Are socio-economic inequalities in breast cancer survival explained by peri-diagnostic factors?

Association Between Physical Activity Levels in Different Domains and Cardiac Autonomic Modulation in Breast Cancer Survivors: A Cross-sectional Study

BACKGROUND

Breast cancer survivors frequently present cardiac autonomic dysfunction. Physical activity (PA) has been associated with better cardiac autonomic modulation (CAM) in breast cancer survivors.

OBJECTIVE

This study aimed to analyze the association between CAM and PA levels performed in different domains (work and occupation, sport and exercise, and leisure time and commuting) in breast cancer survivors.

METHODS

This is a cross-sectional study with 99 breast cancer survivors (age, 55.3 ± 10.4 years). Cardiac autonomic modulation was assessed by heart rate variability, and PA levels at work and occupation, sport and exercise, and leisure time and commuting were assessed using the Baecke PA questionnaire. The sum of these 3 domains provided the total PA. The Mann-Whitney test was used to compare CAM between active and inactive women in different domains of PA.

RESULTS

Cardiac autonomic modulation was similar between active and inactive women in the different domains ( P > .05). However, when considering the total PA, active breast cancer survivors presented higher SDNN (average standard deviation of all normal RR intervals) (20.0 ± 13.4 vs 28.8 ± 14.0; P = .008) and SD2 (standard deviation of the long-term intervals between consecutive heartbeats) indices (29.2 ± 17.3 vs 38.7 ± 19.9; P = .005) compared with their inactive counterparts.

CONCLUSION

Breast cancer survivors with higher total PA presented better CAM compared with their less active peers.

IMPLICATIONS FOR PRACTICE

The results of this study are promising and show the importance of increasing PA levels in different domains for the maintenance of cardiovascular health among breast cancer survivors.

A prognostic survival model for women diagnosed with invasive breast cancer in Queensland, Australia

PURPOSE

Prognostic models can help inform patients on the future course of their cancer and assist the decision making of clinicians and patients in respect to management and treatment of the cancer. In contrast to previous studies considering survival following treatment, this study aimed to develop a prognostic model to quantify breast cancer-specific survival at the time of diagnosis.

METHODS

A large (n = 3323), population-based prospective cohort of women were diagnosed with invasive breast cancer in Queensland, Australia between 2010 and 2013, and followed up to December 2018. Data were collected through a validated semi-structured telephone interview and a self-administered questionnaire, along with data linkage to the Queensland Cancer Register and additional extraction from medical records. Flexible parametric survival models, with multiple imputation to deal with missing data, were used.

RESULTS

Key factors identified as being predictive of poorer survival included more advanced stage at diagnosis, higher tumour grade, "triple negative" breast cancers, and being symptom-detected rather than screen detected. The Harrell's C-statistic for the final predictive model was 0.84 (95% CI 0.82, 0.87), while the area under the ROC curve for 5-year mortality was 0.87. The final model explained about 36% of the variation in survival, with stage at diagnosis alone explaining 26% of the variation.

CONCLUSIONS

In addition to confirming the prognostic importance of stage, grade and clinical subtype, these results highlighted the independent survival benefit of breast cancers diagnosed through screening, although lead and length time bias should be considered. Understanding what additional factors contribute to the substantial unexplained variation in survival outcomes remains an important objective.

Socio-economic inequalities in cancer survival: how do they translate into Number of Life-Years Lost?

BACKGROUND

We aimed to investigate the impact of socio-economic inequalities in cancer survival in England on the Number of Life-Years Lost (NLYL) due to cancer.

METHODS

We analysed 1.2 million patients diagnosed with one of the 23 most common cancers (92.3% of all incident cancers in England) between 2010 and 2014. Socio-economic deprivation of patients was based on the income domain of the English Index of Deprivation. We estimated the NLYL due to cancer within 3 years since diagnosis for each cancer and stratified by sex, age and deprivation, using a non-parametric approach. The relative survival framework enables us to disentangle death from cancer and death from other causes without the information on the cause of death.

RESULTS

The largest socio-economic inequalities were seen mostly in adults <45 years with poor-prognosis cancers. In this age group, the most deprived patients with lung, pancreatic and oesophageal cancer lost up to 6 additional months within 3 years since diagnosis than the least deprived. For most moderate/good prognosis cancers, the socio-economic inequalities widened with age.

CONCLUSIONS

More deprived patients and particularly the young with more lethal cancers, lose systematically more life-years than the less deprived. To reduce these inequalities, cancer policies should systematically encompass the inequities component.

Piloting a novel cancer care pathway: socioeconomic background as a barrier to access

BACKGROUND

The multidisciplinary diagnostic clinic (MDC) model for 'non-specific' symptoms has been piloted in the UK. We aimed to assess the degree to which the MDC pathway was influenced by socioeconomic factors.

METHODS

We collected data for all patients referred to the MDC from 01 January 2017 - 28 March 2019. Indices of multiple deprivation (IMD) scores were matched to patients' postcodes and referring general practitioner (GP) location. Socioeconomic data for MDC patients was compared with all other cancer patients diagnosed in the MDC's base hospital, Airedale General Hospital (AGH), in 2018. Statistical significance was tested using the Mann-Whitney U test and Spearman's rank correlation.

RESULTS

No significant difference was found between MDC pathway and the rest of AGH when comparing social deprivation of patients. There was a moderate negative correlation between the IMD associated with the location of GP premises and the number of referrals; practices in more deprived locations referred fewer patients (p≤0.025).

CONCLUSION

The MDC pathway referral rate seems to be affected by social deprivation in a similar manner to other cancer diagnosis pathways. Our work highlights the importance of engaging GP practices with socially deprived populations as the MDC programme is rolled out across the UK.

Disparities in Cancer-Related Avoidable Mortality by the Level of Area Deprivation in South Korea

Background: This study investigated trends in cancer-related avoidable (preventable and treatable) mortality and its association with area deprivation in Korea. Methods: Cancer-related avoidable mortality rates per 100,000 population between 2015 and 2019 were measured using the Causes of Death Statistics. Area Deprivation Index (ADI) was measured from the Population and Housing Census and information on other independent variables from the Korea Community Health Survey. The gap in avoidable mortality between the more and less deprived groups was expressed as rate ratios (RR) and absolute differences (ADs) with a 95 percent confidence interval (95% CI). The association between avoidable mortality and ADI was investigated through Poisson regression modelling. Results: The more deprived areas had higher avoidable (RR 1.15, 95% CI 1.13–1.17; AD 6.58, 95% CI 5.59–7.57) and preventable (RR 1.19, 95% CI 1.17–1.21; AD 6.22, 95% CI 5.38–7.06) mortality. The overall cancer-related avoidable mortality decreased but the gap between the more and less deprived groups did not decline significantly during the study period. The association between avoidable and preventable mortality and area deprivation remained significant after adjusting for variables, including area levels of smokers and alcohol drinkers. Conclusions: The gap in avoidable mortality signifies the importance of addressing related disparities in cancer.