Interpreting survival differences and trends
Interpreting survival differences and trends
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DOI：
10.1177/030089169708300105
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发表时间：
1997-01-01
期刊：
影响因子：
1.9
通讯作者：
Capocaccia, R
中科院分区：
文献类型：
--
作者：
Berrino, F;Micheli, A;Capocaccia, R
自1990年以来，欧洲以人口为基础的癌症登记机构(EUROCARE项目)之间开展了一项协调行动，目的是确定欧洲癌症患者的存活率是否存在差异，以及造成这种差异的原因。对于诊断时的疾病阶段是主要预后因素的癌症部位(如乳腺癌、胃癌和结肠癌)，存活率实际上存在差异。然而，对于大多数癌症部位来说，存活率随着时间的推移而增加，不同国家的存活率倾向于向更高的值趋同。解读生存差异和趋势并非易事。通过更好的治疗或预期诊断来推迟死亡，可能会获得更长的生存时间。然而，更早的诊断可能会也可能不会使治疗在推迟死亡方面更有效。分期或分期调整后的存活率的计算不足以解释存活率差异，因为分期程序会随着时间的推移而改变，并且在不同的医院和国家可能会有所不同。除了早期诊断和更有效的治疗外，许多因素可能会对生存估计产生偏差。这些因素可分为(至少部分)可在分析中控制的因素，例如其他原因的死亡率、人口因素、诊断时期、不同的统计方法，以及取决于癌症登记数据有效性的因素，例如疾病的定义、登记的穷尽性和质量、后续行动的完整性、诊断日期的定义以及疾病阶段的定义，包括用于确定阶段的诊断程序。为了帮助理清早期诊断和更好的治疗的影响，正在开发几种统计方法：对相对生存数据进行多变量分析，分别估计治愈患者的比例和注定死亡的患者的生存时间的新模型分析，以及在诊断和分期过程中标准化收集分期信息。
Since 1990 a concerted action between European population-based cancer registries (the EUROCARE project) has been carried out with the aims of establishing whether there are differences in cancer patient survival in Europe, and the reasons for such differences. Survival differences actually exist for cancer sites for which the stage of disease at diagnosis is the major prognostic factor (such as breast, stomach and colon cancer). However, for most cancer sites, survival increases over time and the survival rates of different countries tend to converge towards higher values. Interpreting survival differences and trends is not an easy task. Longer survival may be achieved by postponing death through better treatment or by anticipating diagnosis. However, an earlier diagnosis may or may not make a treatment more effective in postponing death. The computation of stage-specific or stage-adjusted survival is not sufficient for interpretation of survival differences, because staging procedures change over time and may vary in different hospitals and countries. In addition to an early diagnosis and more effective treatment, a number of factors may bias survival estimates. They may be classified into factors that can be controlled in the analysis (at least partially), such as mortality from other causes, demographic factors, epoch of diagnosis, different statistical methodology, and factors depending on the validity of cancer registry data, such as definition of the illness, exhaustiveness and quality of registration, completeness of follow-up, definition of the date of diagnosis, and definition of disease stage including the diagnostic procedure used to establish stage. To help disentangle the effects of early diagnosis and better treatment, several statistical approaches are being developed: multivariate analysis on relative survival data, new modeling analysis to separately estimate the proportion of cured patients and the length of survival for those patients destined to die, and the standardized collection of information on stage at diagnosis and staging procedures.