THE IMPACT OF NEW DRUG LAUNCHES ON LIFE-YEARS LOST IN 2015 FROM 19 TYPES OF CANCER IN 36 COUNTRIES
Notice bibliographique
Résumé
Abstract: This study employs a two-way fixed effects research design to measure the mortality impact and cost-effectiveness of cancer drugs: It analyzes the correlation across 36 countries between the relative mortality from 19 types of cancer in 2015 and the relative number of drugs previously launched in that country to treat that type of cancer, controlling for relative incidence. The sample size (both in terms of number of observations and population covered) of this study is considerably larger than the sample sizes of previous studies; a new and improved method of analyzing the lag structure of the relationship between drug launches and life-years lost is used; and a larger set of measures of the burden of cancer is analyzed. The number of DALYs and life-years lost are unrelated to drug launches 0–4 years earlier. This is not surprising, since utilization of a drug tends to be quite low during the first few post-launch years. Moreover, there is likely to be a lag of several years between utilization of a drug and its impact on mortality. However, mortality is significantly inversely related to the number of drug launches at least 5 years earlier, especially to drug launches 5–9 years earlier. One additional drug for a cancer site launched during 2006–2010 is estimated to have reduced the number of 2015 DALYs due to cancer at that site by 5.8%;; one additional drug launched during 1982–2005 is estimated to have reduced the number of 2015 DALYs by about 2.6%. Lower quality (or effectiveness) of earlier vintage drugs may account for their smaller estimated effect. We estimate that drugs launched during the entire 1982–2010 period reduced the number of cancer DALYs in 2015 by about 23.0%, and that, in the absence of new drug launches during 1982–2010, there would have been 26.3 million additional DALYs in 2015. Also, the nine countries with the largest number of drug launches during 1982–2010 are estimated to have had 14% fewer cancer DALYs (controlling for incidence) in 2015 than the nine countries with the smallest number of drug launches during 1982–2010. Estimates of the cost per life-year gained in 2015 from drugs launched during 2006–2010 range between $1,635 (life-years gained at all ages) and $2,820 (life-years gained before age 65). These estimates are similar to those obtained in previous country-specific studies of Belgium, Canada, and Mexico, and are well below the estimate obtained in one study of Switzerland. Mortality in 2015 is strongly inversely related to the number of drug launches in 2006–2010. If the relationship between mortality in 2020 and the number of drug launches in 2011–2015 is similar, drug launches 5–9 years earlier will reduce mortality even more (by 9.9%) between 2015 and 2020 than they did (by 8.4%) between 2010 and 2015.
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 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,005 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».