Differences in Cancer Survival with Relative versus Cause-Specific Approaches: An Update Using More Accurate Life Tables

Abstract

Background: 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). Methods: 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 socioeconomic 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. Results: 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. Conclusion: 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. Impact: Different approaches for net survival estimation should be considered depending on cancer under study.

Percutaneous microwave ablation versus surgical resection for ovarian cancer liver metastasis

“…The size and number of LM lesions may increase the difficulty of operation and fail to enlarge the safety margin, resulting in poor tumor control. Additionally, old age has always been one of the most important factors influencing patient survival, as confirmed in previous studies [27][28][29]. The limitation of this study is its retrospective design with a relatively small patient series.…”

“…The MWA group had similar preoperative ALT and AST levels but lower immediately postoperative ALT levels compared with the SR group. A large amount of evidence supports the concept that the risk of LTP and OS after MWA or SR are driven by unmodifiable patient-and tumor-related factors [23][24][25][26][27]. The size and number of LM lesions may increase the difficulty of operation and fail to enlarge the safety margin, resulting in poor tumor control.…”

Epidemiology and Survival Outcomes of Lung Cancer: A Population-Based Study

“…e relative survival rate represents the cumulative probability of a cancer patient who would have survived a given period compared to the comparable general population after adjusting for age, sex, and observed calendar year [18]. e presented 1-year, 3-year, and 5-year survival rates in each calendar year were estimated using the life table method [19]. e geographic variations in the prevalence and incidence of lung cancer in 2002 and in 2014 were also compared by dividing Taiwan into 21 administrative districts, including Keelung, Taipei city, New Taipei City, Taoyuan city, Hsinchu, Miaoli, Taichung city, Changhua, Yunlin, Nantou, Chiayi, Tainan city, Kaohsiung city, Pingtung, Yilan, Hualien, Taitung, Lianjiang, and offshore Penghu islets.…”

A Risk Assessment Tool for Predicting Fragility Fractures and Mortality in the Elderly

“…(7) The 1-year excess mortality after hip, femur, or pelvis fracture is also higher than the excess mortality for up to 5 years after the diagnosis of breast cancer in women and prostate cancer in men. (4,8) In addition to mortality, survivors after an initial fracture also have an increased risk of subsequent fracture, (5) increased dependence, and reduced quality of life. (6) It is thus critical to identify individualized risk of both fragility fracture and its related consequences to be able to make meaningful decisions about appropriate interventions to prevent not only the first fracture but also the deleterious consequences triggered by the first fracture.…”