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Long-term outcomes of adolescents and young adults with testicular germ cell tumors: A population-based retrospective matched cohort study.

2023· article· en· W4379283217 on OpenAlexafffundabout
Rand Ajaj, Cindy Lau, Sumit Gupta, Nancy N. Baxter, Furqan Shaikh, Paul C. Nathan

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicTesticular diseases and treatments
Canadian institutionsInstitute for Clinical Evaluative SciencesSickKids FoundationHospital for Sick Children
FundersCanadian Institutes of Health Research
KeywordsMedicineHazard ratioInterquartile rangePopulationCumulative incidenceInternal medicineRetrospective cohort studyProportional hazards modelGerm cell tumorsCohortSurgeryChemotherapyConfidence interval

Abstract

fetched live from OpenAlex

12016 Background: Testicular germ cell tumor (TGCT) survival exceeds 90%, but survivors of adult TGCT are at risk of developing late effects. Little is known about the risk for late effects in survivors of TGCT in children, adolescents, or young adults (CAYA). Methods: We identified all CAYA aged 11-21 years at TGCT diagnosis in Ontario, Canada, between 1992-2021. Those with complete treatment records were matched 1:5 by birth date and postal code at diagnosis to individuals from the general population (controls). Controls’ index date was defined as the diagnosis date of their survivor match. Participants were linked to health administrative databases to identify second malignant neoplasms (SMN); cardiovascular disease (CVD: congestive heart failure [CHF], myocardial infarction, coronary artery disease, pericardial disease, valvular abnormalities, arrhythmia, stroke, hypertension); renal disease (dialysis, kidney transplant); and hearing loss (physician-diagnosed hearing loss, hearing aid use). Cumulative incidences were compared between survivors and controls, and between chemotherapy and surgery treated survivors using Gray’s test. Cox proportional hazard models compared the risk of late effects between survivors and controls. Results: 521 TGCT survivors (296 chemotherapy treated, 225 treated with surgery only) were matched to 2605 controls. Median age at diagnosis/index date was 19 years. Survivors’ median follow-up time was 14.8 years (interquartile range: 10.7-21.7). Compared to controls, survivors had higher 15-year incidence and hazard ratio (HR) of all SMN (5.0% vs 0.5%; HR 8.4, p < .0001), non-testicular SMN (2.1% vs 0.5%; HR 3.8, p = 0.0003), dialysis (1.0% vs 0.04%; HR 12.4, p = 0.003), kidney transplant (0.4% vs 0.0%, p = 0.002), hearing loss (7.1% vs 3.1%; HR 1.8, p = 0.005), and hearing aid use (1.0% vs 0.2%; HR 4.1, p = 0.02). Survivors were at substantially increased risk of any CVD (8.2% vs 5.5%; HR 1.4, p < 0.03), CHF (1.2% vs. 0.2%; HR 5.0, p = 0.006), arrhythmia (1.8% vs 0.5%; HR 3.4, p = 0.002), and stroke (0.8% vs 0.05%; HR 8.7, p = 0.0006) despite no anthracycline exposure. Compared to surgery only treated survivors, chemotherapy treated survivors had higher 15-year incidence of any CVD (13.1% vs 2.0%, p < 0.0001), CHF (2.1% vs 0.0%, p = 0.03), arrhythmia (3.3% vs 0.0%, p = 0.02), stroke (1.4% vs 0.0%, p = 0.02), hypertension (7.4% vs 2.0%, p = 0.009), and hearing loss (10.2% vs 3.0%, p = 0.02). Conclusions: Survivors of TGCT during CAYA are at considerable risk for late effects affecting multiple organ systems. In addition to previously described morbidities like hearing loss, survivors (particularly those who received chemotherapy) are at higher risk of CVD. Despite excellent rates of cure, TGCT survivors diagnosed at a young age require life-long risk-directed follow-up to maximize their long-term health.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.160
Threshold uncertainty score0.318

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
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 head0.039
GPT teacher head0.401
Teacher spread0.362 · 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
Published2023
Admission routes3
Has abstractyes

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