{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T17:57:43Z","timestamp":1791223063402,"version":"4.1.0"},"reference-count":22,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Merck Sharp & Dohme LLC"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Accurate tumor growth rate estimation is vital for linking disease progression to patient characteristics and outcomes, especially in rare diseases where limited data increase bias risk. We evaluated 2 potential sources of bias in linear growth rate (LGR) estimation using data from a prior natural history (NH) study of von Hippel\u2013Lindau (VHL) renal cell carcinoma (RCC), a rare hereditary disorder. A quantitative bias analysis assessed selection bias from differential follow-up, while a Bayesian analysis (BA) examined shrinkage bias from a frequentist linear mixed-effects approach. In the NH cohort (244 patients; 601 target tumors), the original median tumor-level LGR was 1.6\u00a0mm\/year. Quantitative bias analysis produced a bias-corrected LGR of 1.7\u00a0mm\/year, suggesting minimal impact of selection bias. Bayesian modeling produced an LGR estimate of 3.93\u00a0mm\/year, aligning more closely with external reports and suggesting that surgically removed tumors had substantially higher growth rates than the mixed cohort implied by frequentist methods. Quantitative bias analysis showed limited bias from differential follow-up, while BA provided a complementary estimate that was less influenced by shrinkage bias inherent to mixed-effects modeling. These findings underscore the importance of appropriate study design and method selection to diagnose and adjust for biases when characterizing tumor growth in VHL RCC.<\/jats:p>","DOI":"10.1093\/aje\/kwag225","type":"journal-article","created":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T08:12:06Z","timestamp":1790842326000},"source":"Crossref","is-referenced-by-count":0,"title":["Evaluating potential sources of bias in linear growth rate analysis of renal tumors: case study in Von Hippel\u2013Lindau disease"],"prefix":"10.1093","author":[{"given":"Cathy Anne","family":"Pinto","sequence":"first","affiliation":[{"name":"Merck & Co., Inc. , Rahway, NJ ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ghada","family":"Abu-Sheasha","sequence":"additional","affiliation":[{"name":"Real World Evidence Solutions, IQVIA , Falls Church, VA ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Miriam J","family":"Haviland","sequence":"additional","affiliation":[{"name":"Real World Evidence Solutions, IQVIA , Falls Church, VA ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Neil","family":"Murphy","sequence":"additional","affiliation":[{"name":"MSD (UK) Limited , London ,","place":["UK"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Steven S","family":"Senglaub","sequence":"additional","affiliation":[{"name":"Merck & Co., Inc. , Rahway, NJ ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rafia","family":"Bosan","sequence":"additional","affiliation":[{"name":"Real World Evidence Solutions, IQVIA , Falls Church, VA ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Caroline G","family":"Tai","sequence":"additional","affiliation":[{"name":"Real World Evidence Solutions, IQVIA , Falls Church, VA ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Florence","family":"Mercier","sequence":"additional","affiliation":[{"name":"Real World Evidence Solutions, IQVIA , Falls Church, VA ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"W Marston","family":"Linehan","sequence":"additional","affiliation":[{"name":"Urologic Oncology Branch, Urologic Oncology Branch, National Cancer Institute , Bethesda, MD ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,10,1]]},"reference":[{"issue":"9374","key":"2026100513321167600_ref1","doi-asserted-by":"publisher","first-page":"2059","DOI":"10.1016\/S0140-6736(03)13643-4","article-title":"von Hippel-Lindau disease","volume":"361","author":"Lonser","year":"2003","journal-title":"Lancet"},{"issue":"1","key":"2026100513321167600_ref2","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1136\/jmedgenet-2016-104058","article-title":"Survival and causes of death in patients with von Hippel-Lindau disease","volume":"54","author":"Binderup","year":"2017","journal-title":"J Med Genet"},{"issue":"5","key":"2026100513321167600_ref3","doi-asserted-by":"publisher","first-page":"466","DOI":"10.1097\/MOU.0000000000000094","article-title":"Nephron-sparing surgery for multifocal and hereditary renal tumors","volume":"24","author":"Metwalli","year":"2014","journal-title":"Curr Opin Urol"},{"key":"2026100513321167600_ref4","author":"US-FDA"},{"issue":"1","key":"2026100513321167600_ref5","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1016\/j.eururo.2025.03.002","article-title":"Longitudinal evaluation of clear-cell renal cell carcinoma in von Hippel-Lindau disease","volume":"88","author":"Linehan","year":"2025","journal-title":"Eur Urol"},{"issue":"3","key":"2026100513321167600_ref6","doi-asserted-by":"publisher","first-page":"435","DOI":"10.1016\/j.urology.2007.04.040","article-title":"Local recurrence after nephron-sparing surgery in von Hippel-Lindau disease","volume":"70","author":"Ploussard","year":"2007","journal-title":"Urology."},{"issue":"2","key":"2026100513321167600_ref7","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1007\/s10689-011-9503-5","article-title":"Active surveillance of renal masses in von Hippel-Lindau disease: growth rates and clinical outcome over a median follow-up period of 56 months","volume":"11","author":"Zhang","year":"2012","journal-title":"Fam Cancer"},{"issue":"1","key":"2026100513321167600_ref8","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1159\/000333348","article-title":"Growth kinetics in von Hippel-Lindau-associated renal cell carcinoma","volume":"88","author":"Jilg","year":"2012","journal-title":"Urol Int"},{"issue":"1","key":"2026100513321167600_ref9","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1186\/s13023-019-1206-2","article-title":"Growth characteristics and therapeutic decision markers in von Hippel-Lindau disease patients with renal cell carcinoma","volume":"14","author":"Schuhmacher","year":"2019","journal-title":"Orphanet J Rare Dis"},{"issue":"6","key":"2026100513321167600_ref10","doi-asserted-by":"publisher","first-page":"380","DOI":"10.1136\/jmedgenet-2018-105567","article-title":"Natural history of renal tumours in von Hippel-Lindau disease: a large retrospective study of Chinese patients","volume":"56","author":"Peng","year":"2019","journal-title":"J Med Genet"},{"issue":"2","key":"2026100513321167600_ref11","doi-asserted-by":"publisher","first-page":"542","DOI":"10.1007\/s00261-023-04087-6","article-title":"The kidney imaging surveillance scoring system (KISSS): using qualitative MRI features to predict growth rate of renal tumors in patients with von-Hippel Lindau (VHL) syndrome","volume":"49","author":"Gopal","year":"2024","journal-title":"Abdom Radiol (NY)"},{"issue":"11","key":"2026100513321167600_ref12","doi-asserted-by":"publisher","first-page":"1146","DOI":"10.1200\/JCO.19.02263","article-title":"Growth rates of genetically defined renal tumors: implications for active surveillance and intervention","volume":"38","author":"Ball","year":"2020","journal-title":"J Clin Oncol"},{"key":"2026100513321167600_ref13","volume-title":"Applying Quantitative Bias Analysis to Epidemiologic Data","author":"Fox","year":"2022"},{"issue":"6","key":"2026100513321167600_ref14","doi-asserted-by":"publisher","first-page":"1969","DOI":"10.1093\/ije\/dyu149","article-title":"Good practices for quantitative bias analysis","volume":"43","author":"Lash","year":"2014","journal-title":"Int J Epidemiol"},{"issue":"7","key":"2026100513321167600_ref15","doi-asserted-by":"publisher","first-page":"623","DOI":"10.1007\/s40264-020-00944-1","article-title":"A framework for methodological choice and evidence assessment for studies using external comparators from real-world data","volume":"43","author":"Gray","year":"2020","journal-title":"Drug Saf"},{"issue":"7","key":"2026100513321167600_ref16","doi-asserted-by":"publisher","first-page":"1227","DOI":"10.2105\/AJPH.2016.303199","article-title":"Quantitative bias analysis in regulatory settings","volume":"106","author":"Lash","year":"2016","journal-title":"Am J Public Health"},{"key":"2026100513321167600_ref17","doi-asserted-by":"crossref","DOI":"10.1201\/b16018","volume-title":"Bayesian Data Analysis","author":"Gelman","year":"2013","edition":"3rd"},{"issue":"1","key":"2026100513321167600_ref18","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1093\/epirev\/mxab012","article-title":"Monte Carlo simulation approaches for quantitative bias analysis: a tutorial","volume":"43","author":"Banack","year":"2021","journal-title":"Epidemiol Rev"},{"issue":"2","key":"2026100513321167600_ref19","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1111\/rssa.12378","article-title":"Visualization in Bayesian workflow","volume":"182","author":"Gabry","year":"2019","journal-title":"J R Stat Soc A Stat Soc"},{"key":"2026100513321167600_ref20","volume-title":"Monte Carlo Statistical Methods","author":"Robert","year":"2013","edition":"2nd"},{"issue":"1","key":"2026100513321167600_ref21","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1093\/biomet\/85.1.1","article-title":"Model choice: a minimum posterior predictive loss approach","volume":"85","author":"Gelfand","year":"1998","journal-title":"Biometrika."},{"issue":"5","key":"2026100513321167600_ref22","doi-asserted-by":"publisher","first-page":"1413","DOI":"10.1007\/s11222-016-9696-4","article-title":"Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC","volume":"27","author":"Vehtari","year":"2017","journal-title":"Stat Comput"}],"container-title":["American Journal of Epidemiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/aje\/advance-article-pdf\/doi\/10.1093\/aje\/kwag225\/71547728\/kwag225.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/aje\/advance-article-pdf\/doi\/10.1093\/aje\/kwag225\/71547728\/kwag225.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T17:32:20Z","timestamp":1791221540000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/aje\/advance-article\/doi\/10.1093\/aje\/kwag225\/8857673"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10,1]]},"references-count":22,"URL":"https:\/\/doi.org\/10.1093\/aje\/kwag225","relation":{},"ISSN":["0002-9262","1476-6256"],"issn-type":[{"value":"0002-9262","type":"print"},{"value":"1476-6256","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,1]]},"article-number":"kwag225"}}