Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, Maryland.
Azores Cancer Registry, Azores Oncological Centre, Portugal.
Cancer Epidemiol Biomarkers Prev. 2019 Sep;28(9):1544-1551. doi: 10.1158/1055-9965.EPI-19-0125. Epub 2019 Jun 20.
We investigated differences in net cancer survival (survival observed if the only possible cause of death was the cancer under study) estimated using new approaches for relative survival (RS) and cause-specific survival (CSS).
We used SEER data for patients diagnosed in 2000 to 2013, followed-up through December 31, 2014. For RS, we used new life tables accounting for geography and socio-economic status. For CSS, we used the SEER cause of death algorithm for attributing cancer-specific death. Estimates were compared by site, age, stage, race, and time since diagnosis.
Differences between 5-year RS and CSS were generally small. RS was always higher in screen-detectable cancers, for example, female breast (89.2% vs. 87.8%) and prostate (98.5% vs. 93.7%) cancers; differences increased with age or time since diagnosis. CSS was usually higher in the remaining cancer sites, particularly those related to specific risk factors, for example, cervix (70.9% vs. 68.3%) and liver (20.7% vs. 17.1%) cancers. For most cancer sites, the gap between estimates was smaller with more advanced stage. RS is the preferred approach to report cancer survival from registry data because cause of death may be inaccurate, particularly for older patients and long-term survivors as comorbidities increase challenges in determining cause of death. However, CSS proved to be more reliable in patients diagnosed with localized disease or cancers related to specific risk factors as general population life tables may not capture other causes of mortality.
Different approaches for net survival estimation should be considered depending on cancer under study.
我们研究了使用新的相对生存率(RS)和病因特异性生存率(CSS)方法估计的净癌症生存率(如果唯一可能的死因是研究中的癌症,则观察到的生存率)的差异。
我们使用了 2000 年至 2013 年诊断并随访至 2014 年 12 月 31 日的 SEER 数据。对于 RS,我们使用了新的生命表,这些生命表考虑了地理位置和社会经济状况。对于 CSS,我们使用了 SEER 死因算法来归因于癌症特异性死亡。按部位、年龄、分期、种族和诊断后时间对估计值进行了比较。
5 年 RS 和 CSS 之间的差异通常较小。RS 在可筛查癌症中始终较高,例如女性乳腺癌(89.2%对 87.8%)和前列腺癌(98.5%对 93.7%);差异随年龄或诊断后时间的增加而增加。在其余癌症部位,CSS 通常更高,特别是与特定危险因素相关的癌症,例如宫颈癌(70.9%对 68.3%)和肝癌(20.7%对 17.1%)。对于大多数癌症部位,估计值之间的差距在分期更晚时较小。RS 是从登记数据报告癌症生存的首选方法,因为死因可能不准确,特别是对于老年患者和长期幸存者,随着合并症的增加,确定死因的挑战更大。然而,CSS 在诊断为局限性疾病或与特定危险因素相关的癌症的患者中更可靠,因为一般人群生命表可能无法捕捉其他死因。
应根据研究的癌症考虑不同的净生存估计方法。