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Record W2582390665 · doi:10.1182/blood.v110.11.369.369

Treatment Decisions for Young Women with Supra-Diaphragmatic, Limited-Stage Hodgkin Lymphoma: Exploration of Options Using a Markov Decision Analysis.

2007· article· en· W2582390665 on OpenAlexaff
Lisa K. Hicks, Rebecca Dent, Ralph M. Meyer, David Naimark

Bibliographic record

VenueBlood · 2007
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsQueen's UniversityHealth Sciences CentreSunnybrook Health Science CentreUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsABVDMedicineOncologyRadiation therapyBreast cancerInternal medicineStage (stratigraphy)Relative riskSurgeryCancerChemotherapyCyclophosphamide

Abstract

fetched live from OpenAlex

Abstract Background: Treatment decisions for patients with limited-stage Hodgkin lymphoma (HL) involve trade-offs between combined modality therapy (CMT), which includes involved field radiation therapy (IFRT), versus ABVD alone. While CMT is associated with superior disease control, these gains must be balanced against late-effects associated with radiation, including a long-term increased risk of solid cancers. This balance may be particularly important for young women in whom IFRT would include portions of the breast, and in whom substantially increased relative risks (RR) of breast cancer have been reported. The use of a Markov decision model (MDM) may assist in evaluating the principles of this trade-off. Methods: We developed a MDM to explore which strategy, CMT or ABVD alone, maximizes life expectancy among young women with limited-stage HL involving supraclavicular, axillary, and/or mediastinal adenopathy and whose IFRT would therefore include portions of the breast. Three base cases assessing women ages 20, 30 and 40 years at the time of HL diagnosis were evaluated. Published data on the RR of breast and other cancers following HL treatment, the risk of HL relapse with CMT and ABVD alone, expected survival with breast and other cancers, the risk of relapse following salvage HL therapy, the risk of leukemia after salvage HL therapy, and expected survival with secondary leukemia were used to populate the model. The RR of breast and other solid cancers was assumed to be negligible for the first 10 years after treatment and constant thereafter. The risk of HL relapse was assumed to be constant during the first five years post-treatment, and substantially lower thereafter. Uncertainty in critical variables was explored with deterministic sensitivity analysis. Results: In our model, women age 20, 30, and 40 years at the time of HL diagnosis have a life expectancy of 56.1, 64.1, and 70.1 years with CMT, and 62.5, 66.1, and 69.9 years with chemotherapy alone. For women age 40 years at HL diagnosis, CMT was the favored strategy at all time points. For younger women, ABVD alone maximized life expectancy, but this benefit was manifest only > 20 years after HL diagnosis. Our model was robust in one-way sensitivity analyses across a plausible range of critical variables. In two-way analyses, the model was sensitive to extreme values for the relative risk of breast cancer post-CMT, the relative risk of other cancer post-CMT, and the risk of HL relapse following ABVD alone. Conclusions: The optimum treatment strategy for young women with limited-stage, supra-diaphragmatic HL is likely influenced by age at diagnosis. Use of a MDM may assist in evaluating the trade-offs associated with current treatment options.

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)0.006
metaresearch head score (Gemma)0.010
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.309
Teacher spread0.270 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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