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. 2021 Jul 27;16(7):e0255361. doi: 10.1371/journal.pone.0255361

An evaluation of factors that may influence clinicians’ decisions not to enroll eligible patients into randomized trials in critical care

Mahesh Ramanan 1,2,3,4,*, Laurent Billot 2, Dorrilyn Rajbhandari 2, John Myburgh 2, Balasubramanian Venkatesh 2,4,5,6
Editor: Linda L Maerz7
PMCID: PMC8315530  PMID: 34314449

Abstract

Objectives

To determine the association between intensive care unit (ICU) characteristics and clinicians’ decision to decline eligible patients for randomization into a multicentered pragmatic comparative-effectiveness controlled trial.

Methods

Screening logs from the Adjunctive Glucocorticoid Therapy in Septic Shock Trial (ADRENAL) and site-level data from the College of Intensive Care Medicine and Australia New Zealand Intensive Care Society were examined. The effects of ICU characteristics such as tertiary academic status, research coordinator availability, number of admissions, and ICU affiliations on clinicians declining to randomize eligible patients were calculated using mixed effects logistic regression modelling.

Results

There were 21,818 patients screened for inclusion in the ADRENAL trial at 69 sites across five countries, out of which 5,501 were eligible, 3,800 were randomized and 659 eligible patients were declined for randomization by the treating clinician. The proportion of eligible patients declined by clinicians at individual ICUs ranged from 0 to41%. In the multivariable model, none of the ICU characteristics were significantly associated with higher clinician decline rate.

Conclusions

Neither tertiary academic status, nor other site-level variables were significantly associated with increased rate of clinicians declining eligible patients.

Background

Prompt enrollment of eligible patients into randomized controlled trials (RCTs) is recognized as a research priority [1]. Enrolment of patients into RCTs in critical care poses challenges including difficulties in obtaining consent because of their altered conscious state due to either underlying conditions or acute therapeutic interventions [2, 3]. Within this environment, attending clinicians may decline to enroll potentially eligible patients, which has been reported to occur for 3–15% of eligible patients [3, 4].

A detailed evaluation of the influence of site-level factors on the clinician decline rate, that is the proportion of eligible patients that are declined for randomization by the treating clinician, in critical care RCTs has not been performed. Some reasons provided by clinicians relate to the nature of the intervention and lack of equipoise. We hypothesized that factors such as the academic and tertiary status of the intensive care unit (ICU) and availability of dedicated research staff may be associated with reduced clinician decline rate.

We performed this study to determine associations between ICU characteristics and clinician decline rate from a large-scale, investigator-initiated, pragmatic, international RCT.

Methods

Institutional Review Board approval was obtained from The Prince Charles Hospital Human Research Ethics Committee (LNR/2018/QPCH/44975).

Patient randomization data was extracted from the Adjunctive glucocorticoid therapy in patients with septic shock [5] (ADRENAL) screening log and linked to ICU characteristics obtained from the Critical Care Resources registry maintained by Australia New Zealand Intensive Care Society (ANZICS) Centre for Outcome and Resource Evaluation. For non-Australia and New Zealand sites, these data were extracted from the site selection and feasibility log. The screening log contained date and site at which each patient was screened, whether they were eligible, randomized, and reason for not being randomized. We defined tertiary ICU status as any ICU meeting criteria for a Level III ICU as per College of Intensive Care Medicine of Australia and New Zealand [6].

The primary outcome was a binary variable indicating whether an eligible patient was declined for randomization by the treating clinician and was analyzed using a multivariable mixed effects logistic regression model. The clinician decline rate was calculated as the proportion of eligible patients who were declined for enrolment by the treating clinician and was presented as median and interquartile range (IQR). Univariate analyses comparing characteristics of tertiary and non-tertiary sites were performed using Mann-Whitney U test and Fishers exact test for continuous and categorical variables. ICU-level variables (volume, i.e., number of admissions per annum; research coordinator full-time equivalent (FTE); after-hours research coordinator availability; dedicated director of research FTE; and ANZICS Clinical Trials Group membership) were entered as fixed effects and site as random effect, with patients nested within sites. Two models were created; one for Australian and New Zealand sites only (additional covariates were available for these sites) and one including all sites. The effect of the covariates on the risk of being declined for randomization was presented as an adjusted odds ratio (OR) with 95% confidence interval (CI) and p-value <0.05 considered significant.

Results

The ADRENAL trial screened 21,818 patients from 69 sites, of whom 5,501 were eligible for randomization, and 3 800 were randomized. The characteristics of tertiary and non-tertiary ICUs participating in the trial are listed in Table 1. Of the 1,701 patients who were eligible but not randomized, 659 were declined for randomization by the treating clinician. Clinician decline rates ranged from 0 to 41%(median rate of 7%, IQR 2–19% for tertiary sites and 9%, IQR 0–20% for non-tertiary sites).

Table 1. Site-level characteristics of tertiary and non-tertiary ICUs that participated in the ADRENAL trial.

Non-tertiary (n = 35 ICUs) Tertiary (n = 34 ICUs) Total (n = 69 ICUs) P †
Volume (admissions per annum), median (IQR) 909.5 (633–1320) 1737 (1244–2156) 1244 (850–1762) <0.001
Director of Research FTE*, median (IQR) 0 (0–0.05) 0 (0–0.23) 0 (0–0.1) 0.3
Research coordinator FTE, median (IQR) 1 (1–2) 2 (1–3) 2 (1–3) 0.02
After-hours research coordinator availability n (%) 13 (37.1) 13 (38.2) 26 (37.7) 0.9
CTG membership* n (%) 16 (55.2) 23 (95.8) 39 (73.6) 0.001
Country n (%) 0.5
Australia 26 (74.3) 19 (55.9) 45 (65.2)
New Zealand 3 (8.6) 5 (14.7) 8 (11.6)
Denmark 0 (0) 1 (2.9) 1 (1.5)
Saudi Arabia 1 (2.9) 2 (5.9) 3 (4.4)
United Kingdom 5 (14.3) 7 (20.6) 12 (17.4)
CDR, median (IQR) 0.09 (0–0.2) 0.07 (0.02–0.19) 0.09 (0.01–0.19) 0.8
Open in a new tab

Definitions of abbreviations: ICU = intensive care unit; ADRENAL = Venkatesh et al. ‘Adjunctive glucocorticoid therapy in patients with septic shock’ Trial; IQR = interquartile range; FTE = full-time equivalent; CTG = Australia New Zealand Intensive Care Society Clinical Trials Group; CDR = clinician decline rate

* Director of Research FTE and CTG membership data is for Australia and New Zealand sites only

* † p values presented in this column have been generated from Fisher’s exact test for categorical variables and Mann-Whitney U tests for continuous variables. Bold p-values are statistically significant

In the multivariable analysis (Table 2), tertiary status was not associated with a significantly reduced clinician decline rate (OR 0.89, 95% CI 0.35–2.31, p = 0.8 for all sites model; OR 0.52, 95% CI 0.17–1.59, p = 0.3 for Australia and New Zealand sites model). None of the other available covariates were significantly associated with clinician decline rate in either model.

Table 2. Multivariable logistic regression for eligible patients being declined for randomization by clinicians in the ADRENAL trial.

All sites model (n = 5329) Odds Ratio (95% CI) P*
Tertiary ICU (versus non-tertiary) 0.89(0.35–2.31) 0.8
ANZ site (yes versus no) 1.86(0.62–5.59) 0.3
Volume (per 1000 admissions/year) 1.14(0.66–1.98) 0.6
First author site (yes versus no) 0.29(0.03–3.13) 0.3
Management committee site (yes versus no) 1.27(0.41–3.97) 0.7
Research coordinator FTE (per 1 FTE) 0.99(0.73–1.34) 1
After-hours research coordinator availability (yes versus no) 0.70(0.31–1.56) 0.4
ANZ sites only model (n = 4291) Odds Ratio (95% CI) p
Tertiary ICU (versus non-tertiary) 0.52(0.17–1.59) 0.3
Volume (per 1000 admissions/year) 1.15(0.52–2.55) 0.7
CTG membership (yes versus no) 2.86(0.92–8.88) 0.1
First author site (yes versus no) 0.27(0.03–2.61) 0.3
Management committee site (yes versus no) 1.87(0.56–6.19) 0.3
Research coordinator FTE (per 1 FTE) 0.99(0.63–1.55) 1
After-hours research coordinator availability (yes versus no) 0.76(0.34–1.71) 0.5
Director of Research FTE (per 1 FTE) 0.84(0.24–2.97) 0.8
Open in a new tab

Definitions of abbreviations: ICU = intensive care unit; ADRENAL = Venkatesh et al. ‘Adjunctive glucocorticoid therapy in patients with septic shock’ Trial; ANZ = Australia and New Zealand; FTE = full- time equivalent; CTG = Australia New Zealand Intensive Care Society Clinical Trials Group

* Each effect estimate listed in this table has been generated from one of two multivariable mixed effects model (“All sites model” and “ANZ sites only model”) i.e., they are adjusted for all other variables listed in the table.

Discussion

The decision by a clinician to exclude a potentially eligible patient is a recognized cause of reduced enrolment into a clinical trial. Using a representative international, large-scale pragmatic RCT in critically ill patients, we report that nearly twelve percent of eligible patients were declined for enrolment by treating clinicians. This rate was not influenced by the academic status of the ICU nor other site characteristics. The ADRENAL trial was a pragmatic study evaluating a commonly used intervention and also allowed deferred consent (patients were allowed to be randomized into the trial and consent obtained subsequently).

The reasons for clinicians declining to enroll eligible patients were not collected in the screening log. The availability of adequate site level resources for trial conduct, the use of a pragmatic and user-friendly consent model and clinician familiarity with the intervention being tested suggest that these were unlikely contributors to the clinician decline rate.

The possibility that clinician equipoise plays a role in patient enrollment needs to be considered. Clinicians have used corticosteroids for the management of septic shock for more than 50 years. International surveys pre and post ADRENAL have demonstrated marked variability in practice in terms of the type, dose and the triggers for corticosteroid prescription in patients with septic shock [7, 8]. These findings suggest that there may be clinician biases in selection of patients for corticosteroid prescription in clinical practice and whether these decisions influenced enrolment into the ADRENAL trial is not known.

Whilst RCTs have traditionally been conducted in large tertiary centers [9], our results show that the participation of smaller non-tertiary centers not only add to patient enrollment, but have similar, comparable recruitment patterns.

We acknowledge that this study is limited by a lack of power, as suggested by the wide confidence intervals in the multivariable analysis. Hence, the findings presented here should be considered exploratory. Nonetheless, the ADRENAL trial was a pragmatic, multinational trial that is representative of modern, large-scale critical care trials and collected detailed screening logs from all recruiting sites. Combined with resourcing data from a high-quality binational registry, the findings presented are robust with respect to internal validity. To improve external validity, a larger sample of trials would be required to confirm our findings.

Further investigation into the factors influencing clinician decline rate is warranted. We recommend that screening logs collect additional data to include patient-related, intervention-related, consent-related, or clinician decision factors that lead to eligible patients not being randomized into clinical trials. The establishment of a ‘baseline’ clinician decline rate (due to non-modifiable factors) may be useful in benchmarking the performance of RCTs as well as individual trial sites. Given that some sites will be participating in multiple trials simultaneously, data on co-enrollment at a site-level would allow for comparisons of the clinician decline rate, not just between sites, but also between trials as well.

Monitoring the clinician decline rate over the course of a trial may inform trial management committees to address this issue on a real-time basis, so that interventions such as increased frequency and intensity of educational site visits can be effectively targeted.

Conclusion

Clinicians declining to randomize patients into critical care RCTs has a substantive effect on patient enrollment, but this does not appear to be associated with individual site characteristics.

Supporting information

S1 File. List of participating sites.

(PDF)

Click here for additional data file. (216.3KB, pdf)

Acknowledgments

The authors thank the College of Intensive Care Medicine of Australia and New Zealand, the Australia New Zealand Intensive Care Society Centre for Outcomes and Resource Evaluation management committee, and clinicians, data collectors, and researchers at the contributing sites listed in S1 File.

Data Availability

Data can be made available on request pending approvals from the relevant Institutional Review Board, the Management Committee of the Australia New Zealand Intensive Care Society Centre for Outcomes and Resource Evaluation (as outlined here: https://www.anzics.com.au/data-access-and-publication-policy/), and The George Institute for Global Health (as outlined here: https://www.georgeinstitute.org/data-sharing-policy)

Funding Statement

The author(s) received no specific funding for this work.

References

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Decision Letter 0

Linda L Maerz

23 Apr 2021

PONE-D-21-04343

An evaluation of factors that may influence clinicians’ decisions not to enrol eligible patients into randomized trials in critical care.

PLOS ONE

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Reviewer #1: The authors' question is important and relevant.

It is logical to characterize the study sites as having trainees and research support to attempt to identify reasons why clinicians may not include eligible patients in a clinical trial.

However, the study is a bit superficial:

First - Only one trial (ADRENAL), though a large trial, was included in the analysis. Any trial specific factors cannot be isolated or assessed. In other words, it is difficult to say if the included research sites had specific protocol reasons to decline eligible patients. Including other trials would potentially provide additional clarity.

Second - Additional site-level characteristics are needed. It is a big jump to say that because there is no correlation between a site being academic or having research support that the clinicians are likely concerned about a lack of equipoise.

While it helps that the ADRENAL trial allowed deferred consent, the authors' conclusion is still based on speculation.

For example, in how many other trials of this size did the sites participate?

Were the rates of declined eligible patients similar for all studies?

This manuscript will be more robust with the answers to these questions.

Reviewer #2: The methods are described with adequate detail. The study is probably underpowered as indicated by the wide confidence intervals reported for many of the variables. Realizing that that the sample size was fixed by what was available in the RCT data base I did not see a description of how adequate power was estimated. Having an estimate of the sample size required to detect differences in outcome could inform future studies and place the current results in perspective.

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Attachment

Submitted filename: PONE-D-21-04343-1 [suggeted edits].docx

Click here for additional data file. (55.1KB, docx)
PLoS One. 2021 Jul 27;16(7):e0255361. doi: 10.1371/journal.pone.0255361.r002

Author response to Decision Letter 0

20 May 2021

Dear Prof Linda Maerz,

Thank you for your thoughtful review and for giving us an opportunity to submit a revised manuscript. We have addressed all the points raised by the Reviewers and Editors. Our responses are highlighted in yellow after each query. Tracked and clean versions of the manuscript are attached to the submission as requested.

We look forward to hearing the outcome of your review.

Yours sincerely,

Mahesh Ramanan on behalf of all authors

Date: 11 May 2021

Reviewer 1

It is logical to characterize the study sites as having trainees and research support to attempt to identify reasons why clinicians may not include eligible patients in a clinical trial.

However, the study is a bit superficial:

First - Only one trial (ADRENAL), though a large trial, was included in the analysis. Any trial specific factors cannot be isolated or assessed. In other words, it is difficult to say if the included research sites had specific protocol reasons to decline eligible patients. Including other trials would potentially provide additional clarity.

Thank you for your review and comments. It is true that trial-specific factors cannot be assessed with our study. Having access to a larger group of trials with similar data would be ideal. However, this was not the case for our study as we did not have access to such data. We have included a statement in the discussion to this effect.

Second - Additional site-level characteristics are needed. It is a big jump to say that because there is no correlation between a site being academic or having research support that the clinicians are likely concerned about a lack of equipoise.

While it helps that the ADRENAL trial allowed deferred consent, the authors' conclusion is still based on speculation.

For example, in how many other trials of this size did the sites participate?

Were the rates of declined eligible patients similar for all studies?

That particular statement with regards to deferred consent and clinician equipoise is indeed speculative, as we have acknowledged in the text. We have added some further discussion to clarify this point.

The data concerning other trials (‘competing trials’) and particularly the rates of CDR in these trials was not available to us. The ADRENAL trial protocol did allow for co-enrollment with several other trials, so it is possible that there were sites which were recruiting in competing trials.

Reviewer 2

The methods are described with adequate detail. The study is probably underpowered as indicated by the wide confidence intervals reported for many of the variables. Realizing that that the sample size was fixed by what was available in the RCT data base I did not see a description of how adequate power was estimated. Having an estimate of the sample size required to detect differences in outcome could inform future studies and place the current results in perspective.

Thank you for your review and for raising the important issue of statistical power. We did not have a baseline clinician decline rate which could be used for power calculations, hence, a priori calculations were not performed. Our results may be used to inform sample size calculations for future studies.

We have elected not to perform post hoc calculations of power as there is significant controversy in the biostatistics literature regarding the validity of such calculations. A recent publication by Zhang et al (Zhang Y, Hedo R, Rivera A, et al. Post hoc power analysis: is it an informative and meaningful analysis? General Psychiatry 2019;32:e100069. doi: 10.1136/gpsych-2019-100069) had the following concluding statements:

“Power analysis is an indispensable component of planning clinical research studies. However, when used to indicate power for outcomes already observed, it is not only conceptually flawed but also analytically misleading. Our simulation results show that such power analyses do not indicate true power for detecting statistical significance, since post hoc power estimates are generally variable in the range of practical interest and can be very different from the true power.

In this report, we focus on the relatively simple statistical model for comparing two population means of continuous outcomes. The same considerations and conclusions also apply to non-continuous outcomes and more complex models such as regression. In general, post hoc power analyses do not provide sensible results.”

Responses to Comments

Page 3

What does this mean?

This should be tertiary status which is defined in the Methods section.

Page 4

Requires a space between “We” and “defined”

This has been inserted.

What is the rationale for derivation of these ICU-level variables? Wouldn’t ICU staffing also be relevant? For instance—full-versus part-time intensivist staffing; physician versus advanced practice provider staffing; trainee presence; number of patients per intensivist, etc.

We selected these variables based on availability and relevance to Australia and New Zealand Intensive Care practice. All ICUs included in the trial in Australia and New Zealand are staffed by specialist Intensivists on-site during the day and on-call at night with on-site trainee presence all 24 hours. There are no advanced practice providers or nurse practitioners in ANZ ICUs. The seniority of trainee presence (i.e. basic trainee, advanced trainee, fellow) is determined by the College of Intensive Care Medicine Level as described earlier in the Methods section. The number pf patients looked after by intensivists in ANZ follow the recommended CICM guidelines as these sites are accredited by the CICM for the purpose of training. We chose volume of admissions as a marker of ICU size, and the other variables selected were resourcing variables that have a direct link to research i.e. availability of research coordinators, director of research etc.

Page 5

Percentage?

Yes. This has been changed.

Page 6

Please provide more detail pertaining to the rationale of this speculation.

Yes. We have now provided this detail in the preceding paragraph.

Need a space between “of” and equipoise.

This sentence has been removed.

Page 7

Need space between “but” and “have”

This has been inserted.

If the study is underpowered, please explain why the conclusions are valid.

Thanks. We have added further to the paragraph to explain that the findings are exploratory but also why they hold validity.

Please define this.

We have shortened the sentence for clarity.

Page 8

Need a space between “on” and “enrollment”

This has been inserted.

Attachment

Submitted filename: Responses to reviewers.docx

Click here for additional data file. (17.9KB, docx)

Decision Letter 1

Linda L Maerz

15 Jul 2021

An evaluation of factors that may influence clinicians’ decisions not to enrol eligible patients into randomized trials in critical care.

PONE-D-21-04343R1

Dear Dr. Ramanan,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Acceptance letter

Linda L Maerz

19 Jul 2021

PONE-D-21-04343R1

An evaluation of factors that may influence clinicians’ decisions not to enroll eligible patients  into randomized trials in critical care.

Dear Dr. Ramanan:

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on behalf of

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Academic Editor

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Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 File. List of participating sites.

    (PDF)

    Click here for additional data file. (216.3KB, pdf)
    Attachment

    Submitted filename: PONE-D-21-04343-1 [suggeted edits].docx

    Click here for additional data file. (55.1KB, docx)
    Attachment

    Submitted filename: Responses to reviewers.docx

    Click here for additional data file. (17.9KB, docx)

    Data Availability Statement

    Data can be made available on request pending approvals from the relevant Institutional Review Board, the Management Committee of the Australia New Zealand Intensive Care Society Centre for Outcomes and Resource Evaluation (as outlined here: https://www.anzics.com.au/data-access-and-publication-policy/), and The George Institute for Global Health (as outlined here: https://www.georgeinstitute.org/data-sharing-policy)

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