MétaCan
Menu
Back to cohort

Longitudinal evaluation of plasma miR371 to detect minimal residual disease and early relapse of germ cell tumors.

2023· article· en· W4324136672 on OpenAlexaff
Lucia Nappi, Neetu Saxena, Sara Pautasso, Sylwia Mazurek, Güliz Özgün, Catarina Kollmannsberger, Antoine Morin Coulombe, Maryam Soleimani, Kim N., Bernhard J. Eigl, Peter C. Black, Alan So, Martin Gleave, Sean Q. Kern, Siamak Daneshmand, Nabil Adra, Lawrence H. Einhorn, Craig R. Nichols, Christian Kollmannsberger

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicTesticular diseases and treatments
Canadian institutionsBC Cancer AgencyUniversity of British Columbia
Fundersnot available
KeywordsMedicineOrchiectomyStage (stratigraphy)Internal medicineBiomarkerTesticular cancerMinimal residual diseaseGerm cell tumorsLog-rank testOncologyExact testGastroenterologySurvival analysisSurgeryCancerChemotherapy

Abstract

fetched live from OpenAlex

407 Background: Active surveillance is routinely recommended to manage patients (pts) with clinical stage I (CSI) germ cell testicular tumors (GCT), the most common presentation of newly diagnosed GCT. Circulating plasma miR371a-3p (miR371) has shown high sensitivity and specificity in pts with metastatic non teratoma GCT or in pts with clinically detectable testicular GCT prior to orchiectomy. However, limited data are available about this biomarker accuracy to detect minimal residual disease post-orchiectomy in pts on active surveillance for early stage disease. Methods: CSI GCT pts with available plasma samples after radical orchiectomy enrolled in the British Columbia provincial biobank research program were selected for this study. RT-PCR was used for qualitative miR371 analysis. Sensitivity, specificity, negative and positive predictive values (NPV, PPV) and AUC in predicting tumor recurrence were evaluated for miR371 and compared to the same operating characteristics of current gold standard diagnostic tests. Relapse free survival (RFS) was correlated to post-orchiectomy miR371 (positive or negative) status. Fisher’s exact test was used to evaluate the sensitivity and specificity, unpaired t-test for comparison of miR371 expression. RFS was calculated using the Kaplan-Meier method, and differences between groups were estimated using the log rank test, 2-sided and with 5% significance threshold. Results: With a median follow-up of 41 months, 101 pts with CSI GTCwere included, of whom 35 (34.6%) experienced a disease relapse during the follow-up. miR371 was positive in 22/35 (62.8%) of the relapsed pts. miR371 positivity preceded clinical evident disease by a median of 3 months (range: 1-12 months).The specificity and PPV were 100% (95% CI: 94.5 - 100 for both), sensitivity 62.8% (95% CI: 44.9 - 78.5), NPV 83.5% (95% CI: 76.7 - 88.6) and AUC 0.81 (95% CI: 0.71 - 0.91). No false positive results were observed. The RFS of the pts with positive post-orchiectomy miR371 was significantly shorter (median: 3.5 months vs. not reached; p<0.0001) compared to the pts with a negative post-orchiectomy miR371 (HR: 16.9; 95% CI: 2.1 - 135.7; p<0.0001). miR371 sensitivity correlated with tumor burden, time between tumor relapse and miRNA testing and histology (nonseminoma > seminoma). Conclusions: miR371 has high specificity and PPV in detecting GCT at an early stage and could be used to guide treatment selection after orchiectomy. Further studies, including the SWOG S1823 clinical trial, are ongoing or have been planned in this setting for validation of clinical utility.

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)0.001
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.157
GPT teacher head0.471
Teacher spread0.313 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Clinical OncologySame topicTesticular diseases and treatmentsFrench-language works237,207