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Record W1990596082 · doi:10.5430/jha.v4n1p57

The data and safety monitoring board in sponsored pediatric clinical trials: practical applications

2015· article· en· W1990596082 on OpenAlexvenueno aff
Pramod M. Lad, Rebecca M. Dahl

Bibliographic record

VenueJournal of Hospital Administration · 2015
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical studies and practices
Canadian institutionsnot available
Fundersnot available
KeywordsInstitutional review boardMedicineClinical trialData monitoring committeeSafety monitoringMedical physicsInternal medicineSurgeryBioinformatics

Abstract

fetched live from OpenAlex

The Data and Safety Monitoring Board (DSMB) monitors the progress of clinical trials for safety and implements stopping rules as needed. Although NIH and FDA guidelines recommend the use of a DSMB for phase I, II, and III pediatric clinical trials, the manner in which the DSMB is constituted has received little attention. In this study we reviewed the Institutional Review Board (IRB) applications submitted between 2008 and 2012 at our institution (Children’s Hospital Los Angeles) for phase I, II and III studies which were multi-site, sponsored and performed under a sponsor’s Investigation New Drug Application (IND) for the type of data and safety monitoring that was being used. Our results indicate that approximately two-third of the studies used an independent DSMB, 10% utilized a sponsor’s DSMB and the remaining studies (25%) did not utilize a DSMB and relied instead on safety monitoring by the Principal Investigator (PI) and the medical monitor/director. This pattern was observed across all study phases and for blinded as well as unblinded studies. Our result suggests that a Data and Safety Monitoring Plan (DSMP), although required by the IRB, is rarely submitted by the sponsor at the time of application. Instead the DSMP is submitted to the IRB by the PI on IRB supplied templates. IRB review of these completed templates were critical to ensuring DSMB related compliance. Additionally, a significant percent of sponsored clinical trials used the PI or an individual designated as medical director/monitor, rather than constituting a DSMB.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.343
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.375
GPT teacher head0.559
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2015
Admission routes1
Has abstractyes

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