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Record W3006195141 · doi:10.1681/asn.2019090889

Authors’ Reply

2019· letter· en· W3006195141 on OpenAlexaff
Germaine Wong, Richard L. Hope, Kirsten Howard, Jeremy R. Chapman, Antoni Castells, Simon D. Roger, Michael J. Bourke, Petra Macaskill, Robin Turner, Gabrielle Williams, Wai H. Lim, Charmaine E. Lok, Fritz Diekman, Nicholas C.P. Cross, Shaundeep Sen, Richard D. Allen, Steven J. Chadban, Carol A. Pollock, Allison Tong, Armando Teixeira‐Pinto, Jean Yang, Narelle Williams, Eric Au, Anh Kieu, Laura James, Jonathan C. Craig

Bibliographic record

VenueJournal of the American Society of Nephrology · 2019
Typeletter
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineColonoscopyTest (biology)Colorectal cancer screeningColorectal cancerPopulationGold standard (test)Internal medicineGastroenterologySurgeryCancer

Abstract

fetched live from OpenAlex

We appreciate the interest shown by Collins et al.1 in our study of screening advanced colorectal neoplasia in people with CKD (DETECT). They assert that the performance characteristics of fecal immunochemical testing (FIT) arising from our study are unreliable because of verification bias and that high false positive rates were found due to low test thresholds.1 We note that the authors have conducted a similar study but found lower test-positive and sensitivity values.2 The observed differences in the test estimates are not unexpected. Their study was conducted in a single center, restricted only to transplant recipients, and of smaller sample size. A quantitative FIT (Eiken OC-Sensor) was the chosen screening tool for DETECT, because it is the screening test of choice by the National Bowel Cancer Screening program in Australia and Spain, rather than the InSure FIT (brush techniques) used by Collins et al.1 Prior studies have also indicated lower positivity rates and sensitivity estimates for advanced colorectal neoplasia with the InSure FIT compared with the Eiken OC-Sensor FIT in the general population.3,4 We suggest that the two-step reference standard (colonoscopy for FIT-positive patients and clinical follow-up for both FIT-positive and FIT-negative patients) is in fact the correct one and not colonoscopy for all for three reasons. First, given the appreciable risk of colonoscopy in potentially high-risk patients, we could not ethically justify subjecting FIT-negative patients to an unnecessary procedure. Second, what Collins et al.1 have not considered is the potential for overdiagnosis. We acknowledge that this has only been recognized as a major issue recently, postdating their publication in 2012. Overdiagnosis occurs when the disease detected through screening does not cause morbidity and/or death.5 This is an important concept to consider, particularly in patients with limited life expectancy, such as those with CKD, and when competing events, such as cardiovascular diseases, predominate as the major cause of death. Overdiagnosis, the downside of cancer screening, will trigger a sequence of overtreatment, with the attendant adverse events and without benefit, because the screened individual will never experience the health consequences of the target condition. We anticipated that the harms associated with diagnostic colonoscopies are likely to be higher among those with CKD and thus, limit the benefits of routine screening. Our findings confirmed that colonoscopies and subsequent treatments, including polypectomy, incurred at least a 10-fold increased risk of major complications, including perforations and infections, in patients with CKD compared with those reported in the general population. Third, our two-step process is clinically feasible and allows for external generalizability. In our study, a follow-up of 2 years was chosen to ensure that all clinically relevant colorectal cancers had enough time to progress to a detectable stage and that new (interval) cancers that develop after the index test (FIT) were also being detected. Importantly, only 14 additional patients (0.9%) were diagnosed with advanced colorectal neoplasia at the end of the 2-year follow-up, indicating that, even if differential verification bias may exist in theory, it is unlikely to be clinically relevant.

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)0.007
metaresearch head score (Gemma)0.109
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.034
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.109
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0050.006
Open science0.0030.004
Research integrity0.0240.033
Insufficient payload (model declined to judge)0.0340.022

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 head0.022
GPT teacher head0.287
Teacher spread0.265 · 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 designNot applicable
Domainnot available
GenreCommentary

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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Citations2
Published2019
Admission routes1
Has abstractyes

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