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Record W4294266603 · doi:10.1056/evidoa2200092

A Randomized Trial of PHOTOdynamic Surgery in Non–Muscle-Invasive Bladder Cancer

2022· article· en· W4294266603 on OpenAlexaff
Rakesh Heer, Rebecca Lewis, Thenmalar Vadiveloo, Ge Yu, Paramananthan Mariappan, Joanne Cresswell, John McGrath, Ghulam Nabi, Hugh Mostafid, Henry Lazarowicz, John D. Kelly, Anne Duncan, Steven Penegar, Matt Breckons, Laura Wilson, Emma Clark, Giovany Orozco-Leal, Zafer Tandoğdu, Ernest Taylor, James N’Dow, John Norrie, Craig Ramsay, Stephen Rice, Luke Vale, Graeme MacLennan, Emma Hall

Bibliographic record

VenueNEJM Evidence · 2022
Typearticle
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsInstitute of Cancer Research
FundersNational Institute for Health and Care Research
KeywordsMedicineBladder cancerHazard ratioConfidence intervalRandomized controlled trialCystectomyAdverse effectSurgeryCancerUrologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Recurrence of non–muscle-invasive bladder cancer (NMIBC) is common after transurethral resection of bladder tumor (TURBT). Photodynamic diagnosis (PDD) provides better diagnostic accuracy and more complete tumor resection and may reduce recurrence. However, there is limited evidence on the longer-term clinical effectiveness and cost-effectiveness of PDD-guided resection. METHODS: In this pragmatic, open-label, parallel-group randomized trial conducted in 22 U.K. National Health Service hospitals, we recruited participants with a suspected first diagnosis of NMIBC at intermediate or high risk for recurrence on the basis of routine visual assessment before being listed for TURBT. Participants were assigned (1:1) to PDD-guided TURBT or to standard white light (WL)–guided TURBT. The primary clinical outcome was time to recurrence at 3 years of follow-up, analyzed by modified intention to treat. RESULTS: A total of 538 participants were enrolled (269 in each group), and 112 participants without histologic confirmation of NMIBC or who had had cystectomy were excluded. After 44 months’ median follow-up, 86 of 209 in the PDD group and 84 of 217 in the WL group had recurrences. The hazard ratio for recurrence was 0.94 (95% confidence interval [CI], 0.69 to 1.28; P=0.70). Three-year recurrence-free rates were 57.8% (95% CI, 50.7 to 64.2) and 61.6% (95% CI, 54.7 to 67.8) in the PDD and WL groups, respectively, with an absolute difference of −3.8 percentage points (95% CI, −13.37 to 5.59) favoring PDD. Adverse events occurred in less than 2% of participants, and rates were similar in both groups, as was health-related quality of life. PDD-guided TURBT was £876 (95% CI, −766 to 2518; P=0.591) more costly than WL-guided TURBT over a 3-year follow-up, with no evidence of a difference in quality-adjusted life years (−0.007; 95% CI, −0.133 to 0.119; P=0.444). CONCLUSIONS: PDD-guided TURBT did not reduce recurrence rates, nor was it cost-effective compared with WL at 3 years. (Funded by the National Institute for Health and Care Research Health Technology Assessment program; ISRCTN number, ISRCTN84013636.)

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)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0100.001

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 head0.043
GPT teacher head0.331
Teacher spread0.288 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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

Citations59
Published2022
Admission routes1
Has abstractyes

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