The Relationship Between Human Development Index and Its Components with Thyroid Cancer Incidence and Mortality: Using the Decomposition Approach

Exploring temporal trends and influencing factors for thyroid cancer in Guangzhou, China: 2004-2018

PURPOSE

Describe and analyze the trends of thyroid cancer incidence and mortality in Guangzhou, explore the potential influencing factors, and provide evidence for the government to formulate prevention and treatment measures.

METHODS

Incident and death cases of thyroid cancer were retrieved from the Guangzhou cancer registry. The joinpoint regression models were used to estimate the incidence and mortality trends. Age-period-cohort models were used to estimate the age, period, and cohort effects on the time trends. Grey correlation analysis was performed to explore possible connections between thyroid cancer and social factors.

RESULTS

A total of 15,955 new cases of thyroid cancer were registered in Guangzhou during 2004-2018, the age-standardized incidence rate (ASIR) of thyroid cancer increased from 4.29/105 in 2004 to 22.36/105 in 2018, with the average annual percentage change (AAPC) of 13.40%. The overall increase can be attributed to the increase in the incidence of papillary thyroid carcinoma (PTC), which was dominated by tumors <2 cm. The ASIR was higher in women (16.12/105) compared to men (5.46/105), and young and middle-aged individuals had higher incidence rates than older people. The number of thyroid cancer deaths registered between 2010 and 2018 was 356, and the age-standardized mortality rates (ASMRs) were stable (approximately 0.42/105). Men's ASMR (0.34/105) and women's (0.49/105) were similar, and those 60 and older had greater mortality. The period and cohort relative risks showed an overall increasing trend. Furthermore, there was a strong positive correlation between the ASIRs and social determinants.

CONCLUSIONS

During the study period, the incidence rate of thyroid cancer among young and middle-aged people in Guangzhou showed a rapidly increasing trend, and the mortality was relatively stable. In the future, more effective preventive measures should be taken for this age group to reduce the burden of disease and avoid overdiagnosis.

Artificial night light and thyroid cancer

BACKGROUND

The occurrence of thyroid cancer (TC) has increased in recent decades. Exposure to outdoor artificial light at night (ALN) is associated with an increased risk of cancer.

AIM

To investigated the impact of ALN, as a significant environmental pollutant, on TC incidence worldwide.

METHODS

The assessment involved analyzing satellite ALN data in conjunction with TC incidence data [adjusted standardized rate (ASR)], while considering the quality of cancer registries (QCR), gross domestic product (GDP) per person, and health expenditure per person (HEP) for each country.

RESULTS

Results indicated a correlation between higher ASR and ALN exposure percentages, particularly in countries with higher GDP or HEP quartiles (all P< 0.05). Significant differences in ASR were observed across QCR levels, both high and low quality (all P < 0.05), but not in countries without registry activity. However, when evaluating ASR against ALN exposure percentages while considering GDP/HEP quartiles or QCR levels, no significant associations were found (all P > 0.10).

CONCLUSION

The findings suggest a potential link between higher GDP and adverse health conditions, serving as possible risk factors for TC, rather than a direct association with ALN. Limitations include the use of cross-sectional data, temporal misalignment, and reliance on ALN as a socioeconomic proxy. It is proposed that light pollution might be connected to a lifestyle conducive to carcinogenesis. Additionally, the presence of higher GDP/HEP could enhance access to diagnostic resources, potentially facilitating TC diagnosis and inclusion in cancer registries.

Survival rate of thyroid cancer in the Asian countries: a systematic review and meta-analysis study

PURPOSE

Overall, thyroid cancer is the most common endocrine malignancy. This cancer is fifth most common cancer among adult women and the second most common cancer in women over 50 years old and it occurs in women 3 times more than men. The present systematic review and meta-analysis were designed with the aim of determining the 5-year survival rate of thyroid cancer in Asian countries in 2022.

METHODS

The current study is a systematic review and meta-analysis of thyroid cancer survival rates in Asian countries. Researchers in the study searched for articles published in six international databases: PubMed/Medline, EMBASE, Scopus, Google Scholar, ISI (Web of Knowledge), and ProQuest until July 03, 2022. A checklist (The Newcastle-Ottawa Quality Assessment Form) has been prepared in previous studies to evaluate the quality of articles.

RESULTS

In general, 38 articles were entered for the meta-analysis. The 5-year survival rate was 95.3%, with a 95% confidence interval of 93.5% to 96.6%. The year of study is a cause of variability in results of 5-year (Reg Coef = 0.145, P < 0.001). According to the results, an increased survival rate across the study period was observed. Human Development Index was a cause of variability in results of 5-year survival rates (Reg Coef = 12.420, P < 0.001). The results of Table 2 showed that women have 4% more 5-year survival rate than men (Hazard ratio: 1.05 CI: 95% 1.04-1.06)).

CONCLUSION

In general, the 5-year survival of thyroid cancer in Asian countries was higher than in European countries, but it is at a lower level than in the United States.

An Assessment of Systemic Factors and COVID-19 Mortality in Africa

Objectives: The objective of this study was to examine the association between several country-level systemic indices and the deaths from COVID-19 across African countries.

Method: Regression analyses were conducted to test the association between selected indices and deaths from COVID-19 across African countries. All tests were run at the α = 0.05 level of significance.

Result: We found a statistically significant correlation between total COVID-19 deaths per million and Stringency Index (p-value <0.001) and Human Development Index (p-value <0.001). Multiple regression analysis showed that Stringency Index was the only variable that remained significant when other factors are controlled for in the model.

Conclusion: Countries in Africa with poorer governance, inadequate pandemic preparedness and lower levels of development have unexpectedly fared better with respect to COVID-19 deaths mainly because of having a younger population than the countries with better indices.

‘Exploring socioeconomic status as a global determinant of COVID-19 prevalence, using statistical, exploratory data analytic, and supervised machine learning techniques.’ (Preprint)

Background

The COVID-19 pandemic represents the most unprecedented global challenge in recent times. As the global community attempts to manage the pandemic in the long term, it is pivotal to understand what factors drive prevalence rates and to predict the future trajectory of the virus.

Objective

This study had 2 objectives. First, it tested the statistical relationship between socioeconomic status and COVID-19 prevalence. Second, it used machine learning techniques to predict cumulative COVID-19 cases in a multicountry sample of 182 countries. Taken together, these objectives will shed light on socioeconomic status as a global risk factor of the COVID-19 pandemic.

Methods

This research used exploratory data analysis and supervised machine learning methods. Exploratory analysis included variable distribution, variable correlations, and outlier detection. Following this, the following 3 supervised regression techniques were applied: linear regression, random forest, and adaptive boosting (AdaBoost). Results were evaluated using k-fold cross-validation and subsequently compared to analyze algorithmic suitability. The analysis involved 2 models. First, the algorithms were trained to predict 2021 COVID-19 prevalence using only 2020 reported case data. Following this, socioeconomic indicators were added as features and the algorithms were trained again. The Human Development Index (HDI) metrics of life expectancy, mean years of schooling, expected years of schooling, and gross national income were used to approximate socioeconomic status.

Results

All variables correlated positively with the 2021 COVID-19 prevalence, with R² values ranging from 0.55 to 0.85. Using socioeconomic indicators, COVID-19 prevalence was predicted with a reasonable degree of accuracy. Using 2020 reported case rates as a lone predictor to predict 2021 prevalence rates, the average predictive accuracy of the algorithms was low (R²=0.543). When socioeconomic indicators were added alongside 2020 prevalence rates as features, the average predictive performance improved considerably (R²=0.721) and all error statistics decreased. Thus, adding socioeconomic indicators alongside 2020 reported case data optimized the prediction of COVID-19 prevalence to a considerable degree. Linear regression was the strongest learner with R²=0.693 on the first model and R²=0.763 on the second model, followed by random forest (0.481 and 0.722) and AdaBoost (0.454 and 0.679). Following this, the second model was retrained using a selection of additional COVID-19 risk factors (population density, median age, and vaccination uptake) instead of the HDI metrics. However, average accuracy dropped to 0.649, which highlights the value of socioeconomic status as a predictor of COVID-19 cases in the chosen sample.

Conclusions

The results show that socioeconomic status is an important variable to consider in future epidemiological modeling, and highlights the reality of the COVID-19 pandemic as a social phenomenon and a health care phenomenon. This paper also puts forward new considerations about the application of statistical and machine learning techniques to understand and combat the COVID-19 pandemic.

Analysis of Race and Gender Disparities in Incidence-Based Mortality in Patients Diagnosed with Thyroid Cancer from 2000 to 2016

Background

Well-differentiated thyroid cancer has better outcomes compared to undifferentiated/anaplastic thyroid cancer. The incidence of well-differentiated thyroid cancer is known to be more in women whereas it is approximately the same in both genders for anaplastic thyroid cancer. The variability of incidence-based mortality across gender in the context of race has not been studied. This study analyzes the rates of incidence-based mortality from the years 2000 to 2016 amongst both the genders in four racial groups.

Methods

The Surveillance, Epidemiology, and End Results (SEER) database was utilized to conduct a nation-wide analysis for the years 2000 to 2016. Incidence-based mortality for all stages of well-differentiated and undifferentiated thyroid cancer was queried and the results were grouped by race (Caucasian/White, African American/Black, American Indian/Alaskan Native and Asian/Pacific Islander) and gender. All stages and ages were included in the analysis. Two sample t-test was used to determine statistically significant difference between various subgroups.

Results

Incidence-based mortality rates (per 100,000) for well-differentiated and undifferentiated thyroid cancer for all races and both the genders were calculated. The incidence-based mortality rates for both genders are approximately the same despite a 2–3:1 difference in incidence. Anaplastic thyroid cancer has a higher mortality rate in Caucasian and Asian/Pacific Islander women compared to men despite an equal ratio in incidence. As expected, the mortality rates of anaplastic thyroid cancer were significantly higher compared to well-differentiated cancer across all races and genders. Also, Asian/Pacific Islander women have a higher rate of mortality compared to both the genders of Caucasian and African American races.

Conclusion

Incidence-based mortality for anaplastic thyroid cancer is higher in women in all races whereas there is no difference in mortality between men and women for well-differentiated thyroid cancer. This is divergent from the incidence ratios noted in these malignancies. In the context of increasing incidence of thyroid cancer for the past few decades, this data suggests that additional resources may be devoted to decreasing the disparity of mortality in this gender.

Distribution of Breast Cancer Subtypes Among Nigerian Women and Correlation to the Risk Factors and Clinicopathological Characteristics

Background

Breast cancer in African women differs from the Caucasian. Understanding the profile of Nigerian women with breast cancer will help with preventive measures and treatment. This study focused on the clinico-pathological characteristics, with risk factors of breast cancer patients in Nigeria.

Methods

Newly diagnosed female patients with breast cancer were assessed over 12 months. Patients were reviewed using a predesigned proforma which focused on socio-demographic information, clinical information, risk factors and tumor biology.

Results

A total of 251 women were identified; their mean age was 46 years. More than half (62.5%) are premenopausal at presentation, 37.8% with Eastern Cooperative Oncology Group (ECOG) score of 0 and right side (50.2%) as the most common primary site of disease. Less than half of them (43.0%) are estrogen receptor (ER) positive, 27.9% are progesterone receptor (PR) positive, 43.8% and 47.4% are hormone receptor positive and triple negative, respectively. Most patients presented at the latter stage of the disease, stage III (66.9%) and stage IV (18.3%). Only 15.9% are well differentiated and almost all (92.8%) had invasive ductal histological type. Obesity (66.2%) and physical inactivity (41.9%) are the most common risk factors for the disease. A significant relationship was found between immunohistochemistry status and family history of breast cancer, tumor site, previous breast surgery, previous lump and alcohol intake.

Conclusion

Findings from this study showed that Nigerian breast cancer patients differ from their counterparts in the high human development index (H-HDI) countries in terms of the patients and disease characteristics. In view of this, prevention and treatment options should consider this uniqueness to ensure better outcome.