Understanding Differences in Cancer Survival between Populations: A New Approach and Application to Breast Cancer Survival Differentials between Danish Regions

Regional cancer incidence and survival in Denmark

BACKGROUND

Potential regional differences in cancer incidence and survival would demand targeted interventions to decrease cancer related death.

METHODS

This descriptive cohort study provides an overview of regional cancer incidence and relative survival (RS) in Denmark during 2007-2021. National cancer incidence and RS estimates were calculated similar to the official statistics for the Danish Cancer Registry. Specifically, we estimated age-standardized (World) cancer incidence rates (ASR), and RS in 3-year periods by sex, and the five regions of Denmark (i.e., Region of Northern Denmark, Central Denmark Region, Region of Southern Denmark, Region Zealand, and Capital Region).

RESULTS

We identified 578,107 incident cancers in Denmark during 2007-2021, of which 124 123 were diagnosed in 2019-2021. Small fluctuations were seen in ASR for cancer overall in all five regions during 2007-2018, followed by decreasing trends in 2019-2021. Men exhibited higher ASRs than women. Consistent improvements in 1- and 5-year RS were seen during the study period in all regions. However, for patients diagnosed in 2019-2021, the 5-year RS levelled off. These patients experienced 1-year RS of 83 % among men and 84 % among women, and the 5-year RS was also similar between sexes (men: 67 %, women: 70 %, overall: 68 %). Region Zealand generally presented lower RS estimates for both sexes combined.

CONCLUSION

Cancer survival improved between 2007 and 2021 in all Danish regions for both sexes. However, the improvements in cancer survival appeared to have levelled off in the most recent period, 2019-2021. For both sexes, the lowest survival was suggested for Region Zealand.

Investigating the impact of COVID-19 on patients with cancer from areas of conflict within the MENA region treated at King Hussein Cancer Center

Background

There is a paucity of evidence regarding the impact of COVID-19 on cancer care among refugees or patients from areas of conflict. Cancer care for these populations remains fragmented due to resource scarcity and limited infrastructure.

Aims

To explore the effect of COVID-19 on cancer care among patients from areas of conflict treated at King Hussein Cancer Center (KHCC).

Methodology

We performed a retrospective chart review of all patients from areas of conflict, treated at KHCC from 2018 to 2021. Patients' demographics and clinical characteristics are presented in the form of descriptive statistics. Interrupted Time Series (ITS) analysis was utilized to investigate the impact of COVID-19 on the number of admissions throughout the study's period.

Results

A total of 3317 patients from areas of conflict were included in the study. Among these, 1546 were males (46.6%) while 1771 (53.4%) were female. Libyans (34.6%), Palestinians (24.8%), Iraqis (24.5%), Syrians (15.3%), and Sudanese patients (0.9%) constituted our study sample. ITS analysis demonstrated that the start of the COVID-19 lockdown significantly decreased admissions by 44.0% (p = 0.020), while the end of the COVID-19 restriction significantly improved admissions by 43.0% (p = 0.023). Among those with available SEER stages, more than a quarter of patients had distant metastasis (n = 935, 28.2%) irrespective of age and biological sex. Advanced presentations during 2020 had approximately a 16% and 6% increase compared to 2018 and 2019, respectively. Breast cancer (21.4%), hematolymphoid cancers (18.1%), and cancers of the digestive system (16.5%) were the most common cancers among our cohort.

Conclusion

Restrictions associated with COVID-19 had a significant effect on the number of admissions of patients from areas of conflict. In the long term, this effect may impact the survival outcomes of affected patients.

Regional variation in cancer survival in Norway

BACKGROUND

Cancer services in Norway are intended to provide high quality services and equal access for all citizens. Still, regional variation in cancer survival has been reported. Currently, the public hospitals are organized in Health Trusts (HTs), respectively within one of four regional trusts (RHTs). We aimed to evaluate the extent and rank pattern of regional and intraregional variation in cancer survival systematically over the last three decades. We postulated that organizational reforms during this period might have modulated the variation.

METHODS

Excess hazard ratios (EHR) of death from cancer were estimated for all individuals identified in The Cancer Registry of Norway as diagnosed with cancer from 1984 to 2018. The model covariates included continuous age at diagnosis, sex, cancer site, stage, 5-year time period of diagnosis and place of residence. In addition to analyses for all cancers combined, selected cohorts with predominantly centralized vs. not centralized primary surgery were evaluated.

RESULTS

For all cancer sites combined and for the centralized surgery cohort, the range of variation in EHR among the four regions was in the order of 0.10. The ranks among the regions were fairly consistent over time. For the not centralized surgery cohort, the range of inter-regional EHR-variation was in the order of 0.10 - 0.15, with no consistent ranks. Intra-regionally, the ranges of EHR-variation were similar, but with more complex rank patterns.

CONCLUSIONS

The range of inter- and intra-regional variation in cancer survival was minor, as compared to the general improvement in cancer survival in the period, with no evidence of effect from organizational reforms on regional variation.

Stagnation of life expectancy in Korea in 2018: A cause-specific decomposition analysis

According to the most recent annual report released by Korea Statistics, the life expectancy at birth (for both sexes) in 2018 was 82.7 years, an increase of 0.0 years over 2017, reflecting the first stagnation in life expectancy since 1960. In this study, a time-series analysis was conducted of trends in life expectancy from 2003 to 2018, and causes of death were analyzed using the Kannisto-Thatcher method and the Arriaga decomposition method. The time trend analysis of yearly life expectancy changes indicated that, in Korea, there was a tendency for the yearly increase in life expectancy between 2003 and 2018 to decrease by 0.0211 years per calendar year. The contribution of cardiovascular diseases, the most important contributor to the life expectancy increase in Korea, gradually decreased over this period. The contribution of cardiovascular diseases to the life expectancy increase was 0.506 years in 2003-2006, but this contribution decreased to 0.218 years in 2015-2018. The positive contributions of ill-defined causes and external causes to life expectancy increase detected in previous periods were not evident in 2015-2018. Diseases of the respiratory system made the largest negative contribution both between 2015 and 2018 and between 2017-2018. The life expectancy stagnation in 2018 could be understood as the combined effect of (a) decreasing momentum in the increase of life expectancy and (b) a chance event in 2018 involving life expectancy. Currently, it is difficult to judge whether the stagnation of life expectancy in 2018 is temporary, and further analyses of life expectancy and contributing causes of death in the future are needed.

Monitoring trends and differences in COVID-19 case-fatality rates using decomposition methods: Contributions of age structure and age-specific fatality

The population-level case-fatality rate (CFR) associated with COVID-19 varies substantially, both across countries at any given time and within countries over time. We analyze the contribution of two key determinants of the variation in the observed CFR: the age-structure of diagnosed infection cases and age-specific case-fatality rates. We use data on diagnosed COVID-19 cases and death counts attributable to COVID-19 by age for China, Germany, Italy, South Korea, Spain, the United States, and New York City. We calculate the CFR for each population at the latest data point and also for Italy, Germany, Spain, and New York City over time. We use demographic decomposition to break the difference between CFRs into unique contributions arising from the age-structure of confirmed cases and the age-specific case-fatality. In late June 2020, CFRs varied from 2.2% in South Korea to 14.0% in Italy. The age-structure of detected cases often explains more than two-thirds of cross-country variation in the CFR. In Italy, the CFR increased from 4.2% to 14.0% between March 9 and June 30, 2020, and more than 90% of the change was due to increasing age-specific case-fatality rates. The importance of the age-structure of confirmed cases likely reflects several factors, including different testing regimes and differences in transmission trajectories; while increasing age-specific case-fatality rates in Italy could indicate other factors, such as the worsening health outcomes of those infected with COVID-19. Our findings lend support to recommendations for data to be disaggregated by age, and potentially other variables, to facilitate a better understanding of population-level differences in CFRs. They also show the need for well-designed seroprevalence studies to ascertain the extent to which differences in testing regimes drive differences in the age-structure of detected cases.

Monitoring trends and differences in COVID-19 case-fatality rates using decomposition methods: Contributions of age structure and age-specific fatality

The population-level case-fatality rate (CFR) associated with COVID-19 varies substantially, both across countries at any given time and within countries over time. We analyze the contribution of two key determinants of the variation in the observed CFR: the age-structure of diagnosed infection cases and age-specific case-fatality rates. We use data on diagnosed COVID-19 cases and death counts attributable to COVID-19 by age for China, Germany, Italy, South Korea, Spain, the United States, and New York City. We calculate the CFR for each population at the latest data point and also for Italy, Germany, Spain, and New York City over time. We use demographic decomposition to break the difference between CFRs into unique contributions arising from the age-structure of confirmed cases and the age-specific case-fatality. In late June 2020, CFRs varied from 2.2% in South Korea to 14.0% in Italy. The age-structure of detected cases often explains more than two-thirds of cross-country variation in the CFR. In Italy, the CFR increased from 4.2% to 14.0% between March 9 and June 30, 2020, and more than 90% of the change was due to increasing age-specific case-fatality rates. The importance of the age-structure of confirmed cases likely reflects several factors, including different testing regimes and differences in transmission trajectories; while increasing age-specific case-fatality rates in Italy could indicate other factors, such as the worsening health outcomes of those infected with COVID-19. Our findings lend support to recommendations for data to be disaggregated by age, and potentially other variables, to facilitate a better understanding of population-level differences in CFRs. They also show the need for well-designed seroprevalence studies to ascertain the extent to which differences in testing regimes drive differences in the age-structure of detected cases.