The Correlation Between the Incidence Rate of Cutaneous Malignant Melanoma and the Incidence Rate of Thyroid Cancer in Eastern European Countries

Research Question: What is the correlation between the average incidence rate of cutaneous malignant melanoma (%) and the average incidence rate of thyroid cancer (%), in Eastern European Countries from 2010-2019?

Background

Growing up with a mother diagnosed with two diseases simultaneously, I have always been keen to understand the mechanics behind comorbid conditions. Particularly, I was interested in exploring the correlation between two multifactorial diseases (where both heritable and environmental factors play a role in their development) to understand whether there could be causative factors responsible for both diseases. After reading about male patients diagnosed with melanoma and their increased susceptibility to hypothyroidism (a condition where the thyroid gland doesn't produce sufficient hormones)[1], I was intrigued to explore whether melanoma patients have an increased risk of thyroid cancer—a different disease that also affects the thyroid gland. Whereas hypothyroidism is very common, thyroid cancer is extremely rare and has very few detectable symptoms[2]. By exploring the potential relationship between malignant melanoma and thyroid cancer, this could serve as crucial information in the medical field, for the early diagnosis of thyroid cancer as well as the development of new, complementary treatments.

Following some brief research into cutaneous malignant melanoma (CMM) and thyroid cancer, I discovered a common genetic component between the two—a mutation to the BRAF gene[3]. I was intrigued to explore the significance of this genetic relationship, in relation to its influence on an individual’s actual chance of developing both diseases and its accordance with clinical observations. This inspired my investigation of the correlation between the incidence rate of CMM and thyroid cancer. I chose to study the male population aged 50 to 69 in Eastern Europe because this group is most susceptible to melanoma (this is further explained in Table 2 below). The results of this investigation will thus be of greater significance as it applies to the populace most affected by the disease.

Cutaneous malignant melanoma is a type of skin cancer in which melanocytes, or cells that produce the pigment melanin, form a malignant tumour[4]. An affected individual can begin to experience an increase in the size of a mole, change in skin colour, itching, or skin breakdown. It most commonly occurs on the extremities for women, and on the back and neck for men. The primary cause of melanoma is ultraviolet (UV) radiation, from sun exposure and indoor tanning, which causes damage to the DNA. Other risk factors include pigmentary characteristics, a family history of melanoma, and immunosuppression. Melanoma is over 20 times more prevalent among whites than African Americans. The risk also increases in males and with age, with the average age of diagnosis at 63[5]. In the long run, the survival rate for patients with metastatic melanoma is only 5%, however, early detection of CMM can lead to a successful recovery. Surgical excision can also be used as an effective cure.

Thyroid cancer is a disease in which malignant cells form in the tissues of the thyroid[6]. The thyroid is a gland at the base of the throat (near the trachea) that is responsible for producing, storing and secreting thyroid hormones that help regulate bodily activities such as breathing and blood circulation[7]. Symptoms are frequently not present, however, some may experience swelling or a lump in the neck, and a hoarse voice. Factors that increase the risk of thyroid cancer include exposure to ionizing radiation, particularly in the neck area, and a family history of thyroid disease or cancer. “Studies have also shown an increased risk of certain types of thyroid cancer in geographic areas where there is a high incidence of goiters (enlarged thyroid glands) due to a lack of dietary iodine.”[8] As well, the risk increases aggressively with age (peak incidence rate is at age 65-69) and is more common among females[9]. The most common form of thyroid cancer is papillary thyroid cancer, which accounts for 90% of thyroid cancer cases.

Many human cancers have been linked to mutations in the BRAF gene[10]. Among the most frequent types are malignant melanoma (40% to 70%) and papillary thyroid cancers (45%). This mutation entails a point mutation at nucleotide 1799, in which the thymine base is replaced with adenine, leading to the amino acid valine (V) being substituted with glutamate (E) at codon 600. This mutation, referred to as the V600E mutation, causes the BRAF kinase protein which is normally involved in cell growth to be constitutively active—causing excessive cancer cell growth and the development of a tumour.

Hypothesis: If the average incidence rate of cutaneous malignant melanoma increases, then the average incidence rate of thyroid cancer should also increase - meaning a positive correlation between the two cancer types, because of the shared genetic cause suggested by the common BRAF gene mutation.

Variables

Table 1. Independent Variable (IV) and Dependent Variable (DV)

Variable

Justification

Method of Measurement

IV: Average incidence rate of cutaneous malignant melanoma (%)

On average, people are diagnosed with CMM at an earlier age (63yrs) than thyroid cancer (65-69yrs). So, to investigate the risk of CMM patients subsequently developing thyroid cancer, the incidences of thyroid cancer theoretically depends on the incidences of CMM—given that a relationship exists. This makes the incidence rate of CMM the independent variable.

The incidence rates of CMM and thyroid cancer for males aged 50 to 69, from 2010 to 2019, in 15 Eastern European countries (Bulgaria, Croatia, Czechia, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Russian Federation, Serbia, Slovakia, Slovenia, North Macedonia, and Moldova) will be used. The raw data is gathered from the Institute for Health Metrics and Evaluation (IHME).

DV: Average incidence rate of thyroid cancer (%)

As explained above, for the purposes of this investigation, the incidence rate of thyroid cancer will be dependent on that of CMM. This then allows the two variables to be directly plotted against each other, to find their correlation.

Table 2. Control Variables

Variable

Method of Control

Reason for Control

Gender

All data for the incidence numbers of both cancers are only of males.

Males are more susceptible to melanoma due to an average greater exposure to the sun but lower use of sun protection. Hormones are also different between genders, causing differences in the risk of thyroid cancer. Calculating male-specific incidence rates ensures that physiological differences between males and females do not influence the results, creating more accurate and reliable data.

Age group

All data for the incidence numbers of both cancers was selected specifically for the age group of 50 to 69 years.

As age increases, the risk of developing either melanoma or thyroid cancer increases, likely due to accumulated exposure to radiation. Using a specific age group ensures that only the subset of the population of interest is being studied and age-specific incidence rates can be calculated. The average age of diagnosis is 63 and 65-69, so the most suitable age group of 50-69 years was chosen.

Source of database for cancers and population

All data for incidence numbers and specific populations are from the same 1,250 censuses and 747 population registry location-years (IHME).

Different databases have varying data collection methods and biases, leading to wide variances. Using a consistent source to collect incidence numbers and populations ensures consistency and thus reliability among the data.

Total population size

All countries have a total population above one million (as of 2019).

Countries with low total populations may have a sample size too small and thus be an outlier, causing the data to be skewed and have large discrepancies. Restricting the population size above one million reduces biases caused by the sample size and increases the accuracy of the data.

Human Development Index (HDI) values

All countries have HDI values above 0.700 ⇒ high and very high values[11] (as of 2019).

The HDI is a measure of a country’s level of social and economic development, according to the average years of schooling, life expectancy, and gross national income. Countries with low HDI values are often correlated with low access to healthcare and poor administrative work, leading to skewed and unreliable data. Using only countries with high/very high HDI increases reliability and thus the accuracy of the data.

Geographic region

All data for incidence rates comes from Eastern European countries.

Different geographic regions have varying environmental factors, such as radiation exposure (i.e. sun irradiance), skin pigmentation, diet, and lifestyle activities, which all influence one’s susceptibility to either cancer. For example, Eastern Europe has one of the highest rates of thyroid cancer while Western Europe has one of the lowest[12]. Restricting the data to only Eastern Europe reduces variance and increases accuracy in the data.

Data Sources

Procedure:

  1. Visit the East European Countries' Committee to find the list of Eastern European Countries. Record in Table 3.
  2. Visit Human Development Reports to find the HDI values (2019) of each country found in step 1. Record in Table 4. Filter out any countries that have an HDI value below 0.700.
  3. Visit The World Bank to find the total population (2019) of each country. Record in Table 4. Filter out any countries that have a population below 1 million.
  4. Visit IHME - GBD Results Tool to find the number of incidences of CMM and thyroid cancer. Select the following filtering criteria and record the data in Table 5 and Table 6.
  1. Visit Global Burden of Disease Study 2019 to find the annual age-sex-location specific population for the years 2010 to 2019. Select the following filtering criteria and record the data in Table 7.

Safety, Environmental and Ethical Considerations

There are no significant safety or environmental considerations, nor waste disposal in this database investigation. Regarding ethics, survey participants of IHME have given their consent to the public sharing of their data prior to completing it. All confidential data possessed by IHME is also only shared between parties under a confidential disclosure agreement. Data collected for this investigation was used ethically as well, according to the regulations outlined by IHME. This includes using the data for non-commercial (not-for-profit) purposes only, and not reproducing, distributing, licensing, nor decrypting the datasets.

Data Collection

There is no qualitative data since all data collected was either numerical or textual.

Table 3. List of Eastern European Countries

Bulgaria

Croatia

Czechia

Estonia

Hungary

Latvia

Lithuania

North Macedonia

Poland

Republic of Kosovo

Republic of Moldova

Romania

Russian Federation

Serbia

Slovakia

Slovenia

Table 4. Eastern European Countries, and their HDI values (>0.700) and Population (>1 million)

Country

HDI (2019)

Population (2019)

Bulgaria

0.816

7,000,039

Croatia

0.851

4,076,246

Czechia

0.900

10,649,800

Estonia

0.892

1,324,820

Hungary

0.854

9,772,756

Latvia

0.866

1,919,968

Lithuania

0.882

2,794,184

North Macedonia

0.774

2,083,459

Poland

0.880

37,972,812

Republic of Kosovo

0.750

1,794,248

Republic of Moldova

0.750

4,043,263

Romania

0.828

19,414,458

Russian Federation

0.824

145,872,256

Serbia

0.806

6,963,764

Slovakia

0.860

5,450,421

Slovenia

0.917

2,080,908

Note: All countries have HDI above 0.700 and population above 1 million. No units and uncertainties for HDI and population.

The Republic of Kosovo was eliminated because GBD Results Tool provides no data for the incidence numbers of either cancers in this country.

Table 5. Number of Incidences of Cutaneous Malignant Melanoma, Thyroid Cancer, and Specific Population of Males Aged 50 to 69 in Bulgaria* in 2010-2019

Measure (#)

Year

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

Incidences of CMM

119.5451

125.3276

131.5338

137.8094

149.1933

150.5282

152.5976

154.1600

153.3544

152.9161

Incidences of Thyroid Cancer

38.9539

39.6752

40.1102

39.7731

41.8160

41.1036

42.5222

43.2287

43.3000

43.4725

Specific Population

927129

933907

936791

936823

934941

929209

917671

909221

904114

899550

*Table is a sample of the data, and only includes Bulgaria. See Appendix for the full data collection tables for all 15 countries.

Note: No units and uncertainties for the number of incidences and population.

Data Processing

Table 6. Incidence Rate of Cutaneous Malignant Melanoma and Incidence Rate of Thyroid Cancer for Males Aged 50-69 in Bulgaria* from 2010-2019

Location

Year

Incidence Rate of CMM (%)

Incidence Rate of Thyroid Cancer (%)

Bulgaria

2010

0.0129**

0.00420

Bulgaria

2011

0.0134

0.00425

Bulgaria

2012

0.0140

0.00428

Bulgaria

2013

0.0147

0.00425

Bulgaria

2014

0.0160

0.00447

Bulgaria

2015

0.0162

0.00442

Bulgaria

2016

0.0166

0.00463

Bulgaria

2017

0.0170

0.00475

Bulgaria

2018

0.0170

0.00479

Bulgaria

2019

0.0170

0.00483

*Table is a sample of the data, and only includes Bulgaria. See Appendix for the full data processing tables for all 15 countries.

Note: All values are rounded to 3 significant digits. All values calculated using =QUOTIENT(numerator, denominator) on Excel 2016. No uncertainties for incidence rates.

**Sample Calculation: Determining the incidence rate of CMM in Bulgaria in 2010.

age-sex specific incidence rate

Table 7. Average Incidence Rate of Cutaneous Malignant Melanoma and Average Incidence Rate of Thyroid Cancer for Males Aged 50-69, in 15 Eastern European Countries

Country

Average Incidence Rate of CMM (%)

Average Incidence Rate of Thyroid Cancer (%)

Bulgaria

0.0155*

0.00449

Croatia

0.0314

0.00621

Czechia

0.0412

0.00698

Estonia

0.0288

0.00576

Hungary

0.0270

0.00640

Latvia

0.0173

0.00583

Lithuania

0.0138

0.00466

Moldova

0.0177

0.00505

Poland

0.00786

0.00468

North Macedonia

0.0226

0.00378

Romania

0.0123

0.00483

Russian Federation

0.0116

0.00473

Serbia

0.0240

0.00590

Slovakia

0.0294

0.00466

Slovenia

0.0443

0.00679

Note: All values are rounded to 3 significant digits. Calculated using =AVERAGE(number 1, number 2,...) on Excel 2016. No uncertainties for average incidence rates.

*Sample Calculation: Determining the average incidence rate of CMM in Bulgaria.

   

Figure 4. Correlation Between the Incidence Rate of Malignant Melanoma (%) and the Incidence Rate of Thyroid Cancer (%) in Eastern Europe, from 2010-2019

Note: No uncertainties applicable. The R2  value and equation was determined using Excel 2016.

Consideration of the Impact of Measurement Uncertainty on the Analysis:

There are no measurement uncertainties for either variable since the number of incidences of CMM and of thyroid cancer are discrete, countable values. Additionally, no apparatus was used in this investigation, so there are no instrument errors. However, there may have been sampling errors and biases within the censuses and population registries conducted by IHME that caused the data to have inaccuracies and be slightly skewed. By averaging out the incidence values over a period of 10 years (2010-2019), the precision of the incidence rate increased. Values were also rounded to 3 significant digits to eliminate excessive precision from the raw data, while still ensuring the differences between percentages are prevalent. To further minimize the impact of sampling error and increase the reliability of the data, expanding the dataset to include more annual values can be done.

Data Interpretation

The upward trendline in Figure 4 and R² value of 0.543, which is between 0.5-0.7, indicates a moderate positive correlation[13] between the average incidence rate of cutaneous malignant melanoma and the average incidence rate of thyroid cancer. This suggests that as the incidence rate of CMM increases, that of thyroid cancer also increases. Moreover, the linear trendline of y = 0.0624x + 0.0039 suggests that the relationship between the two cancers are linear, so they increase proportionally at a constant rate. According to Figure 4 and Table 7, the lowest incidence rate of CMM of 0.00786% occurs in Poland. However, it has the fourth-lowest incidence rate of thyroid cancer of 0.00468%. This demonstrates variability in the data, which resulted in the observed moderate correlation. The country with the lowest rate of thyroid cancer is the Republic of North Macedonia (0.00378%). This data point is also furthest away from the trendline and can be considered an outlier. This is likely due to its higher average iodine nutrition, a factor influencing the development of thyroid cancer. The Republic of North Macedonia is the only country in Europe with a median UI level >200 µg/l, which is above adequate iodine intake but below the excessive intake, whereas most other countries have iodine deficiencies[14]. Slovenia has the highest incidence rate of CMM, at 0.0443%, and the second-highest incidence rate of thyroid cancer, at 0.00679%—just after Czechia (0.00698%). This latter point supports the positive correlation more strongly.

Pearson’s Correlation Coefficient and One-Tailed Test

Pearson’s correlation coefficient, or Pearson’s r, is a measure of the statistical relationship between two continuous variables, x and y. It communicates the direction and strength of the relationship, and can be calculated using the following formula:

Pearson’s r can then be compared to critical values to see if the null hypothesis (H0) is rejected.

Table 8. Calculating Pearson’s Correlation Coefficient

N

x = average incidence rate of CMM (%)

y = average incidence rate of thyroid cancer (%)

xy

x2

y2

1

0.0155

0.00449

0.000069464

0.000239529

0.000020145

2

0.0314

0.00621

0.000195187

0.000989035

0.000038520

...

...

...

...

...

...

15

0.0443

0.00679

0.000300735

0.001963333

0.000046065

Σ

0.337026686

0.079236771

0.001899627

0.009268918

0.000433485

   

Table 9. One-Tailed Test for Pearson’s r

Pearson’s r

Degrees of Freedom (=N-2)

Confidence Level

Critical Value (one-tailed)

0.737

13

0.01

0.641145[15]

Since Pearson’s r (0.737) > the critical value (0.641), the null hypothesis is rejected and the correlation between the incidence rate of CMM and of thyroid cancer is statistically significant; r(13) = .737, p < .01. This attributes 99% confidence in the relationship existing not by chance. The coefficient of 0.737, which is between .60 and .79 also indicates a strong positive correlation.

Evaluation

The overall positive trend in the data, represented by the linear trendline in Figure 4, supports the hypothesis that as the incidence rate of cutaneous malignant melanoma increases, the incidence rate of thyroid cancer also increases. Through the one-tailed test, this positive correlation was confirmed with 99% confidence. The R² value, the statistical measure of how close the data is to the fitted regression line, was 0.543, which is considered moderate. On the other hand, the value for Pearson’s r-value, 0.737, indicates a strong correlation. The R² value may be inaccurate because it did not account for the number of terms in the model; since only 15 points were used, the individual residuals may have had a magnified effect on the final sum. The overall trend could also be moderate due to the many extraneous variables which were not controlled in this investigation, causing wide variances and outliers in the data.

It cannot be certain that this correlation establishes a causal relationship, and further investigations will need to be conducted to prove causation. However, numerous scientific studies have similar findings to this investigation and support the alternate hypothesis as well. Stenger conducted a study using the Utah Population Database to identify the relative risk of papillary thyroid cancer (PTC) in patients with melanoma and vice versa, between 1966 and 2011, as well as tissue analysis to assess the rate of V600E mutation in patients with both diagnoses. He observed a significant 2.3-fold increased risk (P < .001) of melanoma patients being diagnosed with PTC, compared with controls. Stenger also observed a borderline increased risk of PTC in first- and second-degree relatives of melanoma cases (P = .05)—however, these associations were not statistically significant. Among eight patients, diagnosed with both cancers and who had both tissue specimens available, four (50%) had the BRAF V600E mutation in at least one specimen and three (38%) tested positive in both. This tissue analysis shows a strong genetic correlation between the cancers; however, more patient data should be studied to determine if this relationship is consistent across the wider population. There is also evidence for the reversed relationship, of PTC patients developing melanoma. In a survey of 3658 thyroid cancer patients in Norway from 1955 to 1985 by Akslen, males were observed to have a 4.2-fold increased risk of CM (95% CI)[16]. Furthermore, a data analysis of 6841 thyroid cancer patients (mean age of 44 years) in Sweden, French, and Italy conducted from 1934 to 1995 concluded an estimated 2.5-fold increased risk of CM in patients with thyroid cancer[17].

According to Lazzara et al.’s (2019)[18] literature review of 2,470 and 234 articles, using PubMed Central and ScienceDirect online databases, patients with malignant melanoma are at an increased risk for developing other cancers, specifically thyroid carcinoma, due to an alteration of the MEK-ERK-MAP kinase pathway. BRAF missense mutations lead to oncogenic activation of the MAP kinase pathway. As a result, “upregulation in cell division and proliferation leads to tumorigenesis”. This common genetic component, which was mentioned in the background and served as the inspiration for this investigation, is thus consistent with real world and clinical observations. At the same time, according to Bradford et al., who conducted a population-based registry study to assess the risk of CMM patients developing second primary cancers, although the risk of thyroid cancer is significantly increased (0.89%), the cancers with the highest risk are breast (1.34%), prostate (3.49%), and non-Hodgkin lymphoma (1.18%)[19]. Frank et al., who studied the Swedish Family-Cancer Database, also discusses breast and prostate cancer as the most common cancers associated with melanoma[20]. As well, they explain that the most common gene predisposing to melanoma, CDKN2A, is also associated with pancreatic cancer. This means melanoma is not exclusively genetically related to thyroid cancer, but many other cancers - due to the many susceptibility genes that contribute to the development of melanoma. In all, scientific studies do support the general trend observed in this investigation of a positive correlation between CMM and thyroid cancer.

Table 10. Strengths and Limitations of the Investigation

Strengths

Limitations

Many control variables were used in this investigation (i.e. age, gender, geographic region, HDI, population size), which have a great influence on an individual’s risk of developing either CMM or thyroid cancer. By eliminating these major confounding variables, the variance in the data is reduced and a good level of accuracy is ensured.

Many confounding variables remain uncontrolled (e.g. obesity level—which can affect an individuals’ immune system and thus susceptibility to the diseases, GDP per capita—which affects the ability to have a healthy lifestyle and diet, average radiation exposure and iodine levels). This means that wide variances could still exist within the datasets, causing the incidence rates calculated to be less accurate.

Finding the average incidence rate of CMM and thyroid cancer using annual values over a period of 10 years (2010-2019) helped to minimize sampling errors and inaccuracies in the data from a particular year, reducing the amount of random error and increasing the overall precision of the data.

All types of thyroid cancers were included in this study, not only PTC - which is the form of thyroid cancer in which the shared genetic component exists. Although PTC accounts for the majority (90%) of thyroid cancer cases, the remaining data from the other forms may have skewed the data and created unwanted variances, decreasing the accuracy of the results.

The use of credible data sources (i.e. The World Bank, IHME—which gathered data using 1250 surveys and calculates estimates 1000 times, each time sampling from distributions) increases the accuracy of the data and thus ensures reliability in the results.

Only one source (IHME) was used to gather data for the incidence rates of CMM and thyroid cancer. Although this is advantageous to some extent, as the data gathered used the same collection methodologies and criteria, there may exist inherent biases within the censuses that could skew the data and hence decrease the accuracy.

Having multiple statistical measures (i.e. R2 value, Pearson’s r, one-tailed test) to complete statistical analysis allows the values to be cross-checked and the credibility and limitations of each to be assessed.

As an improvement to the methodology of this investigation, more control variables (i.e. BMI, GDP per capita, average UV radiation exposure, and iodine levels) could be implemented to ensure the positive correlation found between the CMM and thyroid cancer is not due to extraneous variables. Narrowing down the criteria mentioned above can strengthen the accuracy of the relationship observed between each variable, increasing the reliability of the results. Using data specific to PTC cases, rather than thyroid cancer in general, can also increase accuracy and the strength of the relationship found between PTC and CMM, helping to better achieve the objective of this investigation - exploring the genetic correlation between PTC and CMM. Lastly, multiple sources which provide the same data should be used, so that the incidence rates can be calculated by averaging the values of the various sources. This eliminates random errors and biases of a particular source, and thus increases the reproducibility and reliability of the experiment.

Overall, the conclusions of this investigation can only be applied to the specific group that was studied, of males aged 50-69 in Eastern Europe. It would be interesting to scale this investigation by repeating the same data collection and data processing procedures for different geographic areas (e.g. countries in Asia) to determine if the correlation still holds true in other regions, and then compare it with the findings of this investigation. Another extension could be to repeat this experiment using data for females, to determine if the positive relationship between CMM and thyroid cancer is true for both males and females. Since the common mutation V600E is not sex-linked, females may also be susceptible to this mutation. However, there may be differences in the impact of environmental factors on females or other female-specific genetic predispositions that make them either more or less at risk of having both conditions. The processed data for females can also be compared with that of males to explore the question: What are the differences between males and females regarding the relationship of their respective incidence rates for CMM and thyroid cancer? A t-test can then be performed to determine if there is a significant difference between the two groups. The results of this extension could provide crucial information on whether males or females are more susceptible to either or both diseases, which would be useful for early clinical diagnoses, disease prevention, and the development of new treatments.


References

Akslen, L. A., & Glattre, E. (1992). Second malignancies in thyroid cancer patients: A

POPULATION-BASED survey Of 3658 cases from Norway. Retrieved March 03, 2021, from https://pubmed.ncbi.nlm.nih.gov/1591071/ 

Andersson, M., De Benoist, B., Darnton-Hill, I., & Delange, F. (n.d.). Iodine Deficiency in

Europe: A continuing public health problem. Retrieved from https://www.who.int/nutritio

n/publications/VMNIS_Iodine_deficiency_in_Europe.pdf

Bradford, P. T., Freedman, D. M., Goldstein, A. M., & Tucker, M. A. (2010). Increased risk of

second primary cancers after a diagnosis of melanoma. Archives of dermatology, 146(3),

265–272. https://doi.org/10.1001/archdermatol.2010.2

Cantwell-Dorris, E., O'Leary, J., & Sheils, O. (2011, March 01). Brafv600e: Implications for

carcinogenesis and molecular therapy. Retrieved March 03, 2021, from https://mct.aacrjournals.org/content/10/3/385 

Clayman, G., DMD, MD, FACS. (n.d.). Thyroid cancer. Retrieved March 03, 2021, from

https://www.endocrineweb.com/conditions/thyroid-cancer/thyroid-cancer 

Eastern European COUNTRIES' Committee introduction and members. (n.d.). Retrieved March

03, 2021, from https://www.insol-europe.org/eastern-european-countries-committee-intro

duction-and-members 

Frank, C., Sundquist, J., Hemminki, A., & Hemminki, K. (2017). Risk of other Cancers in

Families with Melanoma: Novel Familial Links. Scientific reports, 7, 42601. https://doi.org/10.1038/srep42601

Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2019 (GBD

2019) Population Estimates 1950-2019. Seattle, United States of America: Institute for Health Metrics and Evaluation (IHME), 2020. https://doi.org/10.6069/7EGY-0354 

Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2019 (GBD

2019) Results. Seattle, United States: Institute for Health Metrics and Evaluation (IHME), 2020. Available from http://ghdx.healthdata.org/gbd-results-tool.

Human development reports. (n.d.). Retrieved March 10, 2021, from

http://hdr.undp.org/en/content/human-development-report-2020-readers-guide   

Human development reports. (n.d.). Retrieved March 03, 2021, from http://hdr.undp.org/en 

Population, total. (n.d.). Retrieved March 03, 2021, from https://data.worldbank.org/indicator/SP.

POP.TOTL

"Key Statistics for Melanoma Skin Cancer". www.cancer.org. Archived from the original on

2017-04-10. Retrieved 2017-04-10.

Lazzara, D. R., DO, Zarkhin, S. G., DO, Rubenstein, S. N., BS, &amp; Glick, B. P., DO. (2019,

September 01). Melanoma and Thyroid Carcinoma: Our current UNDERSTANDING: JCAD: The Journal of clinical and Aesthetic Dermatology. Retrieved March 03, 2021, from https://jcadonline.com/melanoma-thyroid-carcinoma/

Melanoma treatment (PDQ®)–Health professional version. (n.d.). Retrieved March 03, 2021,

from https://www.cancer.gov/types/skin/hp/melanoma-treatment-pdq#cit/section_1.3 

Namba, H., Nakashima, M., Hayashi, T., Hayashida, N., Maeda, S., Rogounovitch, T., . . .

Yamashita, S. (2003, September 01). Clinical implication of hot spot BRAF MUTATION, V599E, IN papillary thyroid cancers. Retrieved March 03, 2021, from https://academic.oup.com/jcem/article/88/9/4393/2845796 

Quinlan, C., Babin, B. J., Carr, J. C., Griffin, M., & Zikmund, W. G. (2019). Business research

methods. Andover, Hampshire, United Kingdom: Cengage Learning, EMEA.

Rubino, C., De Vathaire, F., Hall, P., Schvartz, C., Couette, J. E., Dondon, M. G., . . .

Schlumberger, M. (2003, November 03). Second primary Malignancies in thyroid cancer patients. Retrieved March 03, 2021, from https://pubmed.ncbi.nlm.nih.gov/14583762 

Shah, M., Orengo, I. F., & Rosen, T. (2006). High prevalence of hypothyroidism in male patients

with cutaneous melanoma. Dermatology online journal, 12(2), 1.

Smith, R. P., MD, Kim, C., MD, & Mandel, S., MD. (2020, June 16). All about thyroid cancer.

Retrieved March 03, 2021, from https://www.oncolink.org/cancers/thyroid/all-about-thyr

oid-cancer

Table of critical values: Pearson correlation. (2020, August 26). Retrieved March 11, 2021, from

https://www.statisticssolutions.com/table-of-critical-values-pearson-correlation/

Thyroid cancer incidence statistics. (2020, April 17). Retrieved March 03, 2021, from

https://www.cancerresearchuk.org/health-professional/cancer-statistics/statistics-by-cancer-type/thyroid-cancer/incidence

Thyroid cancer treatment (adult) (pdq®)–patient version. (n.d.). Retrieved March 03, 2021, from

https://www.cancer.gov/types/thyroid/patient/thyroid-treatment-pdq 

Vecchia, C., Malvezzi, M., Bosetti, C., Garavello, W., Bertuccio, P., Levi, F., & Negri, E. (2014,

October 13). Thyroid cancer mortality and incidence: A global overview. Retrieved March 11, 2021, from https://onlinelibrary.wiley.com/doi/full/10.1002/ijc.29251 


Appendix

Data Collection

Table 11. Number of Incidences of Cutaneous Malignant Melanoma of Males Aged 50 to 69 in 15 Eastern European Countries from 2010-2019

Country

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

Bulgaria

119.5451

125.3276

131.5338

137.8094

149.1933

150.5282

152.5976

154.1600

153.3544

152.9161

Croatia

147.0042

154.0583

162.0850

161.0478

172.2397

188.8461

189.9220

190.2589

188.2991

189.0407

Czechia

538.4835

548.3132

549.0435

551.0236

542.4363

549.4659

543.8793

534.0728

540.6404

533.6089

Estonia

37.6355

40.3315

40.6758

40.2062

44.3683

43.1650

43.2487

43.8434

43.9359

43.7899

Hungary

343.4407

336.3454

323.3229

302.7464

304.6935

307.0109

308.5523

312.7274

322.5627

315.6345

Latvia

37.0715

36.1050

38.1247

39.5953

39.4840

39.8862

37.6945

38.5025

39.1707

39.4964

Lithuania

45.5824

45.2750

45.0580

45.6439

44.4066

46.6743

48.0094

42.9662

44.0218

44.2328

North Macedonia

51.3350

52.2079

53.4007

54.9810

56.9715

58.3832

60.6066

62.0277

63.2327

64.4155

Moldova

693.8544

725.7659

771.4505

806.2437

808.0003

873.5519

889.1672

903.3691

905.5247

908.9855

Poland

27.4100

25.8281

27.5855

29.0302

32.6186

35.9546

38.0419

34.8737

36.1038

35.4800

Romania

244.9345

238.4365

256.8492

258.4893

281.4113

289.8247

310.5785

321.8415

337.2614

343.5399

Russian Federation

1596.8600

1532.8287

1576.6211

1686.6987

1887.5092

2001.0053

2091.1710

1987.1848

1968.2192

2001.9630

Serbia

227.4441

235.2450

243.0404

250.9416

262.1913

276.8790

276.4003

278.6983

274.9061

276.0917

Slovakia

159.5076

166.3601

173.3912

181.2033

191.0122

201.0578

200.4316

205.0815

204.0238

205.2907

Slovenia

104.8435

103.6517

111.1741

116.3583

112.8640

128.2226

130.6239

134.9667

136.4092

137.6038

Note: No units and uncertainties for the number of incidences.

Table 12. Number of Incidences of Thyroid Cancer of Males Aged 50 to 69 in 15 Eastern European Countries from 2010-2019

Country

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

Bulgaria

38.9539

39.6752

40.1102

39.7731

41.8160

41.1036

42.5222

43.2287

43.3000

43.4725

Croatia

33.7993

32.2276

33.7375

32.1630

33.1474

35.0707

36.0079

35.8995

35.6158

35.7718

Czechia

99.4478

99.5576

97.1716

95.4414

89.7808

87.7215

87.1269

87.8000

88.7052

87.9540

Estonia

8.4054

8.5097

8.1930

7.9117

8.7016

8.2311

8.4895

8.5597

8.5793

8.5811

Hungary

76.1114

74.3075

73.8416

70.4501

72.5197

73.5199

77.7610

78.8371

79.5517

77.4702

Latvia

13.0403

13.2271

13.2946

13.4245

13.1581

12.9296

12.4767

12.6484

12.8208

12.8982

Lithuania

17.2772

15.0325

15.1454

14.7950

14.7967

15.6543

15.4443

14.5653

14.8668

15.0507

North Macedonia

9.0820

8.5877

8.7339

8.9988

9.4634

9.6424

10.0764

10.3779

10.6232

10.8403

Moldova

204.6126

210.8564

223.2308

231.9794

235.2892

245.5408

250.3977

253.8654

254.2457

254.5835

Poland

17.6547

17.0126

17.7621

17.7279

19.6552

21.0141

21.2657

20.1420

20.1615

19.7394

Romania

108.2129

103.3841

110.5669

107.2863

113.1949

114.1307

114.9736

114.3539

120.4564

122.8598

Russian Federation

686.1833

663.6507

676.0162

703.4363

768.9670

801.0056

818.6977

777.3276

769.7321

779.7166

Serbia

57.0621

59.5704

61.3457

62.9948

65.6905

69.4178

67.1941

66.8697

65.1480

65.0436

Slovakia

28.8121

28.9251

28.5705

28.6794

29.3428

31.0454

30.0294

30.8315

30.8396

31.2594

Slovenia

16.8163

16.9459

17.5271

18.1012

17.6087

19.1284

19.5019

20.0233

20.1804

20.2681

Note: No units and uncertainties for the number of incidences.

Table 13. Population of Males Aged 50 to 69 in 15 Eastern European Countries from 2010-2019

Country

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

Bulgaria

927129

933907

936791

936823

934941

929209

917671

909221

904114

899550

Croatia

530343

534948

539529

544049

549978

556830

566364

568846

570765

570679

Czechia

1308627

1311741

1315648

1321272

1328157

1335081

1330054

1319946

1311880

1309931

Estonia

140126

141576

142305

144002

145996

147989

149401

149875

149914

150194

Hungary

1186627

1186207

1183788

1178997

1175224

1169257

1170519

1174658

1177535

1180202

Latvia

219676

220152

220441

221284

222223

223432

224798

226004

226220

226039

Lithuania

312858

316972

320570

323544

326787

330845

332988

335912

338442

340098

North Macedonia

233204

238380

242953

248061

253164

258659

264087

268232

270891

273411

Moldova

4455767

4531596

4601865

4666312

4723756

4773517

4789322

4777301

4752107

4723664

Poland

476767

386111

390511

396120

402048

406898

412139

415009

417663

416831

Romania

2329002

2333259

2333354

2331484

2326258

2314390

2303606

2312919

2386108

2428809

Russian Federation

14447304

14797437

15130628

15540826

15924525

16209137

16381027

16349559

16328777

16278114

Serbia

1074577

1077259

1079394

1082955

1086319

1090182

1093113

1095190

1088565

1085140

Slovakia

600172

611063

621318

631711

642054

651394

658945

662929

664122

665278

Slovenia

255527

259350

263472

267319

271160

275753

282079

286140

288287

289932

Note: No units and uncertainties for the population.

Data Processing

Table 14. Incidence Rate of Cutaneous Malignant Melanoma for Males Aged 50-69 in 15 Eastern European Countries from 2010-2019

Country

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

Bulgaria

0.012894

0.01342

0.014041

0.01471

0.015958

0.0162

0.016629

0.016955

0.016962

0.016999

Croatia

0.027719

0.028799

0.030042

0.029602

0.031318

0.033914

0.033534

0.033446

0.032991

0.033126

Czechia

0.041149

0.0418

0.041732

0.041704

0.040841

0.041156

0.040892

0.040462

0.041211

0.040736

Estonia

0.026858

0.028488

0.028584

0.027921

0.03039

0.029168

0.028948

0.029253

0.029307

0.029156

Hungary

0.028943

0.028355

0.027313

0.025678

0.025926

0.026257

0.02636

0.026623

0.027393

0.026744

Latvia

0.016875

0.0164

0.017295

0.017893

0.017768

0.017852

0.016768

0.017036

0.017315

0.017473

Lithuania

0.01457

0.014284

0.014056

0.014107

0.013589

0.014108

0.014418

0.012791

0.013007

0.013006

North Macedonia

0.022013

0.021901

0.02198

0.022164

0.022504

0.022572

0.022949

0.023125

0.023343

0.02356

Moldova

0.015572

0.016016

0.016764

0.017278

0.017105

0.0183

0.018566

0.01891

0.019055

0.019243

Poland

0.005749

0.006689

0.007064

0.007329

0.008113

0.008836

0.00923

0.008403

0.008644

0.008512

Romania

0.010517

0.010219

0.011008

0.011087

0.012097

0.012523

0.013482

0.013915

0.014134

0.014144

Russian Federation

0.011053

0.010359

0.01042

0.010853

0.011853

0.012345

0.012766

0.012154

0.012054

0.012298

Serbia

0.021166

0.021837

0.022516

0.023172

0.024136

0.025397

0.025286

0.025447

0.025254

0.025443

Slovakia

0.026577

0.027225

0.027907

0.028685

0.02975

0.030866

0.030417

0.030936

0.030721

0.030858

Slovenia

0.04103

0.039966

0.042196

0.043528

0.041623

0.046499

0.046308

0.047168

0.047317

0.047461

Note: All values are rounded to 3 significant digits. All values calculated using =QUOTIENT(numerator, denominator) on Excel 2016. No uncertainties for incidence rates.

Table 15. Incidence Rate of Thyroid Cancer for Males Aged 50-69 in 15 Eastern European Countries from 2010-2019

Country

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

Bulgaria

0.004202

0.004248

0.004282

0.004246

0.004473

0.004424

0.004634

0.004754

0.004789

0.004833

Croatia

0.006373

0.006024

0.006253

0.005912

0.006027

0.006298

0.006358

0.006311

0.006240

0.006268

Czechia

0.007599

0.007590

0.007386

0.007223

0.006760

0.006571

0.006551

0.006652

0.006762

0.006714

Estonia

0.005998

0.006011

0.005757

0.005494

0.005960

0.005562

0.005682

0.005711

0.005723

0.005713

Hungary

0.006414

0.006264

0.006238

0.005975

0.006171

0.006288

0.006643

0.006711

0.006756

0.006564

Latvia

0.005936

0.006008

0.006031

0.006067

0.005921

0.005787

0.005550

0.005597

0.005667

0.005706

Lithuania

0.005522

0.004743

0.004725

0.004573

0.004528

0.004732

0.004638

0.004336

0.004393

0.004425

North Macedonia

0.003894

0.003603

0.003595

0.003628

0.003738

0.003728

0.003816

0.003869

0.003922

0.003965

Moldova

0.004592

0.004653

0.004851

0.004971

0.004981

0.005144

0.005228

0.005314

0.005350

0.005390

Poland

0.003703

0.004406

0.004548

0.004475

0.004889

0.005164

0.005160

0.004853

0.004827

0.004736

Romania

0.004646

0.004431

0.004739

0.004602

0.004866

0.004931

0.004991

0.004944

0.005048

0.005058

Russian Federation

0.004750

0.004485

0.004468

0.004526

0.004829

0.004942

0.004998

0.004754

0.004714

0.004790

Serbia

0.005310

0.005530

0.005683

0.005817

0.006047

0.006368

0.006147

0.006106

0.005985

0.005994

Slovakia

0.004801

0.004734

0.004598

0.004540

0.004570

0.004766

0.004557

0.004651

0.004644

0.004699

Slovenia

0.006581

0.006534

0.006652

0.006771

0.006494

0.006937

0.006914

0.006998

0.007000

0.006991

Note: All values are rounded to 3 significant digits. All values calculated using =QUOTIENT(numerator, denominator) on Excel 2016. No uncertainties for incidence rates.


[1] Shah, M., Orengo, I. F., & Rosen, T. (2006). High prevalence of hypothyroidism in male patients with cutaneous melanoma. Dermatology online journal, 12(2), 1.

[2] Clayman, G., DMD, MD, FACS. (n.d.). Thyroid cancer. Retrieved March 03, 2021, from https://www.endocrineweb.com/conditions/thyroid-cancer/thyroid-cancer

[3]Namba, H., Nakashima, M., Hayashi, T., Hayashida, N., Maeda, S., Rogounovitch, T., . . . Yamashita, S. (2003, September 01). Clinical implication of hot spot BRAF MUTATION, V599E, IN papillary thyroid cancers. Retrieved March 03, 2021, from https://academic.oup.com/jcem/article/88/9/4393/2845796

[4]Melanoma treatment (PDQ®)–Health professional version. (n.d.). Retrieved March 03, 2021, from https://www.cancer.gov/types/skin/hp/melanoma-treatment-pdq#cit/section_1.3

[5]"Key Statistics for Melanoma Skin Cancer". www.cancer.org. Archived from the original on 2017-04-10. Retrieved 2017-04-10.

[6]Thyroid cancer treatment (adult) (pdq®)–patient version. (n.d.). Retrieved March 03, 2021, from https://www.cancer.gov/types/thyroid/patient/thyroid-treatment-pdq

[7]Thyroid cancer. (2019, July 15). Retrieved March 03, 2021, from https://www.cdc.gov/cancer/thyroid/index.htm

[8]Smith, R. P., MD, Kim, C., MD, & Mandel, S., MD. (2020, June 16). All about thyroid cancer. Retrieved March 03, 2021, from https://www.oncolink.org/cancers/thyroid/all-about-thyroid-cancer

[9] Thyroid cancer incidence statistics. (2020, April 17). Retrieved March 03, 2021, from https://www.cancerresearchuk.org/health-professional/cancer-statistics/statistics-by-cancer-type/thyroid-cancer/incidence

[10]Cantwell-Dorris, E., O'Leary, J., & Sheils, O. (2011, March 01). Brafv600e: Implications for carcinogenesis and molecular therapy. Retrieved March 03, 2021, from https://mct.aacrjournals.org/content/10/3/385

[11]Human development reports. (n.d.). Retrieved March 10, 2021, from http://hdr.undp.org/en/content/human-development-report- 2020-readers-guide

[12]Vecchia, C., Malvezzi, M., Bosetti, C., Garavello, W., Bertuccio, P., Levi, F., & Negri, E. (2014, October 13). Thyroid cancer mortality and incidence: A global overview. Retrieved March 11, 2021, from https://onlinelibrary.wiley.com/doi/full/10.1002/ijc.29251

[13]Quinlan, C., Babin, B. J., Carr, J. C., Griffin, M., & Zikmund, W. G. (2019). Business research methods. Andover, Hampshire, United Kingdom: Cengage Learning, EMEA.

[14]Andersson, M., De Benoist, B., Darnton-Hill, I., & Delange, F. (n.d.). Iodine Deficiency in Europe: A continuing public health problem. Retrieved from https://www.who.int/nutrition/publications/VMNIS_Iodine_deficiency_in_Europe.pdf

[15]Table of critical values: Pearson correlation. (2020, August 26). Retrieved March 11, 2021, from https://www.statisticssolutions.com/table-of-critical-values-pearson-correlation/

[16]Akslen, L. A., & Glattre, E. (1992). Second malignancies in thyroid cancer patients: A POPULATION-BASED survey Of 3658 cases from Norway. Retrieved March 03, 2021, from https://pubmed.ncbi.nlm.nih.gov/1591071/

[17]Rubino, C., De Vathaire, F., Hall, P., Schvartz, C., Couette, J. E., Dondon, M. G., . . . Schlumberger, M. (2003, November 03). Second primary Malignancies in thyroid cancer patients. Retrieved March 03, 2021, from https://pubmed.ncbi.nlm.nih.gov/14583762

[18]Lazzara, D. R., DO, Zarkhin, S. G., DO, Rubenstein, S. N., BS, &amp; Glick, B. P., DO. (2019, September 01). Melanoma and Thyroid Carcinoma: Our current UNDERSTANDING: JCAD: The Journal of clinical and Aesthetic Dermatology. Retrieved March 03, 2021, from https://jcadonline.com/melanoma-thyroid-carcinoma/

[19]Bradford, P. T., Freedman, D. M., Goldstein, A. M., & Tucker, M. A. (2010). Increased risk of second primary cancers after a diagnosis of melanoma. Archives of dermatology, 146(3), 265–272. https://doi.org/10.1001/archdermatol.2010.2

[20]Frank, C., Sundquist, J., Hemminki, A., & Hemminki, K. (2017). Risk of other Cancers in Families with Melanoma: Novel Familial Links. Scientific reports, 7, 42601. https://doi.org/10.1038/srep42601