Study populations for period analyses of cancer survival

Impact of Waiting Times on Mortality in Advanced Stage Non-Small Cell Lung Cancer: A 10-Year Retrospective Cohort Study in Thailand

OBJECTIVE

This study investigated the relationship between mortality and waiting times from diagnosis to first treatment while also considering other important risk factors associated with mortality.

METHODS

This is a cohort study including 497 patients diagnosed with advanced stage non-small cell lung cancer (NSCLC) between 1st January 2012 and 31st December 2021. The risk factors and waiting periods were analysed to determine their association with mortality. The waiting periods were recorded based on the timeline of patient visits, including the time between the 1st visit and imaging, the time between the 1st visit and tissue diagnosis, the time between the procedure and tissue diagnosis, the time between tissue diagnosis and treatment and the time from the 1st visit until treatment. The data were assessed using Cox regression with time-varying covariates.

RESULTS

Waiting time for tissue diagnosis had a modest effect on mortality, a waiting time of more than four weeks indicated poor prognosis both in univariate and multivariate analyses [HR 1.48 (95%CI 1.18-1.87), p = < 0.01), adjusted HR 1.007 (95%CI 1.002-1.010), p = 0.02]. Waiting time for other services was not shown to be associated with mortality. The mortality rate was 3 times higher in patients with poor ECOG performance status than good ECOG performance [adjusted HR 3.17(2.04-4.91)]. Patients with EGFR sensitizing mutation who were treated with EGFR TKI therapy had a lower risk of lung cancer death compared to those being treated with chemotherapy [adjusted HR 0.49 (0.33-0.72)].

CONCLUSION

Molecular testing for EGFR sensitizing mutation and the TKI treatment were fundamental changes that assisted in improving survival rates for patients diagnosed with advanced stage lung cancer over the 10-year period. However, poor ECOG performance status remained a strong risk factor for lung cancer death. Longer waiting time for tissue diagnosis might indicate a poor prognosis.

Survival trends in chronic lymphocytic leukemia across treatment eras: US SEER database analysis (1985-2017)

In this population-based study, we used the SEER database (1985-2015) to examine survival outcomes in chronic lymphocytic leukemia (CLL) patients followed up to the era of advanced treatments including targeted therapies. Data were extracted for patients 15 years or older with a primary diagnosis of CLL. A period analysis was performed to estimate 5- and 10-year relative survival rates for patients diagnosed during different calendar periods from 1985 to 2015. A mixture cure model was used to examine long-term survivors' proportions among patients diagnosed in 1985-2015 and for two cohorts diagnosed in 2000-2003, followed up to 2012 and 2004-2007, and followed up to 2015. Cox proportional hazard modeling was used for the two cohorts to estimate hazard ratios (HRs) of death adjusted for gender and age. The 5-year and 10-year age-adjusted relative survival rate ranged between 73.7 and 89.4% and from 51.6% to "not reached," respectively, for calendar periods of 1985-1989 to 2010-2014. The long-term survivor proportions varied by age and gender from 0 to 59%. The HRs (95%CI) for the 2004-2007 cohort in comparison to the 2000-2003 cohort were 0.58 (0.43-0.78), 0.58 (0.48-0.70), 0.57 (0.49-0.0.67), 0.68 (0.54-0.85), and 0.83 (0.68-1.02) for the age categories of 45-54, 55-64, 65-74, 75-84, and ≥ 85 years, respectively. Overall, relative survival improved significantly for CLL patients diagnosed between 1985 and 2015. These improvements were markedly better following the introduction of targeted therapies.

Temporal trends in childhood cancer survival in Egypt, 2007 to 2017: A large retrospective study of 14 808 children with cancer from the Children's Cancer Hospital Egypt

Childhood cancer is a priority in Egypt due to large numbers of children with cancer, suboptimal care and insufficient resources. It is difficult to evaluate progress in survival because of paucity of data in National Cancer Registry. In this study, we studied survival rates and trends in survival of the largest available cohort of children with cancer (n = 15 779, aged 0-18 years) from Egypt between 2007 and 2017, treated at Children's Cancer Hospital Egypt-(CCHE), representing 40% to 50% of all childhood cancers across Egypt. We estimated 5-year overall survival (OS) for 14 808 eligible patients using Kaplan-Meier method, and determined survival trends using Cox regression by single year of diagnosis and by diagnosis periods. We compared age-standardized rates to international benchmarks in England and the United States, identified cancers with inferior survival and provided recommendations for improvement. Five-year OS was 72.1% (95% CI 71.3-72.9) for all cancers combined, and survival trends increased significantly by single year of diagnosis (P < .001) and by calendar periods from 69.6% to 74.2% (P < .0001) between 2007-2012 and 2013-2017. Survival trends improved significantly for leukemias, lymphomas, CNS tumors, neuroblastoma, hepatoblastoma and Ewing Sarcoma. Survival was significantly lower by 9% and 11.2% (P < .001) than England and the United States, respectively. Significantly inferior survival was observed for the majority of cancers. Although survival trends are improving for childhood cancers in Egypt/CCHE, survival is still inferior in high-income countries. We provide evidence-based recommendations to improve survival in Egypt by reflecting on current obstacles in care, with further implications on practice and policy.

Estimation of age-standardized net survival, even when age-specific data are sparse

BACKGROUND

Age-standardization is vital in international comparison studies of cancer patient survival, but standard approaches can fail to produce estimates in the case of sparsity.

METHODS

The purpose of this paper is to demonstrate that using a standardization pre-weighting approach is a viable alternative approach for external age-standardization in population-based cancer data and performs well in cases of sparsity. We further de;1;scribe how the pre-weighting approach to age-standardization can be coupled with the Pohar Perme estimator in both a cohort and period analysis setting. For period analysis, we compare approaches for defining the internal age distribution. We use SEER public use data to illustrate our approach and estimate survival for Connecticut and by race to create a scenario with sufficient sparsity.

RESULTS

The pre-weighting approach gives comparable estimates to traditional age-standardization in cases with sufficient data and produces estimates throughout follow-up in cases of sparsity when a traditional approach would fail.

CONCLUSION

International comparison studies and other national population-based survival studies that need to age-standardize estimates for comparability purposes should adopt the Pohar Perme estimator with pre-weighting. This approach avoids issues of non-estimation in the case of sparsity and will allow more consistent comparisons across the produced estimates.

InterPreT cancer survival: A dynamic web interactive prediction cancer survival tool for health-care professionals and cancer epidemiologists

BACKGROUND

There are a variety of ways for quantifying cancer survival with each measure having advantages and disadvantages. Distinguishing these measures and how they should be interpreted has led to confusion among scientists, the media, health care professionals and patients. This motivates the development of tools to facilitate communication and interpretation of these statistics.

METHODS

"InterPreT Cancer Survival" is a newly developed, publicly available, online interactive cancer survival tool targeted towards health-care professionals and epidemiologists (http://interpret.le.ac.uk). It focuses on the correct interpretation of commonly reported cancer survival measures facilitated through the use of dynamic interactive graphics. Statistics presented are based on parameter estimates obtained from flexible parametric relative survival models using large population-based English registry data containing information on survival across 6 cancer sites; Breast, Colon, Rectum, Stomach, Melanoma and Lung.

RESULTS

Through interactivity, the tool improves understanding of various measures and how survival or mortality may vary by age and sex. Routine measures of cancer survival are reported, however, individualised estimates using crude probabilities are advocated, which is more appropriate for patients or health care professionals. The results are presented in various interactive formats facilitating understanding of individual risk and differences between various measures.

CONCLUSIONS

"InterPreT Cancer Survival" is presented as an educational tool which engages the user through interactive features to improve the understanding of commonly reported cancer survival statistics. The tool has received positive feedback from a Cancer Research UK patient sounding board and there are further plans to incorporate more disease characteristics, e.g. stage.

Critical Points for Interpreting Patients' Survival Rate Using Cancer Registries: A Literature Review

Background

Survival rate is used to develop cancer control plans. However, there are limitations and biases when interpreting patient survival rate data. This study aimed to identify and account for potential biases and/or limitations on estimating survival rate to enable more effective control of cancer.

Methods

The authors searched PubMed from December 2010 to December 2015 for articles that investigated or described biases in estimating patient survival using cancer registries. Articles that only described the tendency of survival rate and investigated relationships between patient characteristics, treatment, and survival rate were excluded.

Results

In total, 50 articles met the inclusion criteria. The identified potential biases were categorized into three areas, as follows: 1) the quality of registry data (eg, the completeness of cancer patients, accuracy of data, and follow-up rates); 2) limitations related to estimated methods of survival rates (eg, misclassification of cause of death for cause-specific survival rate or a lack of comparability of background mortality for relative survival rate); and 3) the comparability of survival rates among different groups (eg, age-adjustment or patients with multiple cancers).

Conclusion

We concluded that survival rate can be suitable for answering questions related to health policy and research. Several factors should be considered when interpreting survival rates estimated using cancer registries.

Restriction to period of interest improves informative value of death certificate only proportions in period analysis of cancer survival

OBJECTIVES

The proportion of cases registered by death certificates only (DCO) is a widely used indicator for potential bias in cancer survival studies. Period analysis is increasingly used to derive up-to-date cancer survival estimates. We aimed to assess whether reported DCO proportions should be restricted to the specific recent calendar period ("restricted period") or refer to all diagnosis years of included patients ("full period").

STUDY DESIGN AND SETTING

We assessed correlations of bias in period survival estimates resulting from DCO cases with DCO proportions in the restricted and full period, respectively. We used cancer registry data to simulate bias and DCO proportions resulting from various patterns of underreporting of deceased cases. We show results for six common cancers with very different prognosis and five different age groups.

RESULTS

In all scenarios, the expected bias was highly correlated with expected DCO proportions in both periods, but correlations were consistently higher with DCO proportions in the restricted period.

CONCLUSION

In period analyses of cancer survival, DCO proportions for the restricted period of specific interest are a better indicator of potential bias due to underreporting of deceased cases than DCO proportions for all years of diagnosis of included patients.