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Record W2973231291 · doi:10.1186/s13014-019-1372-3

Skeletal muscle mass correlates with increased toxicity during neoadjuvant radiochemotherapy in locally advanced esophageal cancer: A SAKK 75/08 substudy

2019· article· en· W2973231291 on OpenAlexaff
Cédric Panje, Laura Höng, Stefanie Hayoz, Vickie E. Baracos, Evelyn Herrmann, Helena Garcia Schüler, Urs R. Meier, Guido Henke, Sabina Schacher, Hanne Hawle, Marie-Aline Gérard, Thomas Ruhstaller, Ludwig Plaßwilm

Bibliographic record

VenueRadiation Oncology · 2019
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsUniversity of Alberta
FundersStaatssekretariat für Bildung, Forschung und InnovationSchweizerische Arbeitsgemeinschaft für Klinische KrebsforschungMerck KGaA
KeywordsMedicineEsophageal cancerNeoadjuvant therapyChemoradiotherapyInternal medicineOncologyRadiation therapyCancerCardiologyRadiology

Abstract

fetched live from OpenAlex

BACKGROUND: Sarcopenia, the critical depletion of skeletal muscle mass, is an independent prognostic factor in several tumor entities for treatment-related toxicity and survival. In esophageal cancer, there have been conflicting results regarding the value of sarcopenia as prognostic factor, which may be attributed to the heterogeneous patient populations and the retrospective nature of previous studies. The aim of our study was therefore to determine the impact of sarcopenia on prospectively collected specific outcomes in a subgroup of patients treated within the phase III study SAKK 75/08 with trimodality therapy (induction chemotherapy, radiochemotherapy and surgery) for locally advanced esophageal cancer. METHODS: Sarcopenia was assessed by skeletal muscle index at the 3rd lumbar vertebra (L3) in cross-sectional computed tomography scans before induction chemotherapy, before radiochemotherapy and after neoadjuvant therapy in a subgroup of 61 patients from four centers in Switzerland. Sarcopenia was determined by previously established cut-off values (Martin et al., PMID: 23530101) and correlated with prospectively collected outcomes including treatment-related toxicity, postoperative morbidity, treatment feasibility and survival. RESULTS: Using the published cut-off values, the prevalence of sarcopenia increased from 29.5% before treatment to 63.9% during neoadjuvant therapy (p < 0.001). Feasibility of neoadjuvant therapy and surgery was not different in initially sarcopenic and non-sarcopenic patients. We observed in sarcopenic patients significantly increased grade ≥ 3 toxicities during chemoradiation (83.3% vs 52.4%, p = 0.04) and a non-significant trend towards increased postoperative complications (66.7% vs 42.9%, p = 0.16). No difference in survival according to sarcopenia could be observed in this small study population. CONCLUSIONS: Trimodality therapy in locally advanced esophageal cancer is feasible in selected patients with sarcopenia. Neoadjuvant chemoradiation increased the percentage of sarcopenia. Sarcopenic patients are at higher risk for increased toxicity during neoadjuvant radiochemotherapy and showed a non-significant trend to more postoperative morbidity.

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)0.001
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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)0.0010.000

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 head0.008
GPT teacher head0.305
Teacher spread0.297 · 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

Citations43
Published2019
Admission routes1
Has abstractyes

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