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Enregistrement W4415898738 · doi:10.1136/jitc-2025-sitc2025.0718

718 Global quantitative patient chart review of multidisciplinary team (MDT) care and treatment use in early-stage non-small-cell lung cancer (NSCLC)

2025· article· W4415898738 sur OpenAlexaff
Yao Qiao, Ticiana Leal, Thiago David Alves Pinto, Severin Schmid, R RAWLINSON, Florence MacIver Bulbrook, Mary Kate Shanahan, Nefeli Georgoulia, Torben Riis Rasmussen, Houda Bahig

Notice bibliographique

RevueRegular and Young Investigator Award Abstracts · 2025
Typearticle
Langue
DomaineMedicine
ThématiqueLung Cancer Diagnosis and Treatment
Établissements canadiensUniversité de MontréalMontfort Hospital
Organismes subventionnairesAstraZeneca
Mots-clésMultidisciplinary approachLung cancerChartMEDLINEPatient careLung disease

Résumé

récupéré en direct d'OpenAlex

Background MDT care is increasingly important in the evolving early-stage NSCLC treatment landscape. Here, as part of an ongoing global MDT study, we conducted a review of early-stage NSCLC patient charts to capture demographics, MDT care, treatment use, and biomarker information.Methods Oncologists, surgeons, pulmonologists, radiation oncologists, and chest physicians (UK only) from 11 countries who managed ≥5 patients with stage I-IIIB NSCLC (AJCC 8th ed.) in the year prior to screening (2024), had practiced ≥3 years, were licensed and board certified/eligible, and spent >60% (community) or >30% (academic) of their time in clinical practice were each invited to provide deidentified patient information for three early-stage NSCLC patients via medical chart abstraction. Eligible patients were ≥18 years old, had stage I-IIIB disease at initial diagnosis of NSCLC, received the initial diagnosis 6–18 months prior to data extraction, and are currently treated by the physician. Findings were summarized descriptively; multivariable logistic regression was used to assess the association of MDT discussion with neoadjuvant treatment.Results Baseline characteristics are summarized in table 1. Overall, 80.6% of patients had biomarker testing at diagnosis. Among resected patients (n=926), the most common treatment pathway was surgery followed by adjuvant therapy (37.6%), while 17.1% and 21.9% received neoadjuvant and perioperative treatment, respectively; for unresected patients (n=469), the most common treatment pathway was chemoradiotherapy followed by consolidation therapy (44.1%) (table 2). Notably, 12.1% of the patients reviewed were not discussed at an MDT meeting; this was most common in Canada (31.4%), Mexico (21.8%), Japan (20.1%) and Brazil (19.6%), and in a community (13.9%) versus academic (9.9%) setting. The most cited reasons for patients not being discussed at an MDT meeting included: the physician being confident in the treatment plan without MDT input (49.4%, particularly the case for stage I patients); MDT meeting was scheduled but did not occur (17.4%); delays in diagnostic information or results that were needed for an MDT discussion (17.4%); limited physician availability (15.1%); and administrative issues/errors (9.3%). Multivariable regression among resected patients showed MDT discussion before treatment is a key predictor of receiving therapy before surgery (odds ratio [OR] 2.08, 95% confidence interval [CI] 1.34–3.27), along with disease stage IIIA/IIIB (OR 8.09, 95% CI 5.40–12.32) and presence of comorbidities (OR 1.98, 95% CI 1.35–2.95).Conclusions MDT discussion is impactful for the management of early-stage NSCLC. However, variation in access remains across countries and between academic versus community settings.Acknowledgements This study was funded by AstraZeneca. Medical writing support for the development of this abstract, under the direction of the authors, was provided by James Holland, PhD, of Ashfield MedComms (Manchester, UK), an Inizio company, in accordance with Good Publication Practice (GPP) guidelines (http://www.ismpp.org/gpp-2022), and was funded by AstraZeneca.Abstract 718 Table 1Patient demographicsAJCC, American Joint Committee on Cancer; ALK, anaplastic lymphoma kinase; EGFR, epidermal growth factor receptor; PD-L1, programmed death ligand 1.Abstract 718 Table 2Summary of key findings from patient chart review by disease stage aAll patients discussed by MDT. bIncludes MDT coordinator, general surgeon, radiologist, clinical oncologist, pulmonary oncologist, hematology-oncologist, chest physician/respiratory physician (UK only), cancer nurse specialist, nuclear medicine physician, ‘other,’ and don’t know.Adj, surgery plus adjuvant therapy; CRT, chemoradiotherapy; CRT+cons, chemoradiotherapy followed by consolidation therapy; MDT, multidisciplinary team; Neoadj, neoadjuvanttherapy plus surgery; Periop, perioperative (neoadjuvant therapy, followed by surgery and adjuvant therapy); SBRT, stereotactic body radiotherapy; SBRT+CT, stereotactic body radiotherapy plus chemotherapy.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,010
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,035
Score d'incertitude au seuil0,070

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,010
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0020,003
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,020
Tête enseignante GPT0,309
Écart entre enseignants0,289 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentnon

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