OBJECTIVES: To study the variability of assessment instruments (symptom questionnaires and flow rate recordings) in healthy volunteers during repeat administration in short intervals. To study the effect of inclusion criteria-based censoring of patients during screening for benign prostatic hyperplasia (BPH) treatment trials on the outcome of subsequent tests. METHODS: One hundred forty-five male volunteers without known prostatic diseases with a mean age of 52 years (range 23 to 83) were given the American Urological Association (AUA) Symptom Index (SI), BPH Impact Index (II). Quality of Life (QOL) score, and a flow rate recording twice 10 to 20 days apart without any healthcare intervention. Data were collected and analyzed after typical BPH trial criteria were applied to the first test, and patients who did not "qualify" were censored. RESULTS: Good correlation exists between two closely spaced administrations of the AUA SI, BPH II, QOL score, and flow rate recordings in healthy male volunteers with correlation coefficients between 0.73 and 0.89. Censoring patients and excluding them from the analysis of the second test based on typical BPH trial criteria induces a regression to the mean phenomenon, which results in an artificial improvement in these outcome parameters. The magnitude of the improvement increases as the selection and censoring criteria tighten. The mean differences between the first and second test range from 1.4 to 1.7 mL/s for the peak flow rate, from -1.0 to -1.4 for the AUA SI, and from -0.4 to -0.8 for the BPH II. All these differences induced solely by censoring with resulting regression to the mean are statistically significant. CONCLUSIONS: Censoring of patients based on inclusion and exclusion criteria is typical for BPH treatment trials. One of the under-recognized effects of censoring is a regression to the mean, which leads to an apparent improvement in the outcome parameters assessed. In both placebo or sham-controlled trials, as well as in clinical series without controls, one must keep this effect and its relative magnitude in mind, and interpret the data from such trials with appropriate caution.
OBJECTIVES: To study the variability of assessment instruments (symptom questionnaires and flow rate recordings) in healthy volunteers during repeat administration in short intervals. To study the effect of inclusion criteria-based censoring of patients during screening for benign prostatic hyperplasia (BPH) treatment trials on the outcome of subsequent tests. METHODS: One hundred forty-five male volunteers without known prostatic diseases with a mean age of 52 years (range 23 to 83) were given the American Urological Association (AUA) Symptom Index (SI), BPH Impact Index (II). Quality of Life (QOL) score, and a flow rate recording twice 10 to 20 days apart without any healthcare intervention. Data were collected and analyzed after typical BPH trial criteria were applied to the first test, and patients who did not "qualify" were censored. RESULTS: Good correlation exists between two closely spaced administrations of the AUA SI, BPH II, QOL score, and flow rate recordings in healthy male volunteers with correlation coefficients between 0.73 and 0.89. Censoring patients and excluding them from the analysis of the second test based on typical BPH trial criteria induces a regression to the mean phenomenon, which results in an artificial improvement in these outcome parameters. The magnitude of the improvement increases as the selection and censoring criteria tighten. The mean differences between the first and second test range from 1.4 to 1.7 mL/s for the peak flow rate, from -1.0 to -1.4 for the AUA SI, and from -0.4 to -0.8 for the BPH II. All these differences induced solely by censoring with resulting regression to the mean are statistically significant. CONCLUSIONS: Censoring of patients based on inclusion and exclusion criteria is typical for BPH treatment trials. One of the under-recognized effects of censoring is a regression to the mean, which leads to an apparent improvement in the outcome parameters assessed. In both placebo or sham-controlled trials, as well as in clinical series without controls, one must keep this effect and its relative magnitude in mind, and interpret the data from such trials with appropriate caution.
Authors: Christian T Brown; Tet Yap; David A Cromwell; Lorna Rixon; Liz Steed; Kathleen Mulligan; Anthony Mundy; Stanton P Newman; Jan van der Meulen; Mark Emberton Journal: BMJ Date: 2006-11-21
Authors: Hadi Mostafaei; Sandra Jilch; Greta Lisa Carlin; Keiichiro Mori; Fahad Quhal; Benjamin Pradere; Ekaterina Laukhtina; Victor M Schuettfort; Abdulmajeed Aydh; Reza Sari Motlagh; Claus G Roehrborn; Shahrokh F Shariat; Sakineh Hajebrahimi Journal: Nat Rev Urol Date: 2021-12-23 Impact factor: 14.432
Authors: Sarah Ballou; Ted J Kaptchuk; William Hirsch; Judy Nee; Johanna Iturrino; Kathryn T Hall; John M Kelley; Vivian Cheng; Irving Kirsch; Eric Jacobson; Lisa Conboy; Anthony Lembo; Roger B Davis Journal: Trials Date: 2017-05-25 Impact factor: 2.279