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Record W7132970046

Opportunistic Genomic Screening for a Broad Range of Medically Relevant Secondary Findings: Molecular Findings, Clinical Utility, and Cost-Effectiveness

2024· dissertation· W7132970046 on OpenAlexafffund
Chloe Elizabeth Mighton

Bibliographic record

VenueTSpace · 2024
Typedissertation
Language
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsInstitute of Health Services and Policy Research
FundersCanadian Cancer Society Research InstituteCanadian Institutes of Health Research
KeywordsExome sequencingExomePharmacogenomicsGenomicsRandomized controlled trialPrecision medicineIntervention (counseling)Clinical trial
DOInot available

Abstract

fetched live from OpenAlex

Background: When used as a diagnostic test, genomic sequencing can also be used to opportunistically screen for secondary findings (SFs) – medically relevant variants that are unrelated to the primary indication for testing. However, there is scarce evidence on the outcomes or costs of screening for SFs to inform decisions about whether, and which, secondary findings should be offered to patients. Through a randomized controlled trial (Incidental Genomics RCT; NCT03597165) we aimed to evaluate the clinical, economic, and laboratory outcomes of opportunistic screening for a broad range of medically relevant SFs, encompassing risks for medically actionable and non-medically actionable monogenic disorders, carrier status for recessive disorders, pharmacogenomic variants, and risk variants for common multifactorial disease.Methods: Adult cancer patients received germline exome sequencing with primary cancer findings only (control arm), or primary cancer findings and a choice of secondary findings (intervention arm). Through a chart review and patient-reported outcomes, the yield of reportable secondary findings was characterized, as well as the impact on patients’ medical management and correlations with clinical features and family history. Data from the RCT were linked to healthcare administrative databases, and cost-utility and cost-effectiveness analyses were performed. Laboratory exome analysis logs were analyzed to characterize all variants requiring manual curation, and the resources required for exome analysis. The time horizon for all analyses was the first year after return of exome sequencing results. Results: From the diagnostic laboratory perspective, analyzing all types of secondary findings required substantial effort. Across all intervention arm participants, in the monogenic secondary finding genes there were 4,441 unique variants, 5.0% (221) of which were classified as P/LP and were reportable, and 81.4% (3615) were classified as VUS and not reportable. There were on average 2.6 (SD 1.66, range 0-9) P/LP variants per case in the intervention arm, and 29.5 VUS (SD 13.2, range 2-74). Filtration, variant classification and report generation were substantially more time consuming in the intervention arm compared to the control arm given the greater number of variants being analyzed. All participants who elected to learn SFs had ≥1 variant reported (100% [139/139]). SFs across all categories prompted changes in management among 28.1% of participants, including SFs not a priori categorized as medically actionable. Moreover, a considerable proportion of participants had suggestive clinical features (49.0% [24/49]) or family history (21.7% [27/124]) potentially related to their SFs. Overall costs (costs associated with genomic sequencing, plus downstream healthcare costs) were on average $1290CAD higher per participant in the intervention arm, at $12,965 (SD$20,038) in the intervention arm compared to $11,676 (SD$21,776) in the control arm. However, we did not find strong evidence that these were statistically different (ratio of geometric means: 1.27, 95% CI 0.98 to 1.65, p=0.0652). QALYs were higher for participants in the intervention arm than in the control arm (β=0.04, 95% CI 0.01-0.06, p=0.005), and the odds of having a GS-informed change in management were substantially higher among participants in the intervention arm compared to the control arm (OR 11.2, 95% CI 4.3 to 29.5, p<0.0001). The ICER was $34,929CAD/QALY, falling below commonly accepted cost-effectiveness thresholds. Conclusions: This thesis provides evidence on the laboratory, clinical and health system outcomes of opportunistic screening for a broad range of secondary findings. While secondary findings were associated with higher costs, these may be justified in light of the associated benefits, namely, clinical utility and quality of life.

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)0.012
metaresearch head score (Gemma)0.020
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 score0.012
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.020
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.045
GPT teacher head0.386
Teacher spread0.341 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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