Study Design and Interim Analysis of the Cancer Lifetime Assessment Screening Study in Canines (CLASSiC): The First Prospective Cancer Screening Study in Dogs Using Next-Generation Sequencing-Based Liquid Biopsy
Bibliographic record
Abstract
ABSTRACT Objective The Cancer Lifetime Assessment Screening Study in Canines (CLASSiC) is a prospective, longitudinal cancer screening study, in which enrolled dogs are screened for cancer with physical exams and next-generation sequencing-based liquid biopsy testing on a serial basis. The goals of the first interim analysis, presented here, are to assess the benefits of using the OncoK9® liquid biopsy test as a cancer screening tool in a prospective clinical setting, and to demonstrate test performance for cancer detection, including preclinical detection. Subjects 726 presumably cancer-free client-owned dogs were prospectively enrolled in the study across 24 clinical sites in the US and Canada. Most subjects were at high risk of cancer at the time of enrollment based on age and/or breed. 419 dogs that were enrolled for at least one year and had at least two cancer screening study visits, or that had received a definitive or presumptive diagnosis of cancer up to the time of the interim analysis, were included in the analysis. Methods Clinical data and a blood sample were collected at each study visit (once or twice per year and when cancer was clinically suspected). Cell-free DNA extracted from plasma was tested by OncoK9® using next-generation sequencing (NGS) technology. Results 417 dogs were eligible for inclusion in the interim analysis and had classifiable outcomes, with a mean on-study duration of 422 days. Of these, 51 dogs were newly diagnosed with cancer (37 definitive, 14 presumptive), translating to a 12% (51/417) observed incidence over the study period; the liver, skin, bone, heart, spleen, lung, and lymph node(s) were the most common anatomic locations for disease. The prospectively observed sensitivity (detection rate) of the test was 56.9% (95% CI: 42.3-70.4%) with a specificity of 98.9% (95% CI: 97.0-99.6%). The prospectively observed positive predictive value was 87.9% (95% CI: 70.9-96.0%) and the negative predictive value was 94.3% (95% CI: 91.3-96.3%). NGS-based liquid biopsy doubled the overall number of cancer cases detected in this study population (from 25 to 51); remarkably, the detection rate for preclinical cancer was increased 4.6-fold from 12% (6/51) by routine care alone to 55% (28/51) by combining routine care with OncoK9® testing. Clinical Relevance CLASSiC is the first study to prospectively document the incidence of cancer in a predominantly high-risk canine population, and to prospectively demonstrate that the addition of NGS-based cancer screening to regularly scheduled wellness visits has the potential to substantially increase preclinical cancer detection in this population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".