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The role of an open-label non-intervention design versus a placebo-control arm in oncology randomized trials.

2020· article· en· W3030620127 on OpenAlexaffabout
Igal Kushnir, Mark Clemons, Dean Fergusson, Dominick Bossé, M. Neil Reaume

Bibliographic record

VenueJournal of Clinical Oncology · 2020
Typearticle
Languageen
FieldMedicine
TopicBiomedical Ethics and Regulation
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicinePlaceboRandomized controlled trialIntervention (counseling)Clinical trialClinical endpointQuality of life (healthcare)Physical therapyAlternative medicineSurgeryInternal medicineNursing

Abstract

fetched live from OpenAlex

e14099 Background: Randomized trials are considered the gold standard when assessing the efficacy of new therapeutic agents. In settings where there is no known effective agent available, a randomised study could compare the investigational agent with either a placebo arm or an open-label non-intervention arm (i.e. best supportive care). The use of placebo arm can result in additional inconvenience and time commitments for patients, as well as increased administrative and regulatory costs. We conducted a survey among Canadian medical oncologists to assess whether an open-label non-intervention arm would be an acceptable alternative control to placebo in randomized trials. Methods: Members of the Canadian Association of Medical Oncologists were invited to participate in an anonymous online survey. Standardized case scenarios were used to determine participants’ attitudes regarding the role of open-label randomized-controlled trials instead of a placebo. Results: Eighty-six medical oncologists and trainees responded (response rate was 27%). Eighty-one (94%) of respondents worked at university-affiliated centres and 41 (48%) had been in practice for at least 10 years. Fifty-one (59%) respondents believed that it is acceptable to use an open-label design instead of a placebo arm when assessing a therapeutic agent in the adjuvant setting. Thirty-eight (49%) felt it was acceptable to compare the investigational agent to an open-label arm instead of a placebo to assess overall survival in the metastatic setting. Twenty-eight (38%) of respondents felt using an open-label design when assessing quality of life endpoints was acceptable. Most physicians (75%) were unsure whether or not the US Food and Drug Administration requires a placebo-controlled arm in cancer clinical trials. Conclusions: We report disagreement and uncertainty among Canadian medical oncologists regarding the acceptability of an open-label design in randomized-controlled trials where no standard therapy is approved. Clearer guidance from regulatory bodies on the adequacy of different trial designs could help reduce this equipoise.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.801
metaresearch head score (Gemma)0.813
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.199
Threshold uncertainty score0.246

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.8010.813
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0080.006
Bibliometrics0.0060.007
Science and technology studies0.0030.018
Scholarly communication0.0110.017
Open science0.0050.007
Research integrity0.0170.013
Insufficient payload (model declined to judge)0.0170.003

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 head0.340
GPT teacher head0.551
Teacher spread0.210 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designTheoretical or conceptual
DomainMethods
GenreMethods

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".

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Citations0
Published2020
Admission routes2
Has abstractyes

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