Two to five repeated measurements per patient reduced the required sample size considerably in a randomized clinical trial for patients with inflammatory rheumatic diseases

• Published in: BMC research notes 2013-02, Vol.6 (1), p.37-37, Article 37
• Main Authors: Smedslund, Geir, Zangi, Heidi Andersen, Mowinckel, Petter, Hagen, Kåre Birger
• Format: Article
• Language: English
• Subjects: Arthritis; Clinical trial; Clinical trials; Fatigue; General health questionnaire; Humans; Likert scale; Pain; Patients; Rheumatic diseases; Rheumatic Fever - physiopathology; Rheumatic Fever - psychology; Rheumatology; Sample Size; Self Care; Short Report; Standard deviation; Statistical methods; Statistical power; Studies; Surveys and Questionnaires
• ISSN: 1756-0500; 1756-0500
• DOI: 10.1186/1756-0500-6-37

Patient reported outcomes are accepted as important outcome measures in rheumatology. The fluctuating symptoms in patients with rheumatic diseases have serious implications for sample size in clinical trials. We estimated the effects of measuring the outcome 1-5 times on the sample size required in a two-armed trial. In a randomized controlled trial that evaluated the effects of a mindfulness-based group intervention for patients with inflammatory arthritis (n=71), the outcome variables Numerical Rating Scales (NRS) (pain, fatigue, disease activity, self-care ability, and emotional wellbeing) and General Health Questionnaire (GHQ-20) were measured five times before and after the intervention. For each variable we calculated the necessary sample sizes for obtaining 80% power (α=.05) for one up to five measurements.Two, three, and four measures reduced the required sample sizes by 15%, 21%, and 24%, respectively. With three (and five) measures, the required sample size per group was reduced from 56 to 39 (32) for the GHQ-20, from 71 to 60 (55) for pain, 96 to 71 (73) for fatigue, 57 to 51 (48) for disease activity, 59 to 44 (45) for self-care, and 47 to 37 (33) for emotional wellbeing. Measuring the outcomes five times rather than once reduced the necessary sample size by an average of 27%. When planning a study, researchers should carefully compare the advantages and disadvantages of increasing sample size versus employing three to five repeated measurements in order to obtain the required statistical power.