Accounting for all randomised cases: handling non-compliance and missing data in surgical trials. Temitope Adewuyi.
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Accounting for all randomised cases: handling non-compliance and missing data in surgical trials.
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Accounting for all randomised cases: handling non-compliance and missing data in surgical trials. Temitope Adewuyi.
- 1. Accounting for all randomised cases: handling non-compliance and missing data in surgical trials Health Technology Assessment international Bilbao 2012 Temitope Adewuyi, Jonathan Cook , Graeme MacLennan Health Services Research Unit University of Aberdeen HSRU is funded by the Chief Scientist Office of the Scottish Government Health Directorates. The author accepts full responsibility for this talk.
- 2. Outline • Background • Methods • Results • Conclusions
- 3. Background What is a surgical trial? Saints Cosmas and Damian performing a miraculous transplantation (Courtesy: The Wellcome Library)
- 4. Challenges in surgical trials • What is a perfect trial? • Non-compliance – Equipoise – Surgery unnecessary/impossible • Missing data at follow-up – Decline further follow-up – Non-response
- 5. Why does it matter? Analysis Difference (95% CI) Intention-to-treat 2.4% (-1.0, 6.1) Per-protocol 4.3% (0.7, 8.2) Hollis BMJ 1999
- 6. Aim To assess non-compliance and missing data in RCTs of surgical procedures
- 7. Methods • Search strategy: surgical trials published in 2010 in six general medical journals and 12 surgical journals • Inclusion criteria: primary reports of RCTs involving at least one surgical procedure and any type of comparator • Assessment: two independent reviewers
- 8. Results: Search • Titles and abstracts screened: 462 • Full text assessed: 131 • Included studies: 92 – General medical journals: 17 (18%) – Surgical journals: 75 (82%)
- 9. Results: Included studies Number of arms Two 82 (89%) Three 8 ( 9%) Four 2 ( 2%) Number of participants Median (IQR) 111 (65, 202) Range 15 - 2522
- 10. Results: Non-compliance Yes 49 (60%) Median (IQR): 1% (0, 5%); n=79 Analysis approach: As-randomised 59 (74%) Per-protocol 18 (23%) As-treated 3 ( 4%)
- 11. Results: Missing data Yes 60 (71%) Median (IQR): 6% (0, 15%); n=83 Methods of handling missing data: Simple 53 (88%) Complex 5 ( 8%) Not reported 2 ( 3%)
- 12. Conclusion • Non-compliance and missing data are common but typically low levels • Inadequate methods of handling missing data and non-compliance are still used • Reporting of non-compliance and missing data is sub-optimal
Hinweis der Redaktion
- Good afternoon, I’m Temitope Adewuyi from the University of Aberdeen. the title of my project is “Accounting for all randomised cases: handling non-compliance and missing data in surgical trials”. I acknowledge my co-authors.
- I’ll start with the “Background”, then the “Methods”, “Results” and finally the “Conclusions.”
- A surgical trial is defined as one which involves interventions that physically change body tissues and organs through manual operation such as cutting, abrading, suturing or the use of lasers.
- In a perfect trial patients receive the allocated intervention and have complete follow-up data. In addition to the usual causes of non-compliance in all trials, surgical trials may be more prone to other reasons for patients receiving something other then the allocated intervention. Examples of these reasons are: Lack of surgical skill equipoise or differences in surgical learning curve Intra-op change in management because surgery was deemed unnecessary or impossible As blinding may be impractical, patients may have preference for an other procedures Missing data result when patients decline further follow up or there is non-response possibly due to resentful demoralisation from not getting the treatment option they hoped for. This is common when blinding is impractical.
- The table shows the results from a trial of medical vs surgical management of angina. In that trial, some medical patients deviated to surgery on the surgeon’s advice but on the operating table, some of them had inoperable arteries had to continue on tablets. The investigators did ITT and got a difference in mortality of 2.4% which was non-significant. If they had excluded patients who did not get the allocated treatment, the difference in mortality would be 4.3% and significant. The investigators used ITT so as to minimise bias that could result from self-selecting patients into ad hoc groups. Therefore, how one deals with non-compliance and missing data may affect trial results.
- Slide 8: Aim and Objectives The aim of this review was to assess non-compliance and missing data in RCTs of surgical procedures.
- We conducted a systematic review of methodology and systematically searched in MEDLINE for surgical RCTs published in 2010 in six general medical journals and 12 surgical journals Only primary reports of RCTs involving at least one surgical procedure were included. Two independent reviewers assessed abstracts and full texts.
- Of 462 titles and abstracts, 131 full texts were assessed and 92 were included. Seventeen and 75 of the included studies were from the GMJs and SJs respectively.
- There were 82 two arm, eight three arm and two four arm studies . The median number of participants per study was 111 with an IQR of 65, 202 and a range of 15 to 2522.
- In 81 studies, the occurrence of non-compliance was ascertainable while it was not in 11 studies. Of the 81 studies, 49 had non-compliance and in 2 of the 49, it was not quantifiable. The commonest reason for non-compliance were challenges related to surgical technique or contraindications to surgery. Patient’s preference for another procedure was also a common reason for non-compliance while there were a few instances of unavailability of surgical materials. The median non-compliance was 1% with an IQR of 0 to 5%. In the 11 studies in which the occurrence of non-compliance was not ascertainable, the method of analysis of the primary outcome was not ascertainable either. Therefore, of the remaining 81, 59 analysed as randomised, 18 per-protocol, 3 as treated and in one study, the method used was unclear.
- In 84 studies, the occurrence of missing data was ascertainable while it was not in 8 studies. Of the 84 studies, 60 had missing data and in 1 of the 60, it was not quantifiable. The commonest reason for missing data were loss to follow-up/non-response and missed visits. Patient’s preference for another procedure was also a common reason for non-compliance while there were a few instances of unavailability of surgical materials. The median missing data was 6% with an IQR of 0 to 15%. In the 8 studies in which the occurrence of missing data was not ascertainable, the method of handling missing data was not ascertainable either. Therefore, of 60 studies with missing data, 53 used simple methods such as complete-case analysis, simple imputations, log rank test, Cox regression and survival analysis; 5 used complex methods such as regression and multiple imputations and Mixed model effect and in 2 studies, the method was not reported.
- We concluded that non-compliance and missing data are common but typically low levels. Inadequate methods of handling missing data and non-compliance are still used as the vast majority of studies used simple methods of handling missing data despite widespread availability of more robust techniques. Reporting of non-compliance and missing data is sub-optimal as 12% and 9% of studies did not comment on the occurrence or otherwise of non-compliance and missing data respectively).