Cochrane in CORR®: Strategies to Improve Recruitment to Randomised Trials
Notice bibliographique
Résumé
Importance of the Topic Although an essential part of conducting a clinical trial, recruiting patients is challenging, time consuming, and requires planning and expertise. Trials that recruit slowly take longer to complete and therefore cost more money, leading to inefficiencies in funding and frustration for funders and investigators. Beyond cost and time issues, poor trial recruitment can lead to stopping early for feasibility reasons, leading to underpowered trials. Underpowered trials are a major source of research waste, which has been described as “unethical conduct” and a “moral issue” [3] because patients are exposed to potentially harmful interventions for little scientific benefit, and public research funds are used improperly. Framing the concept of insufficient sample size as a moral issue may sound extreme or unfair given that well-intentioned investigators sometimes encounter unanticipated problems, however, the principle that prospective trials should take steps to ensure adequate recruitment is fundamentally correct both for scientific and social reasons. The Cochrane review by Treweek and colleagues [9] aims to identify the effective methods for improving trial recruitment in randomized trials. An update to two earlier Cochrane systematic reviews, this review contains 68 studies (totaling more than 74,000 patients) of which some were real trials, and some were hypothetical trials in which patients were asked whether they would participate if the trial was real [9]. The authors placed more emphasis on the real trials where possible because patients’ answers in the hypothetical situations may be different from real situations. The authors considered 72 interventions that sought to improve recruitment in randomized trials. Of those, high-quality evidence from more than one study allowed them to draw only three conclusions: (1) Open rather than blinded, placebo controlled trials increased recruitment by a modest amount (about 10%), (2) using telephone reminders increased recruitment in trials that otherwise had low (< 10%) recruitment, but the size of this effect was small (a 6% increase), and (3) creating customized patient-information leaflets made little or no difference in recruitment. The authors’ conclusions provide very little information on which to change practice, despite there being 68 included studies. Upon Closer Inspection Although the Cochrane review does not address this issue, an issue closely related to trial recruitment is trial retention (also known as followup). Loss to followup affects trials in a similar way to ineffective recruitment; it leads to loss of power and/or increased time and cost [6, 10]. There have been two studies [6, 8] in orthopaedics of which we are aware that demonstrated comprehensive strategies to minimize loss to followup by using a combination of targeted and general strategies. Examples of general strategies include designing trials such that followup aligns with standard clinical visits, selecting outcomes that could be obtained over the phone or in person, and compensating participating sites based on the proportion of patients who are accounted for at latest followup. Targeted strategies for patients at high risk of being lost to followup include collecting multiple pieces of contact information, searching local phone books, obituaries, and death registries, and prioritizing outcome measures if patients feel overburdened by questionnaires [6, 8]. It is possible that very few useful conclusions could be drawn from the available literature because a multi-faceted intervention is required. Therefore, if more studies are conducted on trial recruitment in the future, they should evaluate more-comprehensive sets of methods to maximize recruitment. For example, a multifaceted intervention could include an open design with several reminder methods, recruitment that does not require special visits, and develop targeted strategies for patients at risk of not being recruited. Take-home Messages Some of the included studies were from surgical disciplines [1, 7], but only one was specific to orthopaedics (a vitamin D trial) [2]. The Cochrane review finding that open trials recruit better than blinded trials is of particular interest for surgical trials. Surgical trials often face challenges regarding blinding to a much-greater degree than do medical and drug trials. Surgeons often cannot be blinded, and even blinding patients can be a challenge when they see their radiographs or surgical incisions. One way to minimize the risk of bias associated with blinding in surgical trials, even when blinding patients and surgeons is impossible, is to blind other members of the study team, particularly outcome assessors and data analysts [5]. Additionally, trial investigators can prepare blinded interpretation documents to minimize the risk of interpretation bias [4]. Surgeons can use this finding to methodologically justify not blinding patients in trials where it is impossible to do so.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,381 | 0,798 |
| Méta-épidémiologie (sens strict) | 0,006 | 0,010 |
| Méta-épidémiologie (sens large) | 0,011 | 0,012 |
| Bibliométrie | 0,046 | 0,037 |
| Études des sciences et des technologies | 0,003 | 0,006 |
| Communication savante | 0,018 | 0,024 |
| Science ouverte | 0,011 | 0,027 |
| Intégrité de la recherche | 0,019 | 0,015 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,174 | 0,078 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; l’étiquette directe de Gemma et le classifieur distillé Codex s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».