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Enregistrement W1982077008 · doi:10.5045/kjh.2012.47.1.1

The premier statistical report of hematologic malignancies in Korea

2012· article· en· W1982077008 sur OpenAlexaboutno aff
Hee‐Je Kim

Notice bibliographique

RevueThe Korean Journal of Hematology · 2012
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple and Secondary Primary Cancers
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicinePopulationHematologic malignancyHematologic NeoplasmsDiseaseStatisticsCancerEnvironmental healthPathology

Résumé

récupéré en direct d'OpenAlex

Tada! The current issue of the Korean Journal of Hematology includes a very impressive, surprising report describing, for the first time, the statistics of hematologic malignancies in Korea [1]. In fact, until now, no reliable nationwide cancer statistics describing hematologic malignancies have been published in Korea. While the report presented in this current issue may be somewhat incomplete, it represents an excellent database that can be used both domestically and worldwide as an important source of cancer statistics from Korea. Because the database contains all aspects of population-based, disease-specific statistics, along with survival- and death-related data from 1993 to 2008, we can analyze and compare our own data with that of other countries, allowing high-ranked public officials to shape national policies and health strategies in the field of hematologic malignancy in the future. On the other hand, this statistics presented in the current issue could be representative of the estimated incidence and prevalence since we still do not have a reporting system that enables accurate data collection and creation of a nationwide database for specific regions or specific periods of time. The data from 1993 and prior should differ quite dramatically from data for 2008. However, we recognize that the publication of this statistical report provides us with a beginning from which we can establish a reliable health reporting system in Korea. Undoubtedly, this is the first step toward developing more complementary and up-to-date health statistics in this country. Based on an annually increasing trend, we can say for certain that greater than 8,000 new cases of blood cancer patients were diagnosed in 2008 according to data from the Korea National Cancer Incidence Database (KNCIDB) [1, 2]. In addition, survival and mortality data from 1993 to 2008 were obtained from the Korea National Statistics Office (KNSO) [1, 2]. These data were combined, and the current report calculated, for the first time in Korea, the incidence, mortality, prevalence, limited-duration prevalence, and changes in the annual age-standardized cancer incidence rates. Now, Korean medical students can be taught oncology using Korea's own statistics, rather than the statistics of other countries. Therefore, although it is somewhat shameful to admit that this is the first publication of national data on hematologic malignancies, we should consider this a memorable and historical achievement. To establish further reliable statistics on hematologic malignancies, we anticipate that more aggressive efforts will be made to collect data from every regional database in Korea. Based on a recent report published in the Journal Cancer Research and Treatment in 2011 [2], we found that 2,561 new cases of leukemia were diagnosed in Korea in 2008. In contrast to this report, the most recent report published in our journal showed that 2,262 new cases of lymphoid and myeloid leukemia occurred during the same year, according to the same investigators. Moreover, the annual increase in incidence was relatively small (1.2-1.4% for leukemia compared with 3.9% for other hematologic malignancies). An international comparison of the age-standardized incidence rates of hematologic malignancies also revealed that this increase was only about one-half of the increase that occurred in USA and Canada. It may be incomparable to other western countries. This data contradiction must be resolved in near future. The National Cancer Institute's Surveillance, Epidemiology and End Results Program (SEER), published online by SEER Review Facts annually [3], may be a paradigm of cancer statistics observation and reporting that should be considered. The data system used in the SEER program is much more friendly to policy makers, researchers, and even clinicians and patients and introduces some new approaches in the field of hematologic malignancies, including somewhat brief guidelines for chemotherapy, radiation, stem cell transplantation, etc. Furthermore, we could investigate psychosocial sequelae, aspects of socioeconomic understanding in the context of quality of life issues, and different aspects of acute and chronic leukemias in adults and children from these SEER reports. A review of the SEER program suggests that we still need to better subdivide and define age-specific incidence rates for each blood cancer. With regard to preventive medicine, it will be helpful for us to study these diseases, if the data include epidemiology, as shown in SEER approaches. Notwithstanding the above mentioned insufficiencies of our first national blood cancer statistics, we are excited to acknowledge the efforts made by many clinicians and researchers in establishing this first official report in Korea. We will develop many more constructive health policies in this field thanks to the framework published today, and we should be proud of ourselves for establishing this base source for investigating important epidemiologic characteristics, evaluating progress in disease management, and establishing future strategies for all hematologic malignancies. In the era of aging in Korea, cancer incidence is on the rise, and continuous efforts must be made to create more efficient cancer control programs and to make data available, with significant attention to detail and exquisite skills in the periodic statistical analysis of hematologic malignancies. We have just scratched the surface in the proficient development of our own cancer control programs.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,489
Score d'incertitude au seuil0,219

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,025
Tête enseignante GPT0,300
Écart entre enseignants0,275 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2012
Routes d'admission1
Résumé présentoui

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