The therapeutic effect of clinical trials: understanding placebo response rates in clinical trials--a secondary analysis.
OBJECTIVE
Placebo response rates in clinical trials vary considerably and are observed frequently. For new drugs it can be difficult to prove effectiveness superior to placebo. It is unclear what contributes to improvement in the placebo groups. We wanted to clarify, what elements of clinical trials determine placebo variability.


METHODS
We analysed a representative sample of 141 published long-term trials (randomized, double-blind, placebo-controlled; duration > 12 weeks) to find out what study characteristics predict placebo response rates in various diseases. Correlational and regression analyses with study characteristics and placebo response rates were carried out.


RESULTS
We found a high and significant correlation between placebo and treatment response rate across diseases (r = .78; p < .001). A multiple regression model explained 79% of the variance in placebo variability (F = 59.7; p < 0.0001). Significant predictors are, among others, the duration of the study (beta = .31), the quality of the study (beta = .18), the fact whether a study is a prevention trial (beta = .44), whether dropouts have been documented (beta = -.20), or whether additional treatments have been documented (beta = -.17). Healing rates with placebo are lower in the following diagnoses; neoplasms (beta = -.21), nervous diseases (beta = -.10), substance abuse (beta = -.14). Without prevention trials the amount of variance explained is 42%.


CONCLUSIONS
Medication response rates and placebo response rates in clinical trials are highly correlated. Trial characteristics can explain some portion of the variance in placebo healing rates in RCTs. Placebo response in trials is only partially due to methodological artefacts and only partially dependent on the diagnoses treated.
Walach
Harald
H
University Hospital Freiburg, Brsg., Institute of Environmental Medicine and Hospital Epidemiology, Germany. harald.walach@northampont.ac.uk
Sadaghiani
Catarina
C
Dehm
Cornelia
C
Bierman
Dick
D
D003627:Data Interpretation, Statistical; D004311:Double-Blind Method; D004341:Drug Evaluation / Q000379:methods*; D006801:Humans; D009010:Monte Carlo Method; D015990:Placebo Effect; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data*; D012044:Regression Analysis; D012107:Research Design / Q000706:statistics & numerical data; D035842:Research Subjects / Q000523:psychology*; D013997:Time Factors; D016896:Treatment Outcome