Botta Laura, Capocaccia Riccardo, Trama Annalisa, Herrmann Christian, Salmerón Diego, De Angelis Roberta, Mallone Sandra, Bidoli Ettore, Marcos-Gragera Rafael, Dudek-Godeau Dorota, Gatta Gemma, Cleries Ramon
Evaluative Epidemiology Unit, Fondazione IRCCS Istituto Nazionale Tumori, Milan, Italy.
Evaluative Epidemiology Unit, Fondazione IRCCS Istituto Nazionale Tumori, Milan, Italy.
Cancer Epidemiol. 2018 Jun;54:95-100. doi: 10.1016/j.canep.2018.04.003. Epub 2018 Apr 21.
The RARECAREnet project has updated the estimates of the burden of the 198 rare cancers in each European country. Suspecting that scant data could affect the reliability of statistical analysis, we employed a Bayesian approach to estimate the incidence of these cancers.
We analyzed about 2,000,000 rare cancers diagnosed in 2000-2007 provided by 83 population-based cancer registries from 27 European countries. We considered European incidence rates (IRs), calculated over all the data available in RARECAREnet, as a valid a priori to merge with country-specific observed data. Therefore we provided (1) Bayesian estimates of IRs and the yearly numbers of cases of rare cancers in each country; (2) the expected time (T) in years needed to observe one new case; and (3) practical criteria to decide when to use the Bayesian approach.
Bayesian and classical estimates did not differ much; substantial differences (>10%) ranged from 77 rare cancers in Iceland to 14 in England. The smaller the population the larger the number of rare cancers needing a Bayesian approach. Bayesian estimates were useful for cancers with fewer than 150 observed cases in a country during the study period; this occurred mostly when the population of the country is small.
For the first time the Bayesian estimates of IRs and the yearly expected numbers of cases for each rare cancer in each individual European country were calculated. Moreover, the indicator T is useful to convey incidence estimates for exceptionally rare cancers and in small countries; it far exceeds the professional lifespan of a medical doctor.
RARECAREnet项目更新了每个欧洲国家198种罕见癌症的负担估计。由于怀疑数据不足可能影响统计分析的可靠性，我们采用贝叶斯方法来估计这些癌症的发病率。
我们分析了来自27个欧洲国家的83个基于人群的癌症登记处提供的2000 - 2007年诊断出的约200万例罕见癌症。我们将基于RARECAREnet所有可用数据计算得出的欧洲发病率（IRs）视为有效的先验信息，与各国特定的观察数据合并。因此，我们提供了：（1）每个国家IRs的贝叶斯估计值以及罕见癌症每年的病例数；（2）观察到一例新病例所需的预期年数（T）；（3）决定何时使用贝叶斯方法的实用标准。
贝叶斯估计值与经典估计值差异不大；差异较大（>10%）的情况从冰岛的77种罕见癌症到英国的14种不等。人口越少，需要采用贝叶斯方法的罕见癌症数量就越多。对于研究期间一个国家中观察病例少于150例的癌症，贝叶斯估计很有用；这种情况大多发生在该国人口较少时。
首次计算了每个欧洲国家每种罕见癌症的IRs贝叶斯估计值以及每年的预期病例数。此外，指标T对于传达极罕见癌症和小国的发病率估计很有用；它远远超过了一名医生的职业寿命。
