Quality of controlled clinical trials on glaucoma and intraocular high pressure

J Glaucoma. 2005 Jun;14(3):190-5. doi: 10.1097/01.ijg.0000159124.57112.69.


Aim: To study the quality of controlled clinical trials on glaucoma.

Methods: Two hundred and twenty-six clinical trials published between 1980 and 1999 were selected from seven international ophthalmological journals. Their quality was assessed by four researchers with epidemiological skills using a structured questionnaire.

Results: Sample size was pre-estimated in 34 (15.0%) papers, which were of greater size (P = 0.05). Randomization was performed in 98.2% of the trials, although the procedure of randomization was scarcely reported. Masking was reported in 56.6% of the papers, and was more frequent in medical treatments (P < 0.001). The basal characteristics of the groups were compared in 139 papers (61.5%). Patient losses during the follow-up period were fully described in only 27 trials. Intention-to-treat analysis was used in 17 (7.7%) papers. Most trials reported P values, but a measure of effect (mean, proportion, or relative risk) appeared in only 16 trials (7.7%). Trials performed in the US more frequently compared baseline characteristics of the groups (P = 0.03), described the patient flow (P = 0.04), and used adequate statistical procedures (P = 0.03). Those trials that included a statistician or an epidemiologist among the authors were more commonly blinded (P = 0.06) and they always avoided the analyses of subgroups (P = 0.006). Several methodological issues have improved throughout the studied period.

Conclusions: Several methodological characteristics should be improved when reporting a clinical trial on glaucoma. Using a checklist like that suggested by the CONSORT can help to achieve this.

MeSH terms

  • Controlled Clinical Trials as Topic / standards*
  • Controlled Clinical Trials as Topic / statistics & numerical data
  • Glaucoma*
  • Humans
  • Intraocular Pressure*
  • Ocular Hypertension
  • Publishing / standards*
  • Publishing / statistics & numerical data
  • Quality Control*
  • Research Design / standards