Abstract PO5-12-02: Landscape analysis of oncology nutrition research among patients being treated for breast cancer
Notice bibliographique
Résumé
Abstract The American Institute for Cancer Research/World Cancer Research Fund and the American Cancer Society regularly conduct systematic reviews on the evidence supporting nutrition interventions during cancer treatment. These reviews have found that the evidence to support clinical oncology nutrition practice guidelines is limited. It is unclear how many oncology nutrition studies are currently being conducted, especially among patients being treated for breast cancer. The goal of this project was to conduct a landscape analysis of nutrition research being conducted among breast cancer patients over the past 10 years. Methods: This analysis was part of a larger effort to describe the oncology nutrition research landscape for all cancer sites. Searches of ClinicalTrials.gov were performed on 1/8/2023 using the following search terms/combinations: “cancer AND nutrition”, “cancer nutrition”, “oncology AND nutrition”, “diet AND cancer”, “cancer, oncology, neoplasms, nutrition, diet”. Search results were downloaded as .csv files and uploaded to RStudio for merging and data cleaning (elimination of duplicates, and exclusion of studies registered in ClinicalTrials.gov before 1/1/2013 or after 12/31/2022). The resulting harmonized dataset was then uploaded to REDCap, and each entry was reviewed for eligibility by one of the authors. To be included in this landscape analysis, studies must have included data collection from patients who were actively receiving cancer treatment at the time of the study and the study had to be first posted to ClinicalTrials.gov between 1/1/2013 and 12/31/2022. Studies were excluded if they: 1) focused on the role of diet in primary cancer prevention, 2) focused on cancer survivors who had completed primary treatment for their cancers. Following eligibility review, the study datafile was returned to RStudio for further cleaning and analysis. Results: The initial ClinicalTrials.gov search identified 4,345 unique study listings. After review, 1,267 studies met the inclusion criteria, of which 132 (10.4%) studies were specific to breast cancer (117 intervention studies and 15 observational studies). Among breast cancer studies, reasons for exclusion were: study focused on diet/nutrition in the prevention of a primary cancer diagnosis (n=40), study participants had already completed their cancer treatment (n=128), study did not include a diet/nutrition intervention or assessment (n=31). The largest number of breast cancer specific studies were based in the United States (n=55, 41.6%), Italy (n=11, 8.3%), France (n=10, 7.6%) and Canada (n=9, 6.8%). Dietary supplement interventions were the most common type of intervention (n=50 studies, 42.7%), followed by behavior change interventions (n=22, 18.8%), diet in relation to a drug intervention (n=25, 21.4%), diet in relation to a device/procedure/radiation intervention (n=16, 14%), fasting/time-restricted feeding studies (n=13, 11.1%) and ketogenic diet interventions (n=3, 2.6%). Changes in weight or body composition (n=52, 39.4%), quality of life (n=45, 34.1%), adverse events (n=24, 18.2%), survival (n=20, 15,2%) and fatigue (n=17, 12.9%) were the most common outcome measures. Sixteen (12.1%) studies were supported by NIH funding and 9 (6.8%) studies were industry funded, although the majority (n=124, 93.9%) reported funding from “other” sources. Of the 41 studies that started between 2013-2017 (five years prior to the January 2023 ClinicalTrials.gov search), only 21 (51.2%) were listed as being “completed” and of those, only 7 were listed as “has results”. Conclusion: More research is needed to support evidence-based supportive care guidelines for oncology nutrition interventions during breast cancer treatment. Efforts should be made to support researchers in completing studies and disseminating research findings. Citation Format: Kim Robien, Heather Wopat. Landscape analysis of oncology nutrition research among patients being treated for breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-12-02.
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 | 0,024 | 0,105 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,011 |
| Bibliométrie | 0,026 | 0,048 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,006 | 0,003 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,017 | 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 ».