Estimating Treatment Effects in Clinical Trials Subject to Regression to the Mean

Biometrics ◽  
1985 ◽  
Vol 41 (2) ◽  
pp. 555 ◽  
Author(s):  
Stephen J. Senn ◽  
Richard A. Brown ◽  
K. E. James
Rheumatology ◽  
2021 ◽  
Author(s):  
Robyn T Domsic ◽  
Shiyao Gao ◽  
Maureen Laffoon ◽  
Steven Wisniewski ◽  
Yuqing Zhang ◽  
...  

Abstract Objectives Clinical trials in early diffuse cutaneous systemic sclerosis (SSc) using the modified Rodnan skin score (mRSS) as the primary outcome measure have most often been negative. We wanted to assess how the definition of disease onset (first SSc manifestation vs first non-Raynaud manifestation), and varying lengths of disease duration at trial entry as an inclusion criteria functioned. Our objective was to optimize trial inclusion criteria Methods We used the prospective, observational University of Pittsburgh Scleroderma Cohort to identify early diffuse SSc patients first evaluated between 1980 and 2015. All had <3 years from first SSc (n = 481) or first non-Raynaud manifestation (n = 514) and 3 or more mRSS scores. We used descriptive, survival and group-based trajectory analyses to compare the different definitions of disease onset and disease duration as inclusion criteria for clinical trials. Results There was no appreciable difference between using first SSc manifestation compared with first non-Raynaud manifestation as the definition of disease onset. Compared with other disease durations, <18 months of disease had >70% of patients fitting into trajectories with worsening cutaneous disease over six months of follow-up. Longer disease durations demonstrated the majority of patients with trajectories showing an improvement in mRSS (regression to the mean) over six months. Conclusions Regardless of whether the first SSc or first non-Raynaud manifestation is used to define disease onset, duration of < 18 months at enrolment is preferable. Longer disease duration criteria more frequently results in regression to the mean of the mRSS score, and likely contributes to negative trial outcomes.


2021 ◽  
pp. ASN.2021070948
Author(s):  
Brendon Neuen ◽  
Hocine Tighiouart ◽  
Hiddo Heerspink ◽  
Edward Vonesh ◽  
Juhi Chaudhari ◽  
...  

Background Acute changes in glomerular filtration rate (GFR) can occur following initiation of interventions targeting progression of chronic kidney disease (CKD). These acute changes complicate the interpretation of long-term treatment effects. Methods To assess the magnitude and consistency of acute effects in randomized clinical trials and explore factors that might affect them, we performed a meta-analysis of 53 randomized clinical trials for CKD progression enrolling 56,413 participants with at least one estimated GFR measurement by 6 months following randomization. We defined acute treatment effects as the mean difference in GFR slope from baseline to 3 months between randomized groups. We performed univariable and multivariable meta-regression to assess the effect of intervention type, disease state, baseline GFR, and albuminuria on the magnitude of acute effects. Results The mean acute effect across all studies was -0.21 mL/min per 1.73m2 (95% confidence interval, -0.63 to 0.22) over 3 months, with substantial heterogeneity across interventions (95% coverage interval across studies, -2.50 to +2.08 mL/min per 1.73m2). We observed negative average acute effects in renin angiotensin system blockade, BP lowering, and sodium-glucose cotransporter 2 inhibitor trials, and positive acute effects in trials of immunosuppressive agents. Larger negative acute effects were observed in trials with a higher mean baseline GFR. Conclusion The magnitude and consistency of acute GFR effects vary across different interventions, and are larger at higher baseline GFR. Understanding the nature and magnitude of acute effects can help inform the optimal design of randomized clinical trials evaluating disease progression in CKD.


2004 ◽  
Vol 1 (4) ◽  
pp. 323-328 ◽  
Author(s):  
Jeffrey Cummings ◽  
Rochelle Tractenberg ◽  
Anthony Gamst ◽  
Linda Teri ◽  
Donna Masterman ◽  
...  

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Shu Zhang ◽  
◽  
Dongdong Qin ◽  
Liwen Wu ◽  
Man Li ◽  
...  

Abstract Background Duchenne muscular dystrophy (DMD) is the most common genetic muscle disease in human. We aimed to describe the genotype distribution in a large cohort of Chinese DMD patients and their delayed loss of ambulation by glucocorticoid (GC) treatments. This is to facilitate protocol designs and outcome measures for the emerging DMD clinical trials. Results A total of 1163 patients with DMD were recruited and genotyped. Genotype variations were categorized as large deletions, large duplications, and small mutations. Large deletions were further analyzed for those amenable to exon-skipping therapies. Participants aged 5 years or older were grouped into GC-treated and GC-naïve groups. Clinical progression among different genotypes and their responses to GC treatments were measured by age at loss of ambulation (LOA). Among the mutation genotypes, large deletions, large duplications, and small mutations accounted for 68.79%, 7.14%, and 24.07%, respectively. The mean age at diagnosis was 4.59 years; the median ages at LOA for the GC-naïve, prednisone/prednisolone-treated, and deflazacort-treated groups were 10.23, 12.02, and 13.95 years, respectively. The “deletion amenable to skipping exon 44” subgroup and the nonsense-mutation subgroup had older ages at LOA than the “other deletions” subgroup. Subgroups were further analyzed by both genotypes and GC status. All genotypes showed significant beneficial responses to GC treatment. Deletions amenable to skipping exon 44 showed a lower hazard ratio (0.155). The mean age at death was 18.57 years in this DMD group. Conclusion Genotype variation influences clinical progression in certain DMD groups. Beneficial responses to GC treatment were observed among all DMD genotypes. Compared with other genotypes, deletions amenable to skipping exon 44 had a lower hazard ratio, which may indicate a stronger protective effect of GC treatments on this subgroup. These data are valuable for designing future clinical trials, as clinical outcomes may be influenced by the genotypes.


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