Incidence rates of thyroid cancer and myeloid leukaemia in French Polynesia
Notice bibliographique
Résumé
The International Agency for Research on Cancer regularly updates the monograph “Cancer Incidence in Five Continents” providing international comparisons of cancer incidence rates from population-based cancer registries around the world. The most recent data cover the 4-year period 1998–2002.1 In Figure 1, we show the ten regions/populations of the world with the highest and lowest incidence rates among women (age-standardised rates for the world population, ASRw) and their 95% Confidence Intervals (95%CI) for thyroid cancer (International Classification of Diseases ICD code: C73) and myeloid leukaemia (ICD code: C92.9). Regions/populations around the world with the highest and the lowest age standardized (world population) incidence rates of thyroid cancer and myeloid leukaemia among women with corresponding 95% Confidence Intervals, 1998–2002.1 Women in French Polynesia (245 405 inhabitants in 2002) show the highest incidence rates of both thyroid cancer (ASRw: 37.4/100 000, 95%CI: 31.8–43.03) and myeloid leukaemia (ASRw: 6.0/100 000, 95%CI: 3.7–8.3). The current observation is based on 180 new cases diagnosed during the 4-year period. Rates for myeloid leukaemia are based on 27 new cases for the same period. Incidences rates for these two cancer sites were also high among men: for the 4-year period, French Polynesian men rank fifth among the 300 involved cancer registries for thyroid cancer (incidence rates 5.4/100 000, 95%CI: 3.14–7.66, 26 cases) and 70th for myeloid leukaemia (incidence rates 4.7/100 000, 95%CI: 2.64–6.76, 23 cases). The Cancer Registry of French Polynesia started in 1988.2 The geographical comparison of ASRw between 175 registries for the period 1988–1992 shows that French Polynesia already ranked 2nd for thyroid cancer among females and 9th among males. During the same period, incidence of myeloid leukaemia in French Polynesia was relatively low and similar among females and males, ranking 80th and 79th, respectively.3 Radiation exposure is a well-established risk factor for these two cancers. In particular, leukaemia (especially myeloid leukaemia) and thyroid cancer were the first radiation-induced cancers reported among A-bomb survivors with the risk peaking within 10 years of exposure and remaining increased for at least several decades.4 Several studies among A-bomb survivors have also reported that in addition to dose and age at exposure, sex could modify radiation carcinogenesis with women being more prone than males to develop induced solid tumours.5 This was also observed after the Chernobyl accident.6 France conducted nuclear tests in French Polynesia in the atolls of Mururoa and Fangataufa between 1966 and 1995, 42 of these tests took place during the period 1966–1974 in the atmosphere.7 Reports on the health effects of the actual residual radioactive material from such tests have so far been reassuring,7 but these reports did not concern potential effects of contamination at time of nuclear tests. A case–control study aiming to evaluate the role of radio-iodine fallouts from atmospheric tests is ongoing on thyroid cancer,8 but only descriptive reports,2, 9 and no epidemiological studies have been undertaken on myeloid leukaemia. Comparisons of cancer incidences between cancer registries are difficult because of differences in completeness and accuracy of cancer registration and access to medical facilities. Incidence rates for myeloid leukaemia are generally based on few cases providing large overlapping confidence intervals. Therefore, differences between countries at high risk are not significant. Besides, no incidence data exist for previous periods for comparison. We believe, however, in the necessity of sustained surveillance of the population in this region to monitor health consequences of exposure to radiations emanating from nuclear tests. Yours sincerely, Christine Bouchardy*, Simone Benhamou* , Florent de Vathaire§, Robin Schaffar*, Elisabetta Rapiti*, * Geneva Cancer Registry, Institute for Social and Preventive Medicine, University of Geneva, Geneva, Switzerland, INSERM, U946, Fondation Jean Dausset-CEPH, Paris, France, CNRS UMR8200, Gustave-Roussy Institute, Villejuif, France, § INSERM, U605, Gustave-Roussy Institute, Villejuif, France.
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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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».