Non-entry of eligible patients into the Australasian laparoscopic colon cancer study

Abstract

<h4>Background</h4>There is currently a need to assess the reasons for non-entry of eligible patients into surgical randomized controlled trials to determine measures to improve the low recruitment rates in such trials.<h4>Methods</h4>Reasons for non-entry of all eligible patients not recruited into the Australasian Laparoscopic Colon Cancer Study were prospectively recorded using a survey completed by the participating surgeons for a period of 6 months.<h4>Results</h4>In the 6-month period of the study, 51 (45%) out of 113 eligible patients examined by the 18 actively participating surgeons were recruited into the trial. Eighty-nine reasons were recorded for the non-entry of the 62 eligible patients. The most commonly recorded reason was preference for one form of surgery (42%) or the surgeon (31%) by the patient (45 patients (73%) in total). This was followed by lack of time (10 patients (16%)), hospital accreditation (7 patients (11%)) or staffing/equipment (6 patients (10%)). Concern about the doctor-patient relationship or causing the patient anxiety was recorded for three (5%) and two (3%) patients, respectively. Recruitment was positively associated with the availability of a data manager (chi2 = 19.91; P < 0.001, odds ratio (95% confidence interval) = 9.50 (3.53-25.53)) and negatively associated with an increased caseload (more than five eligible patients seen by the surgeon in the study period) (continuity adjusted chi2 = 16.052; P < 0.001, odds ratio (95% confidence interval) = 0.11(0.04-0.30)).<h4>Conclusion</h4>Having a preference for one form of surgery by the patient or the surgeon was the most common reason for non-entry of eligible patients in the Australasian Laparoscopic Colon Cancer Study. Concern about the doctor-patient relationship played a minimal role in determining the outcome of recruitment. Patient and surgeon preferences, caseload and the distribution of supportive staff such as data managers according to patient population density should be considered in the planning of future trials.