The potential for lost productivity in lung cancer patients
Notice bibliographique
Résumé
6093 Background: Lung cancer significantly impacts on a patient’s personal and professional life. Little is known about lung cancer patients’ lost productivity, which in turn has an important effect on society. We undertook this descriptive study to learn about lost productivity experienced by lung cancer patients and their caregivers. Methods: 40 consecutive patients attending outpatient lung clinics at a major cancer centre completed questionnaires assessing demographic details, patient and caregiver productivity, and quality of life (EQ5D, FACT-L). Results: 52.5% of respondents were male. Median age was 67 years (range 36 -81). Median disclosed income was $20,000–$39,999; 46.2% had pursued post-secondary training. 70% were ex-smokers, 40% had NSCLC, 27% SCLC, while a third did not know their diagnosis. Treatments received included IV chemotherapy (62.5%), oral therapy (20%), radiation (55%), surgery (42.5%) and 5% no treatment. Over 25% were working full-time prior to diagnosis, 40% were retired. None were able to continue full-time employment; 20% required disability or sick leave. 8 (20%) were able to work part-time. Of those still working, a median of 14 h were missed due to illness in the preceding 3 weeks, with a median of 32 h worked in that period. Patients reported an overall moderate (5/10) impact on their productivity and a significant (6/10) impact on their daily activities attributable to their cancer. Only 8.5% of patients received paid assistance, while 76% had their spouse, relative or friend as an unpaid caregiver. In the preceding 3 weeks, caregivers who assisted patients provided a median 24h of care; 25% of caregivers missed a median 12h of work. Overall, mobility, self-care and anxiety/depression were rated as mildly affected (1/3), while daily activities and pain/discomfort were rated as moderately affected (2/3). Median overall health state rated by the respondents was 60 {scale 0(worst)-100(best)}. Quality of life overall was poor - FACT-L median score was 93.2 (range 50 to 125). Conclusion: Lung cancer negatively impacts work productivity and significantly impairs activity. While many lung cancer patients are retired, there is a significant burden on caregivers, which may result in a substantial burden to society in lost productivity. No significant financial relationships to disclose.
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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 | 0,002 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
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.
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 ».