Evidence map›Paper›PMID 24980279›Full record

ArticleClinical trials (London, England)2014

Evaluating protocol lifecycle time intervals in HIV/AIDS clinical trials.

Scott R Rosas, Jeffrey T Schouten, Dennis Dixon, Suresh Varghese, Marie T Cope, Joe Marci, Jonathan M Kagan

Abstract read
In one paragraph

Article in Clinical trials (London, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Trial
  2. Strategy management in collaborative clinical research partnerships.Contemporary clinical trials communications · 2021
    Article
  3. Review
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Scott R RosasConcept Systems, Inc., Ithaca, NY, USA srosas@conceptsystems.com.
Jeffrey T SchoutenOffice of HIV/AIDS Network Coordination, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
Dennis DixonIndependent Consultant, Bethesda, MD, USA.
Suresh VargheseDigital Infuzion, Inc., Gaithersburg, MD, USA.
Marie T CopeConcept Systems, Inc., Ithaca, NY, USA.
Joe MarciDivision of Acquired Immunodeficiency Syndrome, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services, United States Government, Bethesda, MD, USA.
Jonathan M KaganDivision of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services, United States Government, Bethesda, MD, USA.

Funding

Leadership Group for a Global HIV Vaccine Clinical Trials NetworkU01AI068614 · NIAID · FRED HUTCHINSON CANCER RESEARCH CENTER · PI COREY, LAWRENCE · 2006 to 2010
$181.5M
NIAID NIH HHS N01 AI050022NIAID NIH HHS N01AI-50022NIAID NIH HHS U01 AI068614NIAID NIH HHS U01AI068614
6 · The paper itself

Abstract

backgroundIdentifying efficacious interventions for the prevention and treatment of human diseases depends on the efficient development and implementation of controlled clinical trials. Essential to reducing the time and burden of completing the clinical trial lifecycle is determining which aspects take the longest, delay other stages, and may lead to better resource utilization without diminishing scientific quality, safety, or the protection of human subjects. PURPOSE: In this study, we modeled time-to-event data to explore relationships between clinical trial protocol development and implementation times, as well as to identify potential correlates of prolonged development and implementation.

methodsWe obtained time interval and participant accrual data from 111 interventional clinical trials initiated between 2006 and 2011 by National Institutes of Health's HIV/AIDS Clinical Trials Networks. We determined the time (in days) required to complete defined phases of clinical trial protocol development and implementation. Kaplan-Meier estimates were used to assess the rates at which protocols reached specified terminal events, stratified by study purpose (therapeutic, prevention) and phase group (pilot/phase I, phase II, and phase III/IV). We also examined several potential correlates to prolonged development and implementation intervals.

resultsEven though phase grouping did not determine development or implementation times of either therapeutic or prevention studies, overall we observed wide variation in protocol development times. Moreover, we detected a trend toward phase III/IV therapeutic protocols exhibiting longer developmental (median 2½ years) and implementation times (>3 years). We also found that protocols exceeding the median number of days for completing the development interval had significantly longer implementation. LIMITATIONS: The use of a relatively small set of protocols may have limited our ability to detect differences across phase groupings. Some timing effects present for a specific study phase may have been masked by combining protocols into phase groupings. Presence of informative censoring, such as withdrawal of some protocols from development if they began showing signs of lost interest among investigators, complicates interpretation of Kaplan-Meier estimates. Because this study constitutes a retrospective examination over an extended period of time, it does not allow for the precise identification of relative factors impacting timing.

conclusionDelays not only increase the time and cost to complete clinical trials but they also diminish their usefulness by failing to answer research questions in time. We believe that research analyzing the time spent traversing defined intervals across the clinical trial protocol development and implementation continuum can stimulate business process analyses and re-engineering efforts that could lead to reductions in the time from clinical trial concept to results, thereby accelerating progress in clinical research.

Indexed as

Clinical ProtocolsPatient SelectionAcquired Immunodeficiency SyndromeBiomedical ResearchClinical Trials as TopicHIV InfectionsHumansKaplan-Meier EstimateNational Institute of Allergy and Infectious Diseases (U.S.)Time FactorsUnited StatesHIV/AIDS Clinical Trialsprotocol developmentprotocol implementationSurvival analysistime-based analyses

Identifiers

PMID24980279
PMCPMC4156886

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.