Global patterns and trends in multiple myeloma incidence: Age, period and birth cohort analysis

doi:10.21203/rs.3.rs-1977463/v1

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Global patterns and trends in multiple myeloma incidence: Age, period and birth cohort analysis

https://doi.org/10.21203/rs.3.rs-1977463/v1

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Background

The incidence of multiple myeloma (MM) are increasing in some countries. This study aimed to examine global differences in MM incidence and temporal trends from 1978 to 2012, In addition, the effect of birth cohort was analyzed.

Patients and methods:

The incidence of MM in 43 countries was extracted from the Cancer Incidence in Five Continents database (CI5), Joinpoint regression and age - period - cohort models were applied.

Results

From 2008 to 2012, the incidence rates of MM were generally 1- to 2-fold higher in males than in females, except for Bahrain. Rates were highest in North America, Oceania and Northern Europe. Twenty countries showed significant increasing trends, except for Costa Rica in the period 1978 to 2012 (P < 0.05). The incidence rates increased with age in all birth cohorts and most age groups increased steadily with birth cohorts in most countries. Pronounced cohort-specific decreases in risk for recent birth cohorts were only seen in eight countries for both sexes. The cohort-specific incidence rate ratios increased rapidly in Belarus, Bulgaria, and Philippines cohorts born before 1920 for males, and in Ireland, and Slovakia cohorts born before 1990 for females. Cohort-specific incidence rate ratios for both sexes decreased in Iceland for cohorts born since 1960.

Conclusion

Disparities in MM incidence and increasing trends persist worldwide. Further studies are warranted to investigate the prevention and control of MM from population level.

Multiple myeloma

Incidence

Global trends

Birth cohort effect

Multiple myeloma (MM) is a common malignant plasma cell disease, ranking the second most common hematological malignancy^[1–3]. The absolute number of new cases attributed to MM was still increasing, causing about 159,985 new cases in 2018 and accounting for 0.9% of all new tumors^[4]. In addition, the MM burden remained highest in North America, Australia, New Zealand, and Europe, whereas it is the lowest in Asia (except for Western Asia)^[5]. Due to the increasing disease burden of MM and global differences, understanding the risk of MM in each region and identifying possible causes are very important for primary prevention.

The etiology of MM is not completely clear. Virtually all MM patients are preceded by a precursor disease (PD), being monoclonal gammopathy of uncertain significance (MGUS) the most frequent PD^[6]. Previous studies have suggested that radiation exposure, chronic inflammation, heredity, virus infection and gene mutation may be related to the pathogenesis of MM^[7–10]. The recognition of other risk factors such as lifestyle, dietary habit, also seems important^[11]. There also might exist some potential risk factors which we still could not recognize.

Knowing the differences in the incidence between countries and temporal trends are important. Age-period-cohort models were applied to better evaluate the effect of age, period and birth cohort on MM incidence. Birth cohort effects can reflect generational influence on the potential risk factors, such as lifestyle, dietary habit, and environmental radiation, which has delayed effects on MM outcomes^[12]. The time trends of incidence rate could provide clues to understand the role of risk or protective factors in the etiology of disease. However, up to now, the age - period - cohort model has not been applied to assess the global trends in MM, which is more effective than conventional cross - sectional models in evaluating trends^[13].

Therefore, in this study, we aimed to assess the geographic patterns and temporal trends in MM incidence from 1978 to 2012 for 43 countries across five continents. Specifically, we evaluated the effect of birth cohort to examine the importance of changes in environment and identify countries with increasing risk of MM.

Data sources

Incident multiple myeloma cases and population-at-risk of the years 1978–2012 were obtained from the Cancer Incidence in Five Continents (CI5), which collects available comparable data on cancer incidence at approximately five-year intervals from as wide a range of geographical locations worldwide as possible^[14]. The available CI5 Volumes include volume V (1978–1982), volume VI (1983–1987), volume VII (1988–1992), volume VIII (1993–1997), volume IX (1998–2002), volume X (2003–2007), and volume XI (2008–2012).

A total of 43 countries worldwide, from 11 regions, with at least three consecutive volumes of data and compilation in the most recent volume were included according to inclusion criteria. National incidence data were available for 21 countries (Denmark, Estonia, Iceland, Ireland, Lithuania, Norway, Austria, the Netherlands, Croatia, Cyprus, Malta, Slovenia, Belarus, Bulgaria, Czech Republic, Slovakia, Costa Rica, Bahrain, Israel, Kuwait, and New Zealand). The remaining 22 countries included with more than one cancer registry (the United Kingdom, France, Germany, Switzerland, Italy, Spain, Poland, Canada, the United States, Brazil, Chile, Colombia, Ecuador, People’s Republic of China, Japan, Republic of Korea, the Philippines, Thailand, India, Turkey, Australia, and Uganda), cases and population-at-risk were pooled to obtain an accurate estimate of national incidence^[15]. Incidence data for the United States were divided into black and white races.

Statistical analyses

To assess the sex differences in MM incidence from 2008 to 2012, Age-standardized incidence rates (ASR) were estimated by gender using the world standard population, and the male to female ratios were calculated for different regions. To evaluate the change in age-adjusted incidence rates from 1978 to 2012 years, we constructed a Joinpoint regression model of the natural log-transformed rates to calculate the annual percent change (APC) and the average annual percent change (AAPC)^[16]. In addition, we plotted the change in ASRs as the midpoint of each 5-year interval on the same scale by different regions. AAPCs were then plotted by ASRs in 2008–2012. The age-specific rates were plotted by birth cohorts on a semi-log scale in all countries. The birth cohorts were calculated by subtracting the midpoints of 5-year age groups from the corresponding calendar periods. There were quasi-parallelism of the age-specific curves on either time scale, indicating their respective influence on the temporal pattern.

Finally, because there is a completely linear relationship (period = age + cohort), we performed age-period-cohort model on the incidence of MM by for each country and sex using a web tool, newly developed by the National Cancer Institute (NCI), United States^[17]. In general, the number of new MM cases followed a Poisson distribution:

$$[\mathbf{log}{\lambda }\left(\left({a},{p}\right)\right)={{\alpha }}_{{a}}+ {{\beta }}_{{p}}+ {{\gamma }}_{{c}}]$$

Where $\lambda$ refers to the rate and ${{\alpha }}_{{a}}$, ${{\beta }}_{{p}}$ and${ {\gamma }}_{{c}}$ are functions of age (${\alpha }$), period (${\beta }$) and birth cohort (${\gamma }$), respectively. By constraining the linear component of the period effect to have a zero slope, we presented the birth cohort effect as the incidence rate ratios (IRR) relative to the reference birth cohort, assuming that the linear change of trends are related to the cohort^{[18, 19]}.

Figures were drawn using Sigma Plot v14.0 (SY Software, San Jose, Calif). Joinpoint regression models were established using Joinpoint Regression Program v4.8.0.1 (https://surveillance.cancer.gov/joinpoint/). The age-period-cohort model analyses were performed in the APC web tool^{[17, 20]} (Biostatistics Branch, National Cancer Institute, Bethesda, MD https://analysistools.nci.nih.gov/apc/).

The incidence rate of MM in most countries showed significant sex difference in the period 2008 to 2012, with male rates about 1- to 2- fold slightly higher than female rates, expect for Bahrain (M: F = 0.78:1) (Figure S1). Malta had the greatest sex difference in rates (M: F ratio = 1.78).

In 2008–2012, as shown in Table 1 and Table 2, the ASRs were highest in North America, Oceania, and Northern Europe, while lowest in Africa, Eastern Asia and Southeastern Asia. The ASRs among males were the highest in New Zealand (ASR = 5.9 per 100,000 person-years) and Norway (ASR = 5.8 per 100,000 person-years), and the lowest in Philippines (ASR = 0.8 per 100,000 person-years); The ASRs among females were the highest in Israel (ASR = 3.9 per 100,000 person-years), and the lowest in Costa Rica (ASR = 0.7 per 100,000 person-years) and Philippines (ASR = 0.8 per 100,000 person-years). However, the ASRs were slightly discrepancy in different areas, ranging from 5.6 in Israel to 1.2 in Bahrain for men (high to low ratio = 4.7) and from 3.9 in Israel to 0.9 in India for women (high to low ratio = 4.3).

Table 1

Age-adjusted males multiple myeloma incidence rates per 100,000 person years (1978–1982 and 2008–2012)
Population	1978–1982 (Volume V)		2008–2012 (Volume XI)		Trend1 APC (%)	Trend2 APC (%)	Join-point	AAPC (%)
Population	Cases	Rate	Cases	Rate	Trend1 APC (%)	Trend2 APC (%)	Join-point	AAPC (%)
Africa
Uganda	-	-	23	1.8	11.4			11.4
Eastern Asia
China	271	1.0	3382	1.5	1.9			1.9*
Korea	-	-	4279	2.1	3.3			3.3*
Japan	301	1.6	3205	2.1	0.9			0.9*
Southeastern Asia
Philippines	11	0.4	174	0.8	2.2			2.2
Thailand	-	-	347	1.2	4.8			4.8*
Southwestern Asia
India	157	1.1	1483	1.4	0.9			0.9
Kuwait	19	2.2	95	2.0	-1.2			-1.2
Turkey	-	-	946	3.2	5.5			5.5*
Bahrain	-	-	15	1.2	-4.7			-4.7
Israel	552	3.9	1130	5.6	-5.8	5.2	1990	1.4*
Central and Eastern Europe
Czech Republic	-	-	1180	3.0	0.6			0.6
Poland	82	1.8	1026	2.6	1.5			1.5
Bulgaria	-	-	496	1.7	3.4			3.4*
Belarus	-	-	555	2.0	3.6			3.6
Slovakia	269	2.2	410	4.3	2.1			2.1*
Northern Europe
Denmark	535	3.1	1035	4.5	1.1			1.1*
Estonia	-	-	148	3.3	3.7			3.7*
Ireland	15	1.6	735	5.3	0.9			0.9
Iceland	53	4.7	60	5.6	-1.3	4.5	2000	0.6
Norway	683	4.9	1086	5.8	-0.8	2.1	1995	0.6*
Lithuania	-	-	339	3.3	2.7			2.7*
UK	7293	3.0	25223	5.3	1.7			1.7*
Southern Europe
Croatia	-	-	483	2.8	2.4			2.4
Cyprus	-	-	110	3.9	6.2			6.2
Italy	117	4.7	5445	4.8	0.8			0.8
Malta	-	-	57	3.6	0.6			0.6
Slovenia	84	2.3	326	3.8	3.3			3.3
Spain	102	1.9	1614	3.8	1.7			1.7*
Western Europe
Austria	-	-	1152	3.4	1.0			1.0
France	163	2.4	2070	4.7	2.0			2.0*
Germany	947	1.8	10685	4.3	4.0	1.2	2000	3.1*
The Netherlands	683	4.9	3289	5.0	-2.4	1.3	1990	0.1
Switzerland	219	3.9	802	4.6	0.8			0.8
North America
Canada	4439	3.7	4753	4.9	0.6			0.6*
USA	1579	4.4	176696	5.5	0.7			0.7*
Central and South America
Chile	-	-	119	2.6	-2.8			-2.8
Brazil	94	3.0	270	3.8	2.5			2.5
Colombia	23	2.2	221	2.7	1.0			1.0
Costa Rica	37	2.4	82	1.1	-2.9			-2.9*
Ecuador	-	-	237	2.1	0.0			0.0
Oceania
Australia	816	3.8	8963	5.6	1.4			1.4*
New Zealand	284	3.7	890	5.9	1.1			1.1*
*: Significant statistical difference, P < 0.05.
Abbreviation: UK, United Kingdom; USA, United States of America; APC, annual percent change; AAPC, average annual percent change;

Table 2

Age-adjusted females multiple myeloma incidence rates per 100,000 person-years (1978–1982 and 2008–2012)
Population	1978–1982(Volume V)		2008–2012(Volume XI)		Trend1 APC(%)	Trend2 APC(%)	Join-point	AAPC(%)
Population	Cases	Rate	Cases	Rate	Trend1 APC(%)	Trend2 APC(%)	Join-point	AAPC(%)
Africa
Uganda	-	-	23	1.4	4.1			4.1
Eastern Asia
China	195	0.6	2347	1.0	1.8			1.8*
Korea	-	-	3521	1.4	3.8			3.8*
Japan	286	1.1	3122	1.6	1.1			1.1*
Southeastern Asia
Philippines	9	0.3	212	0.8	9.9	-1.9	1995	3.8*
Thailand	-	-	372	1.1	6.4			6.4*
Southwestern Asia
India	100	0.8	988	0.9	0.3			0.3
Kuwait	14	2.0	53	1.7	-0.8			-0.8
Turkey	-	-	776	2.3	5.3			5.3
Bahrain	-	-	19	1.6	1.1			1.1
Israel	422	2.7	947	3.9	1.7			1.7
Central and Eastern Europe
Czech Republic	-	-	1038	2.0	0.2			0.2
Poland	83	1.3	1255	2.3	2.3			2.3*
Bulgaria	-	-	472	1.3	2.4			2.4
Belarus	-	-	770	1.8	3.9			3.9*
Slovakia	248	1.6	489	3.5	2.5			2.5*
Northern Europe
Denmark	452	2.0	821	3.1	1.0			1.0*
Estonia	-	-	200	2.6	3.1			3.1*
Ireland	10	0.9	518	3.1	0.7			0.7
Iceland	34	2.4	39	3.2	0.9			0.9
Norway	536	2.9	832	3.7	0.9			0.9
Lithuania	-	-	412	2.5	1.9			1.9
UK	7361	2.1	20111	3.5	1.5			1.5*
Southern Europe
Croatia	-	-	447	1.9	2.6			2.6
Cyprus	-	-	96	2.9	6.4			6.4
Italy	99	2.0	4965	3.4	2.7	-0.3	2000	1.7*
Malta	-	-	40	2.0	-2.7			-2.7
Slovenia	76	1.4	288	2.4	3.6			3.6
Spain	85	1.3	1422	2.7	1.6			1.6*
Western Europe
Austria	-	-	1151	2.6	0.6			0.6
France	179	1.9	1878	3.2	1.6			1.6*
Germany	1160	1.3	9064	2.9	3.6	1.0	2000	2.7*
The Netherlands	536	2.9	2538	3.2	0.7			0.7
Switzerland	183	2.2	701	3.2	1.1			1.1*
North America
Canda	4023	2.7	3714	3.2	0.5			0.5*
USA	1631	3.2	144340	3.7	0.5			0.5*
Central and South America
Chile	-	-	117	2.2	-1.0			-1.0
Brazil	117	2.6	258	2.6	1.5			1.5
Colombia	23	1.4	203	1.8	1.3			1.3
Costa Rica	36	2.0	54	0.7	-3.5			-3.5*
Ecuador	-	-	186	1.5	2.2			2.2
Oceania
Australia	638	2.3	6634	3.6	1.4			1.4*
New Zealand	247	2.5	638	3,6	1.0			1.0*
*: Significant statistical difference, P < 0.05.
Abbreviation: UK: United Kingdom; USA: APC, annual percent change; AAPC, average annual percent change;

Temporal trends were similar markedly for both sexes. As shown in Fig. 1 and Figure S2, trends in multiple myeloma incidence rates were plotted by sex and countries from 1978–1982 to 2008–2012. Twenty countries showed significant increasing trends (all P < 0.05), with the largest increase in Thailand (AAPC = 4.8% for males and 6.8% for females), and one country (Costa Rica for males and females) displayed significant decreasing trends. For males, among European countries, Bulgaria, Denmark, Estonia, France, Germany, Lithuania, Norway, Spain, Slovakia, and UK had significant increasing trends (AAPCs = 3.4%, 1.1%, 3.7%, 2.0%, 3.1%, 2.7%, 0.6%, 1.7%, 2.1% and 1.7%, respectively). Among American countries, the US and Canada showed steady increasing trends (AAPCs = 0.7% and 0.6%, respectively), whereas Costa Rica displayed significant decreasing trend (AAPC=-2.9%, P < 0.05). In Oceania, increasing trends were found over time in Australia and New Zealand (AAPCs = 1.4% and 1.1%, respectively). In Asia, Korea, Thailand and Turkey displayed similar great increasing trends (AAPCs = 3.3%, 4.8% and 5.5%, respectively), and China, Japan, Israel showed relatively small increasing trends (AAPCs = 1.9%, 0.9% and 1.4%, respectively). It was noteworthy that Israel revealed declining trends before 1990 and then increase, whereas Norway showed declining trends before 1995 and then increase. There was no difference in trends between males and females in these countries.

Multiple myeloma is rare in young patients, especially before 40 years at diagnosis, representing less than 2% of all patients with MM^[21]. The age-specific rates of MM starting from 40 years old were shown for males and females by birth cohort. As shown in Fig. 2 and Fig. 3, the non-parallel phenomenon between age-specific incidence rate and birth cohort indicated obvious cohort effect in most countries. Both sexes showed that the incidence rates increased with age in all birth cohorts and the incidence rate of most age groups increased steadily with birth cohorts in most countries. However, decreasing rates for recent birth cohorts were seen in Croatia, Cyprus, Estonia, Iceland, Poland, Czech Republic, Colombia, and Ecuador for males (Fig. 2A and Fig. 3A); and in Croatia, Cyprus, Germany, Iceland, Ireland, Czech Republic, Colombia, and Costa Rica for females (Fig. 2B and Fig. 3B). In Austria, Croatia, Cyprus, Estonia, Germany, and Italy, the incidence rates reached peak in 1910–1920 birth cohorts. In Europe, U-shaped and reversed U-shaped trends were discovered for males in Belarus, Croatia, Italy, and Poland; 40 to 59 years old in Denmark; 40 to 54 years old in Lithuania, Slovakia, and Switzerland; 40 to 49 years old in Czech Republic; 55 to 64 years old in Netherlands (Fig. 2A). For females, U-shaped and reversed U-shaped trends were found in Belarus, Croatia, and Poland; 40 to 59 years old in Denmark; 40 to 54 years old in Lithuania and Switzerland; 40 to 49 years old in Czech Republic (Fig. 2A). Incidence rate gradually decreased from 55–75 years old for males and 40–59 females in Austria. In non-Europe, U-shaped and reversed U-shaped trends were discovered for males in Israel and Ecuador; 40 to 69 years old in China and Japan, (Fig. 3A) as well as for females who were in Israel and Ecuador (Fig. 3B). U-shaped and reversed U-shaped trends of birth cohorts mainly occurred in middle and older age groups and indicated that the risks of the incidence of MM increased in the middle and older birth cohorts. It was observed that rates in males were slightly higher than females in each age group in most countries.

Age-specific rates per 100,000 person-years and incidence rate ratios by birth cohort in all countries for both sexes were in Figs. 4–7. The incidence rates of both males and females increased with age. Belarus, Bulgaria, Denmark, and Czech Republic existed peak age at diagnosis for both sexes, and Lithuania, Poland, The Netherlands, and Korea for females. The incidence rate ratios of both sexes increased with birth cohorts in most countries. For males, however, the recent generations went to be flat in Austria, Cyprus, Italy, Spain, Switzerland, the Netherlands, Canada, Ecuador, Korea, Malta, Philippines, USA, and decreased in Iceland and Costa Rica (Figre 4 and Fig. 5). For females, cohort-specific incidence rate ratios among recent generations became plateau in Austria, Czech Republic, Ireland, Switzerland, The Netherlands, Canada, Colombia, India, Kuwait, USA, and decreased in Iceland, Chile, Costa Rica, and Korea (Figre 6 and Fig. 7). A reversed-U-shaped or V-shaped trend was observed for Cyprus, Italy, and Chile in males, and for Malta, Chile, and Colombia in females. In addition, cohort-specific incidence rate ratios increased rapidly in Belarus, Bulgaria, and Philippines cohorts born before 1920 for males, and in Ireland and Slovakia cohorts born before 1990 for females. Cohort-specific incidence rate ratios for both sexes decreased in Iceland for cohorts born since 1960. The lowest risks mainly occurring in the 1900 to 1910 birth cohorts in most countries for both sexes.

The incidence rates and risk of MM varied among countries worldwide. In 2008–2012, significant differences between sexes were observed in 43 countries, with male rates about 1- to 2-fold higher than female rates. MM incidence rates were highest in North America, Oceania, and Northern Europe and lowest in Africa, Eastern Asia, and Southeastern Asia. The highest rates occurred in New Zealand and Norway for males and in Israel for females. From 1978 to 2012, twenty countries revealed significantly increasing trends and one country displayed a significant decreasing trend for both sexes. The incidence rates increased with age in all birth cohorts and most age groups increased steadily with birth cohorts in most countries. However, pronounced cohort-specific declines in risk for recent birth cohorts were seen in Croatia, Cyprus, Estonia, Iceland, Poland, Czech Republic, Colombia, and Ecuador for males, and in Croatia, Cyprus, Germany, Iceland, Ireland, Czech Republic, Colombia, and Costa Rica for females. Cohort-specific incidence rate ratios increased rapidly in Belarus, Bulgaria, and Philippines cohorts born before 1920 for males, and in Ireland and Slovakia cohorts born before 1990 for females. Cohort-specific incidence rate ratios for both sexes decreased in Iceland for cohorts born since 1960.

In most countries, males MM rates were 1- to 2- fold higher than females rates. The mechanisms driving this difference are poorly understood. In myeloma, the main genetic abnormalities causing clonal plasma cell population are hyperdiploidy and immunoglobulin heavy chain gene (IGH) translocations^[22]. Boyd et al^[23] found gender-dependent differences in the prevalence of hyperdiploidy and IGH translocations in myeloma patients, in which hyperdiploidy was more common in men and IGH translocations was more common in women. Hyperdiploidy or IGH translocations may be influenced by sex chromosomes gene variation, or by hormonal differences between men and women in some way. Female sex-steroids hormones have immunomodulatory effects, which may affect the risk of MM^[24]. Unfortunately, no consensus has been reached between hormone and multiple myeloma as most studies were underpowered. Further studies are warranted to investigate sex difference in MM.

The relative contribution of genetic and environmental factors to the incidence rate of MM remains uncertain. A population-based migrant study specific for plasma cell neoplasm^[25] in Chinese suggested that the incidence in British Columbia Chinese populations was similar to Hong Kong Chinese, but was much lower than that in the British Columbia non-Chinese background population. The incidence of MM in Asian showed a similar in risk when they move to USA and Australia^[26]. These data highlight the strong impact of genetic component on MM risk. Global variations and temporal trends in the incidence of MM can be attributed to changes in risk factors, including black race, family history and the presence of a precursor disease status (monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM)). It is consistent with previous research conclusions that MM incidence in the African American population is two-folds that of the European American population, whereas the incidence of MM is lower in Asians^{[27, 28]}. Family history of MM or a related plasma cell dyscrasia (such as MGUS) is a strong risk factor for MM. A Swedish cohort study showed myeloma risk is 2.3 times higher in people with a first-degree relative with myeloma compared with the general population^[29]. A systematic review showed myeloma risk is 50% higher in people with pernicious anaemia compared with those without the disease^[30], and MGUS risk is 67% higher in people with pernicious anaemia.

Obesity is the only modifiable factor in MM recognized by the World Health Organization^[31]. Myeloma risk is 12% higher per 5-unit body mass index (BMI) increment^[32], and increases in males and females for both overweight and obesity categories^[33]. In a meta-analysis of 11 cohort studies conducted in the United States, Asia and Europe, the relative risk of MM developing due to obesity was 1.14 for males and 1.13 for females^[34]. The mechanism of the link between obesity and MM remains unclear and may be explained by the following hypothesis. Adipose tissue can secrete a number of adipocytokines: interleukin-6, tumor necrosis factor-alpha (TNF-α), adiponectin, leptin, resistin, and visfatin, which regulate energy metabolism, hematopoiesis, inflammation and tumorigenesis^[35]. For example, interleukin-6 (IL-6) is known to be an effective myeloma cell growth factor, obese people may produce more of the protein IL-6, affecting proliferation and development of normal and malignant plasma cells^[34]. Decreased circulating adiponectin and increased leptin levels were associated with the occurrence and development of MM^[36]. The lower MM incidence for women than men may be due in part to their body mass index. Besides, obesity may shorten the latency period from benign to malignant diseases. A recent population-based study reported a faster rate of transformation from MGUS to multiple myeloma among patients who are obese compared with individuals of normal weight^[37].

Our results suggested that, in addition to an age effect, birth cohort effect contributed to the increasing trend in incidence of MM. The incidence rate of all 43 countries increased with age. The older birth cohort has a greater impact on the incidence rate of MM, which suggested that occupation or environmental exposure may be a role in the pathogenesis of MM. One possibility is that the occupations of older birth groups are mainly related to agriculture, because farmers commonly experienced exposures which might contribute to the occurrence of MM include infectious microorganisms, solvents and pesticides^[38]. Another possibility is that people are increasingly exposed to engine exhaust^[39]. On the other hand, lifestyle or persistence of some environmental pollutants, such as polychlorinated biphenyls, polychlorinated dibenzo-p-dioxins, and polychlorinated dibenzofurans, may play a role in the pathogenesis of MM^[40]. These findings provide a theoretical basis for further analytical epidemiological studies to find the cause of MM.

This is the first study to provide a global geographic variations in MM incidence and temporal trends by applying an age-period-cohort model using the most up-to-date CI5 data. Nevertheless, there are some limitations. Firstly, rates for developing or poor countries may be underestimated, while developed countries may be overestimated. Secondly, random variation may confounding the results for females and low risk populations due to small numbers. Thirdly, we cannot estimate trends in African countries due to lack of information in the databases. Lastly, the delay of CI5-related studies is a common limitation.

In conclusion, our study shows a significant increase in MM incidence for both sexes worldwide from 1978 to 2012. These unfavorable trends may be due to changes in genetic factors, environmental exposure and lifestyle in the populations, including a precursor disease status, environmental pollutants, and the increasing obesity rates worldwide. The cohort analysis also suggested the incidence rate of most age groups increased steadily with birth cohorts in most countries. Despite the unfavorable incidence trends worldwide, in some countries, the declines were observed in recent birth cohorts. The reason for countries with a cohort-specific increase in risk for recent birth cohorts should be explored further with etiology studies. These findings may help predict future changes in incidence of MM.

AAPC, average annual percent change; APC, annual percent change; ASR, Age-standardized incidence rates; BMI, body mass index; CI5, Cancer Incidence in Five Continents database; HDM-ASCT, high-dose melphalan followed by autologous stem-cell transplant; IGH, immunoglobulin heavy chain gene; IL-6, interleukin-6; IRR, incidence rate ratios; MGUS, monoclonal gammopathy of undetermined significance; MM, multiple myeloma; NCI, National Cancer Institute; TNF-α, tumor necrosis factor-alpha.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Availability of data and materials

The data analyzed in this study were obtained from m the Cancer Incidence in Five Continents at http://ci5.iarc.fr/CI5I-X/Pages/download.aspx.

Competing interests

The authors declare that they have no competing interests.

Funding

This study was supported by the National Key Project of Research and Development Program of China [Grant 2021YFC2500400], and National Natural Science Foundation of China [Grants 81974439, 81974488].

Authors’ Contributions

Chenyang Li designed the study, did the statistical analysis and drafted the manuscript, Xiao Lin participate in picture modification. Fengju Song reviewed and revised the manuscript. All authors approved the final version.

Acknowledgements

Not applicable.

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No competing interests reported.

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Global patterns and trends in multiple myeloma incidence: Age, period and birth cohort analysis

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