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Lifelong disease burden of chemotherapy in Hodgkin lymphoma (HL): A simulation study from the St. Jude Lifetime (SJLIFE) Cohort and HL International Study for Individual Care (HoLISTIC).

2020· article· en· W3028917365 on OpenAlexaff
Susan K. Parsons, Nickhill Bhakta, Angie Mae Rodday, Carlton Scharman, Marc André, Massimo Federico, Jonathan W. Friedberg, Debra L. Friedman, Andrea Gallamini, Annette E. Hay, Brad S. Kahl, Frank G. Keller, Kara M. Kelly, Ralph M. Meyer, John Raemaekers, Leslie L. Robison, Melissa M. Hudson, Joshua T. Cohen, Andrew M. Evens, F. Lennie Wong

Bibliographic record

VenueJournal of Clinical Oncology · 2020
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsJuravinski HospitalQueen's University
Fundersnot available
KeywordsMedicineCohortLife expectancyInternal medicinePopulationMicrosimulationCohort studyPediatricsOncologyEnvironmental health

Abstract

fetched live from OpenAlex

12068 Background: Current emphasis for childhood and young adults with HL is to maintain high cure rates while concurrently identifying regimens to reduce excess long-term mortality/morbidity. Thus, understanding the late effects (LE) of contemporary clinical trials (CCT) for HL is critical. Methods: We used simulation to estimate the projected life expectancy (LExp), quality adjusted life-expectancy (QALE) & cause of death (COD) in a large cohort of HL CCT patients (pts) in the recently established HoLISTIC consortium by linking long-term risk models from the SJLIFE cohort. Individual patient data (IPD) on bleomycin, alkylating agents and anthracycline were extracted & harmonized for 982 HL pts in 5 prospective CCT (mean diagnosis age 19y, range 3-30y; 51% male; all treated with chemotherapy only; progression-free survival [PFS] >5y) in the HoLISTIC database. LExp, QALE & COD were projected using a previously developed microsimulation model (Bhakta, Blood [Supplement], 2019) that incorporated mortality & incidence of LEs by diagnosis age, sex, race, treatment exposures & attained age estimated from 5,522 adult 10-y survivors of childhood cancers in the SJLIFE cohort (56% male; mean age at last follow-up 35y, range 19-68). Microsimulation was applied to 10,000 randomly selected survivors of HL CCT cohort, from 10y after HL diagnosis until death to project the LExp, QALE & COD. Results: Assuming 10-y PFS, LExp and QALEs projected for the HL CCT cohort using adjusted US general population rates linked with the SJLIFE microsimulation model, COD and trial-specific exposures are shown in the Table. Conclusions: A novel lifetime simulation approach was used to project LExp, QALE & COD by linking together IPD from CCTs with the long-term risk model of the SJLIFE survivorship cohort. Despite differences in PFS, reflecting in part the variation in risk/stage status, the projected long-term outcomes were similar. Our approach highlights a new opportunity to inform future clinical trial design and aid provider & patient decision-making. [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 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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.129
GPT teacher head0.471
Teacher spread0.342 · 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 designSimulation or modeling
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

Citations2
Published2020
Admission routes1
Has abstractyes

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