Abstract P1-11-07: The relationship between breast cancer progression and workplace productivity in the US
Notice bibliographique
Résumé
Abstract Background: A significant proportion of women with breast cancer leave employment due to their disease. Little is known about the effects of breast cancer progression on productivity among those who remain employed. We sought to determine the effect of disease progression on workplace productivity among women with breast cancer. Methods: By linking health insurance claims data to workplace productivity data, a longitudinal dataset of women with breast cancer was constructed. The study cohort consisted of commercially insured women aged 18 to 64 in the US who were treated for any type of breast cancer between 2005 and 2012. Disease stage was measured through diagnosis codes and treatments observed, to classify women into the following breast cancer groups in each 90-day quarter: local; locally advanced; other non-metastatic; metastatic, 1st line therapy; metastatic, 2nd line therapy; metastatic, ≥ 3rd line therapy; metastatic, end-of-life care. Progression was defined as movement to a more advanced disease stage. Workplace productivity was measured as employment status and total hours away from work per quarter. Covariates included employer industry, comorbidities, age, region of residence, and a time trend. Reduced workplace productivity was valued using average U.S. wages by industry. Kaplan Meier analysis was used to test whether women whose cancer progressed were more likely to drop out of our employment-based sample. Linear and Heckman models were used to measure the effect of disease progression on workplace hours missed. The Heckman model was used to correct for selection bias, given that healthier women may be more likely to remain in our employment-based dataset. Results: The study cohort included 6,409 women. Mean patient age was 52.0 years (SD: 7.7). The mean number of Charlson comorbidities was 0.52 per patient (SD: 2.9). The majority of our employment-based sample had non-metastatic breast cancer (90.7%). Breast cancer progression was associated with a lower probability of employment (hazard ratio = 0.65, P<0.01). Patients who left our employment-based dataset by the 12th quarter had a greater number of comorbidities (P<0.01) and missed a greater number of hours in the first two quarters (P<0.1), compared with those who remained. This indicated that patients leaving our employment-based sample were less healthy than those who stayed, supporting the use of the Heckman model. According to the Heckman results, progression was associated with increased workplace hours missed per quarter, both when comparing early versus late stage (P<0.001), and first-line versus later-line metastatic therapy (P<0.05). Linear results were similar. Using the Heckman results, the annual valuation of work missed per patient was $29,881 for patients without metastases and $34,141 for patients with, indicating that progression to metastatic cancer adds an additional $6,500 of lost work time, or about 14% of average US wages. Conclusions: Breast cancer progression leads to increased workplace hours missed, with greater hours missed among those with more advanced disease. Avoiding or delaying disease progression could bring productivity gains to the workplace in addition to the benefits to the patient. Support: This study was funded by Pfizer Inc. Citation Format: Yin W, Horblyuk R, Perkins JJ, Sison S, Smith G, Snider JT, Wu Y, Philipson TJ. The relationship between breast cancer progression and workplace productivity in the US. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P1-11-07.
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 | 0,001 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».