Families of Children Newly Diagnosed With Cancer Incur Significant Out-of-Pocket Expenditure for Treatment: Report of a Multi-Site Prospective Longitudinal Study From India (INPOG-ACC-16-01)
Notice bibliographique
Résumé
Background: Diagnosis of cancer in a child places considerable economic burden on families. The health expenditures are more catastrophic in resource limited countries like India where GDP spend on health is just over 1% and financing of treatment is usually out-of-pocket (OOP). Consequently parents may abandon their child's cancer treatment to ensure financial sustainability of the family. Research in this area is mostly from resource rich countries and OOP expenditure burden remains unknown in India. Aim: The objective of this study is to describe the OOP expenditure incurred by families of children (< 18 years age) with cancer being treated in India prior to and during cancer directed treatment. Methods: A prospective cost of illness study from a family household perspective was conducted in 14 centers (5 public, 5 private and 4 charitable trust sector) in 4 cities in India from 2016-2018. Baseline family demographic and socioeconomic data were collected followed by OOP expenditure incurred prior to start of treatment. For the duration of the child's treatment, a social worker contacted parents at regular intervals to record their expenditure on cancer directed treatment. Data collection was stopped when one of these happened - completion of treatment or death or progression/relapse or abandonment or transfer. Data were described descriptively and a univariate/multivariate analysis using logistic regression was done to detect factors associated with OOP expenditure. Results: 394 children (63% male, median age 5 years) with cancer (64% leukemia/lymphoma, 33% solid tumors, 3% CNS tumors) were enrolled from public (45%), charitable trust (28%) and private (27%) sector hospitals. They were symptomatic for a median duration of 6 weeks (range 0 to 104 weeks). 88% had no insurance and 73% were from families with monthly income of ≤ 10,000 rupees (≤ 159 US$). Mean OOP expenditure was Rs 209,500 (3325 US$) which is 195% of per capita income (1706 US$) of India. OOP expenditure from onset of symptoms to start of treatment was Rs 53,104 (843 US$) of which 77% was medical (15% laboratory tests, 11% medicines, 9% hospital bed costs) and 23% nonmedical (12% travel, 6% food, 3% lodging). OOP expenditure on cancer directed treatment was Rs 156,396 (2482 US$) of which 64% was medical (9% hospital bed costs, 9% supportive care drugs, 8% laboratory tests) and 36% nonmedical (19% food, 9% travel, 6% lodging). On univariate analysis age, gender, city, type of treatment facility, insurance, type of cancer, driving time and distance were significantly associated with OOP expenditure but only insurance and type of treatment facility were found significant on multivariate analysis. Conclusion: Families of children with cancer incur significant OOP expenditure prior to and during cancer directed treatment, which includes a significant portion on nonmedical expenses. Expenditure varied significantly by insurance and type of treatment facility.
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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».