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Record W3025890592 · doi:10.1097/dcr.0000000000001665

Nonoperative Management Versus Radical Surgery of Rectal Cancer After Neoadjuvant Therapy-Induced Clinical Complete Response: A Markov Decision Analysis

2020· article· en· W3025890592 on OpenAlexaff
Anthony de Buck van Overstraeten, Sepehr Khorasani, Erin Kennedy, Nicole J. Look Hong

Bibliographic record

VenueDiseases of the Colon & Rectum · 2020
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Surgical Treatments
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science CentreMount Sinai Hospital
Fundersnot available
KeywordsMedicineNeoadjuvant therapySurgical oncologyColorectal surgeryRadical surgeryColorectal cancerComplete responseSurgeryDecision analysisGeneral surgeryOncologyCancerAbdominal surgeryInternal medicineChemotherapy

Abstract

fetched live from OpenAlex

BACKGROUND: Nonoperative management of rectal cancer was introduced for patients with clinical complete response after neoadjuvant chemoradiotherapy to avoid short- and long-term surgical morbidity related to radical resection. OBJECTIVE: The purpose of this study was to determine the expected life-years and quality-adjusted life-years for nonoperative management and radical resection of locally advanced rectal cancer after clinical complete response following neoadjuvant chemoradiotherapy. DESIGN: Markov modeling was used to simulate nonoperative management and radical surgery for a base case scenario over a 10-year time horizon. Estimates for various clinical variables were obtained after extensive literature search. Outcome was expressed in both life-years and quality-adjusted life-years. Deterministic sensitivity analyses were completed to assess the impact of variation in key parameters. SETTING: A decision model using a Markov model was designed. PATIENTS: The base case was a 65-year-old man with a distal rectal tumor who had achieved clinical complete response after neoadjuvant chemoradiotherapy. MAIN OUTCOME MEASURES: Life-years and quality-adjusted life-years were measured. RESULTS: Quality-adjusted life-years (5.79 for nonoperative management vs 5.62 for radical surgery) and life-years (6.92 for nonoperative management vs 6.96 for radical surgery) were similar between nonoperative management and radical surgery. The preferred treatment strategy changed with variations in the probability of local regrowth in nonoperative management, the probability of salvage surgery for regrowth in nonoperative management, utilities associated with nonoperative management and low anterior resection, and the utility of low anterior resection syndrome. The model was not sensitive to (dis)utilities associated with stoma, chemotherapy, or postoperative morbidity and mortality. LIMITATIONS: The study was limited by assumptions inherent to modeling studies. CONCLUSIONS: Nonoperative management and radical surgery resulted in similar (quality-adjusted) life-years. Nonoperative management should therefore be considered as a reasonable treatment option. See Video Abstract at http://links.lww.com/DCR/B246. MANEJO NO-QUIRÚRGICO VERSUS CIRUGÍA RADICAL DEL CÁNCER RECTAL DESPUÉS DE LA RESPUESTA CLÍNICA COMPLETA INDUCIDA POR TERAPIA NEOADYUVANTE: UN ANÁLISIS DE DECISIÓN DE MARKOV: Se introdujo el tratamiento no quirúrgico del cáncer rectal para pacientes con respuesta clínica completa después de la quimiorradioterapia neoadyuvante para evitar la morbilidad quirúrgica a corto y largo plazo relacionada con la resección radical.Determinar los años de vida esperados y los años de vida ajustados por calidad para el tratamiento no-quirúrgico y la resección radical del cáncer rectal localmente avanzado, después de la respuesta clínica completa siguiente de la quimiorradioterapia neoadyuvante.El modelo de Markov se usó para simular el manejo no-quirúrgico y la cirugía radical para un escenario de caso base en un horizonte temporal de 10 años. Se obtuvieron estimaciones para diversas variables clínicas después de una extensa búsqueda bibliográfica. El resultado se expresó tanto en años de vida como en años de vida ajustados por calidad. Se completaron análisis determinísticos de sensibilidad para evaluar el impacto de la variación en los parámetros clave.Se diseñó un modelo de decisión utilizando un modelo de Markov.El caso base fue un hombre de 65 años con un tumor rectal distal que había logrado una respuesta clínica completa después de la quimiorradioterapia neoadyuvante.Años de vida y años de vida ajustados por calidad.Los años de vida ajustados por calidad (5.79 para el tratamiento no-quirúrgico frente a 5.62 para la cirugía radical) y los años de vida (6.92 para el tratamiento no-quirúrgico frente a 6.96 para la cirugía radical) fueron similares entre el tratamiento no-quirúrgico y la cirugía radical. La estrategia de tratamiento preferida cambió con las variaciones en la probabilidad de nuevo crecimiento local en el manejo no-operatorio, la probabilidad de cirugía de rescate para el rebrote en el manejo no-operatorio, las utilidades asociadas con el manejo no-operatorio, y la resección anterior baja y la utilidad de el syndrome de resección anterior baja. El modelo no era sensible a las (des) utilidades asociadas con el estoma, la quimioterapia o la morbilidad y mortalidad postoperatorias.El estudio estuvo limitado por suposiciones inherentes a los estudios de modelado.El manejo no-quirúrgico y la cirugía radical resultaron en años de vida similares (ajustados por calidad). Por lo tanto, el tratamiento no-quirúrgico debe considerarse como una opción de tratamiento razonable. Consulte Video Resumen en http://links.lww.com/DCR/B246.

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)0.008
metaresearch head score (Gemma)0.012
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 score0.019
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.081
GPT teacher head0.372
Teacher spread0.290 · 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

Citations8
Published2020
Admission routes1
Has abstractyes

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