ΔinΔ -2.6% 95% CI: -5.9% to 0.7%, p=0.12). To capture a holistic measure of centers' patient population risk, the predicted 1-year survival was compared in the NBCs vs controls using the logistic regression model generated for each year's CSA. The predicted OS increased by 3.08% and 3.30% in the NBCs and controls respectively, with no statistically significant difference (-0.23%, 95% CI: -1.4% to 0.9%, p=0.70, Figure 1). The observed overall survival (adjusted for predicted 1 year OS) also increased in both BECs and controls by 0.9% and 4.5% respectively, without statistically significant difference (-3.6%, 95% CI: -6.7% to -0.7%, p=0.02). Discussion For centers receiving a -1 report, no statistically significant changes were seen in patient population characteristics in the following 3 years when compared to centers with OS was as expected. There was variability in the changes in high-risk patient characteristics at the NBCs relative to the controls, and in some cases more patients with high-risk characteristics were selected at these centers compared to those at controls. The change in predicted overall survival at 1 year, a summary indicator of survival risk, was similar between BECs and control centers. Although the number of patients in centers with below expected OS was small, these findings suggest the public reporting of outcomes in HCT in the US does not unintentionally affect access to HCT for high-risk patients at NBCs.