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Comparison of the Harms, Advantages, and Costs Associated With Alternative Guidelines for the Evaluation of Hematuria

2019· article· en· W2964930251 on OpenAlexaboutno aff
Mihaela Georgieva, Stephanie B. Wheeler, Daniel Erim, Rebecca Smith‐Bindman, Ronald K. Loo, Casey K. Ng, Tullika Garg, Mathew Raynor, Matthew E. Nielsen

Bibliographic record

VenueJAMA Internal Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCystoscopyCohortUrinary systemPyelogramCohort studyRadiologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

IMPORTANCE: Existing recommendations for the diagnostic testing of hematuria range from uniform evaluation of varying intensity to patient-level risk stratification. Concerns have been raised about not only the costs and advantages of computed tomography (CT) scans but also the potential harms of CT radiation exposure. OBJECTIVE: To compare the advantages, harms, and costs associated with 5 guidelines for hematuria evaluation. DESIGN, SETTING, AND PARTICIPANTS: A microsimulation model was developed to assess each of the following guidelines (listed in order of increasing intensity) for initial evaluation of hematuria: Dutch, Canadian Urological Association (CUA), Kaiser Permanente (KP), Hematuria Risk Index (HRI), and American Urological Association (AUA). Participants comprised a hypothetical cohort of patients (n = 100 000) with hematuria aged 35 years or older. This study was conducted from August 2017 through November 2018. EXPOSURES: Under the Dutch and CUA guidelines, patients received cystoscopy and ultrasonography if they were 50 years or older (Dutch) or 40 years or older (CUA). Under the KP and HRI guidelines, patients received different combinations of cystoscopy, ultrasonography, and CT urography or no evaluation on the basis of risk factors. Under the AUA guidelines, all patients 35 years or older received cystoscopy and CT urography. MAIN OUTCOMES AND MEASURES: Urinary tract cancer detection rates, radiation-induced secondary cancers (from CT radiation exposure), procedural complications, false-positive rates per 100 000 patients, and incremental cost per additional urinary tract cancer detected. RESULTS: The simulated cohort included 100 000 patients with hematuria, aged 35 years or older. A total of 3514 patients had urinary tract cancers (estimated prevalence, 3.5%; 95% CI, 3.0%-4.0%). The AUA guidelines missed detection for the fewest number of cancers (82 [2.3%]) compared with the detection rate of the HRI (116 [3.3%]) and KP (130 [3.7%]) guidelines. However, the simulation model projected 108 (95% CI, 34-201) radiation-induced cancers under the KP guidelines, 136 (95% CI, 62-229) under the HRI guidelines, and 575 (95% CI, 184-1069) under the AUA guidelines per 100 000 patients. The CUA and Dutch guidelines missed detection for a larger number of cancers (172 [4.9%] and 251 [7.1%]) but had 0 radiation-induced secondary cancers. The AUA guidelines cost approximately double the other 4 guidelines ($939/person vs $443/person for Dutch guidelines), with an incremental cost of $1 034 374 per urinary tract cancer detected compared with that of the HRI guidelines. CONCLUSIONS AND RELEVANCE: In this simulation study, uniform CT imaging for patients with hematuria was associated with increased costs and harms of secondary cancers, procedural complications, and false positives, with only a marginal increase in cancer detection. Risk stratification may optimize the balance of advantages, harms, and costs of CT.

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)0.022
metaresearch head score (Gemma)0.074
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.074
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.118
GPT teacher head0.447
Teacher spread0.330 · 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 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

Citations49
Published2019
Admission routes1
Has abstractyes

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