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Stockholm3 validation in a multi-ethnic cohort for prostate cancer (SEPTA) detection: A multicentered, prospective trial.

2024· article· en· W4391303212 on OpenAlexaff
Hari T. Vigneswaran, Martin Eklund, Andrea Discacciati, Tobias Nordström, Rebecca A. Hubbard, Nathan Perlis, Michael R. Abern, Daniel M. Moreira, Scott E. Eggener, Paul Yonover, Alexander K. Chow, Kara Watts, Michael A. Liss, Gregory R. Thoreson, Andre Luis Abreu, Geoffrey A. Sonn, Thorgerdur Palsdottir, Fredrik Wiklund, Henrik Grönberg, Adam B. Murphy

Bibliographic record

VenueJournal of Clinical Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicRadiomics and Machine Learning in Medical Imaging
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
FundersVetenskapsrådet
KeywordsMedicineProstate cancerProspective cohort studyCohortCancerProstateOncologyGynecologyInternal medicine

Abstract

fetched live from OpenAlex

262 Background: Stockholm3 is a multiparametric blood test incorporating germline risk, proteins and clinical data which improves prostate cancer (PC) risk stratification compared to PSA, however no validation exists in an ethnically diverse population. Methods: SEPTA is a prospective trial (NCT04583072) aimed to validate Stockholm3 in an ethnically diverse cohort of men referred for prostate biopsy at 17 North American sites from 2019 to 2023 (supplemented with bio-banked specimens 2008-2020). The trial had two prespecified primary aims when comparing Stockholm3 (≥15) compared to PSA (≥4 ng/ml): (1) Demonstrate non-inferior sensitivity in detecting clinically significant PC (csPC) (defined as ISUP Gleason Grade group ≥2) compared to PSA (non-inferiority margin of 20%). (2) Prove superior specificity thereby reducing the number of biopsies compared to PSA in men with benign or ISUP 1 biopsies. Both aims were assessed using a one-sided alpha of 0.025. A secondary aim was to evaluate Stockholm3 and PSA across ethnic subgroups. Statistical analysis plans were published before the analysis commenced. Results: The study involved 2,129 biopsied participants, categorized into self-identified groups: African American/Black (24%), White/Caucasian (46%), Hispanic/Latino (14%), and Asian (16%). Median participant age was 63 years. PSA and Stockholm3 median values were 6.1 ng/mL and 17, respectively. A total of 16% underwent MRI-targeted biopsies and 20% had a prior benign biopsy. On either systematic or targeted biopsy, csPC was found in 29%, 14% had ISUP 1 cancer, and 57% benign. The detection rate for csPC across groups were: African American/Black (37%), White/Caucasian (28%), Hispanic/Latino (29%), and Asian (21%). Overall, Stockholm3≥15 showed non-inferior sensitivity compared to PSA≥4 ng/ml (relative sensitivity: 0.95 [95% CI: 0.92-0.99]) and nearly 3 times superior specificity (relative specificity: 2.91 [95% CI: 2.63-3.22]). Results were consistent across ethnic subgroups: non-inferior sensitivity (0.91-0.98) and superior specificity (2.51-4.70). Stockholm3 ≥15 would have reduced benign and ISUP 1 biopsies by 45% overall and between 42-52% across ethnic subgroups compared to PSA ≥4 ng/ml. Stockholm3 exhibited higher AUC (0.82) compared to PSA (0.66), with similar trends in ethnic subgroups. Conclusions: In an ethnically diverse population, Stockholm3 would significantly reduce unnecessary prostate biopsies and diagnosis of ISUP 1 cancer at a similar sensitivity of PSA for detecting clinically significant cancer. Clinical trial information: NCT04583072 . [Table: see text]

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)0.006
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.860
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.144
GPT teacher head0.540
Teacher spread0.396 · 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 designOther design
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

Citations6
Published2024
Admission routes1
Has abstractyes

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