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Risk of Treatment-Related Stomach Cancer Among Hodgkin Lymphoma Survivors

2010· article· en· W2558595032 on OpenAlexaff
Lindsay M. Morton, Ethel S. Gilbert, Charles F. Lynch, Per Hall, Graça M. Dores, Rochelle E. Curtis, Hans H. Storm, Tom Børge Johannesen, Marilyn Stovall, Susan A. Smith, Rita E. Weathers, Berthe M.P. Aleman, Ruth A. Kleinerman, Joseph F. Fraumeni, Eric J. Holowaty, ­Eero Pukkala, Magnus Kaijser, Michael Hauptmann, Sophie D. Fosså, Heikki Joensuu, Michael Andersson, Alexandra W. van den Belt‐Dusebout, Leila Vaalavirta, Frøydis Langmark, Lois B. Travis, Flora E. van Leeuwen

Bibliographic record

VenueBlood · 2010
Typearticle
Languageen
FieldMedicine
TopicGastric Cancer Management and Outcomes
Canadian institutionsCancer Care Ontario
Fundersnot available
KeywordsMedicineStomach cancerStomachCancerInternal medicineOdds ratioRadiation therapyGastroenterologyPopulation

Abstract

fetched live from OpenAlex

Abstract Abstract 2679 Introduction. Subsequent malignancies are a leading cause of morbidity and mortality among Hodgkin lymphoma (HL) survivors. Stomach cancer is one of the more common second malignancies occurring after HL, yet few studies have quantified stomach cancer risk in relation to radiation dose, and only one investigation has evaluated potential risks associated with chemotherapy. Methods. We conducted a nested case-control study of stomach cancer among 17,447 ≥5-year survivors of HL from six European and North American population-based cancer registries during 1953–2005. Patients included 71 cases diagnosed with HL and subsequent stomach cancer, and 142 individually-matched controls diagnosed with HL only. Data were pooled with a previous hospital-based case-control study from The Netherlands (18 cases, 48 controls), resulting in a total of 89 cases and 190 controls. For all patients, detailed data were abstracted from medical records on HL diagnosis and treatment and, for cases, stomach cancer diagnosis. Based on detailed radiotherapy information, the radiation dose was estimated to the area of the stomach where the case patient's tumor developed and to the comparable location in matched control patients. Chemotherapy data included specific drugs, doses, and number of cycles. The relative risk of stomach cancer was estimated using odds ratios (ORs) derived from conditional logistic regression analyses. Results. Median ages of case patients at HL and stomach cancer diagnosis were 32 years (range, 11–83 years) and 50 years (range, 26–89 years), respectively, with a median interval between HL and stomach cancer of 16 years (range, 5–36 years). Most patients received combined modality treatment (chemotherapy + radiotherapy, 56% cases, 44% controls) or radiotherapy alone (36% cases, 43% controls), whereas few patients received chemotherapy alone (8% cases, 13% controls). Stomach cancer risk increased with increasing radiation dose to the stomach tumor location (Ptrend<0.001). Compared with patients receiving <0.5 Gy, radiation doses of 30–39 Gy were associated with 5.3-fold increased risk [95% confidence interval (CI) 2.1–13], whereas radiation doses ≥40 Gy were associated with 2.1-fold increased risk (95%CI 0.8–5.9). Stomach cancer risk also increased with increasing number of cycles of alkylating agent chemotherapy (≥11 cycles versus no chemotherapy, OR=2.8, 95%CI 1.2–7.0; Ptrend=0.042), and was most strongly associated with increasing dose of procarbazine (Ptrend=0.004). Conclusions. Past treatment with radiotherapy and alkylating agent-based chemotherapy is associated with dose-dependent increased risk for stomach cancer among HL survivors. Current treatment practices with involved field radiotherapy, lower radiation doses, and alternate chemotherapy regimens may be associated with lower risk, however, patients receiving abdominal radiation and/or alkylating agents may still be at increased risk. Our results highlight the importance of increased awareness among clinicians and patients during long-term follow-up and prompt evaluation of signs and symptoms referable to the upper gastrointestinal tract. Disclosures: No relevant conflicts of interest to declare.

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)0.002
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.008
GPT teacher head0.250
Teacher spread0.242 · 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".

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Citations0
Published2010
Admission routes1
Has abstractyes

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