Abstract PO-058: Piloting a novel strategy to rapidly implement smoking cessation treatment for newly-diagnosed head and neck cancer patients
Notice bibliographique
Résumé
Abstract Purpose The purpose of this study is to evaluate a novel, bimodal strategy to implement smoking cessation treatment prior to oncologic therapy in newly-diagnosed head and neck cancer (HNC) patients. Background Among the 65,000 people who develop HNC in the United States (US) annually, 20-30% smoke cigarettes and 50-80% will continue smoking throughout survivorship. Quitting smoking before oncologic therapy correlates with improved health outcomes. However, the window of opportunity to quit smoking is narrow since cancer treatment often begins 4-5 weeks after the first oncology visit. The failure to rapidly implement evidence-based smoking cessation treatment is a major cause of this problem. Offering both behavioral therapy and pharmacotherapy increases abstinence rates by 2-3-fold. Despite this, only 4-17% of cancer patients receive both therapies at any time. Methods We conducted a pragmatic, quasi-experimental, pilot study using a pre-post design to evaluate a strategy to rapidly implement behavioral therapy and pharmacotherapy. The pre-test period was from 1/21-3/22 and the strategy was deployed from 4/22-10/22. The population included newly-diagnosed patients with mucosal HNC or salivary gland cancer. The setting was an academic medical center with an established tobacco treatment program (TTP). The implementation strategy involved bimodal administration of the evidence-based Ask, Advise, Connect (AAC) approach before and at the first surgical oncology visit. First, a dedicated medical assistant (MA) used an electronic health record (EHR)-based tool to identify, ask, advise, and connect (i.e. refer) smokers to the TTP at the time of clinic referral, or ~1-2 weeks before the first surgical oncology visit. Second, the AAC strategy was delivered by the triage MA and nurse at the time of the first surgical oncology visit. Some surgeons opportunistically offered patients pharmacotherapy. Results Among the 383 eligible, newly-diagnosed HNC patients, and 48 (12.5%) were current smokers. Twelve smokers were diagnosed between 4/22-10/22 and were eligible for the bimodal AAC strategy. However, only six of 12 patients received the AAC strategy before the first oncology visit. Among the 48 smokers, 75% were male, the median age was 65.5-years, and cancer treatment was started a median 34 days after the first oncology visit. Within 30 days of the first surgical oncology visit, 67% were advised to quit, 25% were referred to the TTP, 6% completed a comprehensive TTP visit, 21% had pharmacotherapy ordered, and 17% received both behavioral therapy and pharmacotherapy. While there were otherwise no differences in outcomes between pre- and post-strategy groups, more bimodal AAC strategy-eligible patients received pharmacotherapy (42%) compared to pre-strategy patients (14%, p=0.040). Conclusions Our bimodal AAC strategy correlated with increased use of pharmacotherapy, despite suboptimal fidelity to the approach. Additional strategies to improve delivery of timely behavioral therapy and pharmacotherapy for smoking cessation are needed. Citation Format: Sahajveer Mann, Julia Casazza, Dalia Mitchell, Quynh-Chi Dang, Dequan Weston, Brette Harding, Baran D. Sumer, Brittny Tillman, Heather Kitzman, George Jackson, Robert Schnoll, Amit Singal, Andrew T. Day. Piloting a novel strategy to rapidly implement smoking cessation treatment for newly-diagnosed head and neck cancer patients [abstract]. In: Proceedings of the AACR-AHNS Head and Neck Cancer Conference: Innovating through Basic, Clinical, and Translational Research; 2023 Jul 7-8; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2023;29(18_Suppl):Abstract nr PO-058.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».