Literature DB >> 29573332

Epidemiology of multiple myeloma in 17 Latin American countries: an update.

Maria Paula Curado1,2,3, Max M Oliveira1,4, Diego R M Silva1, Dyego L B Souza5.   

Abstract

The objective of this study was to describe incidence, mortality rates, and trends for multiple myeloma (MM) in Latin America (LA), contributing to better knowledge on the epidemiology of MM in this continent. Incidence data were extracted from the International Agency for Research on Cancer (IARC), for the period 1990-2007. Mortality data were obtained for 17 countries from the World Health Organization, for the period 1995-2013. Annual average percentage change (AAPC) and 95% confidence interval (95% CI) were calculated for incidence and mortality. The average incidence rate of MM was higher in Cali (Colombia). For the age-group over 60 years old, rates were 14.2 and 12.8 per 100,000 inhabitants for men and women, respectively. Increasing incidence trends were verified for Cali (Colombia). Mortality rates were higher among men; most countries presented increasing trends, and the highest increments were observed in Guatemala (12.5% [95% CI: 10.6; 14.5] in men; 8.8% [95% CI: 7.8; 9.8] in women), Ecuador (5.5% [95% CI: 5.0; 6.0] in men; 3.7 [95% CI: 3.1; 4.3] in women), Paraguay (2.9% [95% CI: 2.3; 3.5] in men; 3.2% [95% CI: 2.1; 4.3] in women), and Brazil (1.4% [95% CI: 1.3; 1.5] in men; 0.9% [95% CI: 0.8; 1.0] in women). Multiple myeloma presented heterogeneous incidence patterns in Cali (Colombia), Quito (Ecuador), and Costa Rica. Increasing mortality trends were verified for most Latin American countries and could be related to limited access to diagnosis and new therapies.
© 2018 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Entities:  

Keywords:  incidence; mortality; multiple myeloma; trend

Mesh:

Year:  2018        PMID: 29573332      PMCID: PMC5943416          DOI: 10.1002/cam4.1347

Source DB:  PubMed          Journal:  Cancer Med        ISSN: 2045-7634            Impact factor:   4.452


Introduction

Multiple myeloma (MM) represents, approximately, 1% of all cancers in the world; although rare, it is the second most frequent hematologic neoplasm 1, 2, 3. Incidence is higher in individuals over 60 years old, in men, in the Black race, and in individuals with family history of this malignancy 4, 5, 6, 7, 8. In the world, in 2012, 144,251 new MM cases were estimated for both sexes, with standardized incidence rates of 1.5/100,000 and 80,019 deaths, with the global standardized mortality rate being 1.0/100,000 1. Incidence rates for White North Americans and for most European countries are similar 1, 2, 3. In South America, the estimated rates are 1.7 for incidence and 1.3/100,000 for mortality 1, 3. Multiple myeloma incidence has increased in Great Britain, the United States, and in West Europe; this increase was attributed to better accessibility to health services and better MM diagnosis 8, 9, 10. Despite the increasing incidence rates for MM, studies that use population data are more frequent in developed countries 8, 9, 10, 11 than in developing countries 12. Latin America is a geographic area with scarce studies on multiple myeloma, a rare malignancy. Within Latin America, the life expectancy of the population is increasing, and therefore, it is relevant to describe the epidemiological profile of MM in Latin American countries. The aim of this study was to describe incidence, mortality rates, and trends for multiple myeloma in selected countries of Latin America, based on data from the existing Population‐Based Cancer Registries and from the mortality database available at the WHO Web site.

Methods

An ecological study is presented herein, based on temporal series, which utilized data on multiple myeloma incidence and mortality (C90) 13, 14 from the databases of the International Agency for Research of Cancer (IARC) and World Health Organization (WHO) 15, 16. Incident cases of MM over a period of 17 years (1990–2007) were extracted from Cancer Incidence in Five Continents—CI5 PLUS 15, which included three PBCRS: two regional registries, Cali (Colombia) and Quito (Ecuador), and one national registry, Costa Rica 15. Regarding mortality, death records of 17 Latin American countries were selected, which represented approximately 90% of the population of Latin America, between 1995 and 2013 (WHO Cancer Mortality Database) 16. The number of cases was extracted, and age‐adjusted specific rates were calculated for two age‐groups (40–59 and 60+) and to all ages. The age‐adjusted specific rates were calculated using the world standard population, according to sex and for selected geographic areas with available data. Standardized incidence and mortality rate ratios were calculated per sex (male:female) with a 95% confidence interval (95% CI). The annual average percentage change (AAPC) was estimated for mortality and incidence with 95% CI, except for Belize, El Salvador, and Suriname, due to lack of cases in the historical series. Statistical analyses were carried out using the R package epitools version 0.5‐9 17 and the Joinpoint Regression Program software, version 4.5.0.0 18.

Results

Between 1990 and 2007, the highest incidence rates of multiple myeloma were observed in Cali (Colombia) and Quito (Ecuador) in the age‐group over 60 years old, with rates ranging from 14.2/100,000 for men to 12.8/100,000 for women. Incidence rate ratios were higher in Quito (Ecuador), 1.4 (95% CI: 1.2; 1.7), and more frequent in men (Table 1, Fig. 1).
Table 1

Age standardized incidence rate (ASIR), number of cases (N), average annual percent change (AAPC), and incidence rate ratio (SIR) for multiple myeloma, according to age and sex, in Cali (Colombia), Costa Rica, and Quito (Ecuador), for the period 1990–2007

PBCRAge‐group (years)MaleFemaleSIR (95% CIa)
ASIR (N)AAPC (95% CIa)ASIR (N)AAPC (95% CIa)
Cali (Colombia)40–594.4 (117) 2.0 (1.4; 2.6) 3.1 (97) 1.6 (0.3; 2.9) 1.4 (1.1; 1.8)
60+14.2 (170) 2.0 (0.9; 3.1) 12.8 (186) 3.5 (2.7; 4.3) 1.1 (0.9; 1.4)
Total2.6 (306) 2.0 (1.1; 2.8) 2.0 (293) 2.8 (2.0; 3.6) 1.3 (1.1; 1.5)
Costa Rica40–592.1 (115) −3.6 (−4.6; −2.5) 1.6 (90)0.8 (−0.4; 2.0) 1.3 (1.1; 1.6)
60+9.1 (237) −2.0 (−2.6; −1.4) 7.3 (202) −3.9 (−4.6; −3.2) 1.2 (1.1; 1.4)
Total1.5 (366) −2.7 (−3.1; −2.4) 1.2 (303) −2.5 (−3.1; −1.9) 1.3 (1.1; 1.4)
Quito (Ecuador)40–593.6 (65) 8.5 (7.5; 9.6) 2.3 (46) −1.1 (−2.1; −0.1) 1.6 (1.2; 2.1)
60+13.5 (118) 2.6 (1.7; 3.4) 10.3 (109) −0.7 (−1.1; −0.2) 1.3 (1.1; 1.6)
Total2.3 (194) 4.1 (3.5; 4.7) 1.6 (159) −0.9 (−1.5; −0.3) 1.4 (1.2; 1.7)

95% confidence interval. Bold represents statistically significant values (p<0.05).

Figure 1

Multiple myeloma age‐adjusted incidence rates (95% confidence interval) for sex, age above 60 years, for Cali (Colombia), Costa Rica, and Quito (Ecuador), for the period 1990–2007. 95% CI: 95% confidence interval. The gray line represents trends over the period.

Age standardized incidence rate (ASIR), number of cases (N), average annual percent change (AAPC), and incidence rate ratio (SIR) for multiple myeloma, according to age and sex, in Cali (Colombia), Costa Rica, and Quito (Ecuador), for the period 1990–2007 95% confidence interval. Bold represents statistically significant values (p<0.05). Multiple myeloma age‐adjusted incidence rates (95% confidence interval) for sex, age above 60 years, for Cali (Colombia), Costa Rica, and Quito (Ecuador), for the period 1990–2007. 95% CI: 95% confidence interval. The gray line represents trends over the period. Increasing incidence trends for MM were observed, for both sexes, in Cali (2.0% [95% CI: 1.1; 2.8] in men; 2.8% [95% CI: 2.0; 3.6] in women), higher in women. Incidence trends by age‐group followed similar patterns in Cali (Colombia), Costa Rica, and Quito (Ecuador) (Table 1, Figs. 1 and 2).
Figure 2

Multiple myeloma age‐adjusted incidence rates (95% confidence interval), by sex, for Cali (Colombia), Costa Rica, and Quito (Ecuador), for the period 1990–2007. 95% CI: 95% confidence interval. The gray line represents trends over the period.

Multiple myeloma age‐adjusted incidence rates (95% confidence interval), by sex, for Cali (Colombia), Costa Rica, and Quito (Ecuador), for the period 1990–2007. 95% CI: 95% confidence interval. The gray line represents trends over the period. Between 1995 and 2013, the highest MM mortality rates were observed in Chile (15.1/100,000 in men and 11.9/100,000 in women). Mortality rate ratios were higher in men for all countries and statistically significant (higher than 1), for most countries studied (Table 2).
Table 2

Age standardized mortality rate (ASMR) per 100,000, number (N) of deaths and mortality rate ratio (SMR) for multiple myeloma, by sex and age‐group, for 17 Latin American populations, in the period 1995–2013

PopulationData availabilityAge‐groupsASMR (N)SRM (95% CI*)
MaleFemale
Argentina1997–201340–591.5 (1028)1.1 (805) 1.4 (1.2; 1.5)
60+8.9 (3791)6.5 (4068) 1.4 (1.3; 1.4)
Total1.3 (4896)1.0 (4910) 2.2 (2.1; 2.3)
Belize1997–201340–591.2 (4)1.4 (4)0.9 (0.2; 3.2)
60+3.7 (5)2.9 (4)1.3 (0.3; 4.9)
Total0.7 (9)0.6 (8)1.2 (0.6; 2.4)
Brazil1996–201340–591.5 (4680)1.1 (3907) 1.4 (1.3; 1.4)
60+8.4 (10977)6.6 (11655) 1.3 (1.2; 1.3)
Total1.2 (16018)1.0 (15819) 1.2 (1.2; 1.2)
Chile1997–201340–592.3 (724)1.6 (517)1.0 (0.9; 1.1)
60+15.1 (2383)11.9 (2584)1.0 (1.0; 1.1)
Total2.2 (3134)1.6 (3120)1.0 (1.0; 1.1)
Colombia1997–201340–591.3 (880)1.0 (731) 1.3 (1.2; 1.4)
60+7.4 (2011)5.8 (1972) 1.3 (1.2; 1.4)
Total1.1 (2954)0.9 (2752) 1.2 (1.2; 1.3)
Costa Rica1997–201340–591.6 (117)1.3 (99)1.2 (1.0; 1.6)
60+12.4 (444)8.8 (355) 1.4 (1.2; 1.6)
Total1.7 (571)1.2 (457) 1.4 (1.3; 1.6)
Ecuador1997–201340–590.9 (168)0.6 (120) 1.5 (1.2; 1.9)
60+4.4 (415)3.4 (362) 1.3 (1.1; 1.5)
Total0.7 (600)0.5 (500) 1.4 (1.3; 1.6)
El Salvador1997–201340–590.2 (16)0.2 (18)1.0 (0.5; 2.0)
60+0.8 (35)0.5 (28)1.6 (1.0; 2.7)
Total0.1 (53)0.1 (49)1.0 (0.7; 1.5)
Guatemala2000–201340–590.4 (40)0.2 (31) 2.0 (1.2; 3.2)
60+1.2 (68)1.1 (70)1.1 (0.8; 1.5)
Total0.2 (111)0.2 (113)1.0 (0.8; 1.2)
Mexico1998–201340–591.4 (2047)1.2 (1789) 1.2 (1.1; 1.2)
60+6.5 (4308)4.8 (3782) 1.4 (1.3; 1.4)
Total1.0 (6559)0.8 (5702) 1.3 (1.2; 1.3)
Nicaragua1997–201340–590.6 (37)0.4 (30)1.5 (0.9; 2.4)
60+2.4 (60)1.3 (41) 1.9 (1.2; 2.8)
Total0.4 (105)0.2 (74) 2.0 (1.6; 2.6)
Panama1998–201340–591.8 (88)1.2 (61) 1.5 (1.1; 2.1)
60+10.2 (260)10.2 (210)1.0 (0.8; 1.2)
Total1.5 (356)1.1 (275) 1.4 (1.2; 1.6)
Paraguay1996–201340–590.7 (62)0.6 (48)1.2 (0.8; 1.7)
60+3.9 (144)3.6 (149)1.1 (0.9; 1.4)
Total0.6 (215)0.5 (200)1.2 (1.0; 1.4)
Peru1999–201340–590.9 (335)0.6 (228) 1.5 (1.3; 1.8)
60+6.2 (1086)3.6 (733) 1.7 (1.6; 1.9)
Total0.9 (1468)0.5 (990) 1.8 (1.7; 1.9)
Suriname1995–201340–591.4 (12)1.0 (9)1.4 (0.6; 3.3)
60+10.7 (41)2.8 (14) 3.8 (2.0; 7.2)
Total1.5 (53)0.5 (24) 3.0 (1.9; 4.8)
Uruguay1997–201040–592.1 (106)1.8 (104)1.2 (0.9; 1.5)
60+14.2 (535)10.5 (641) 1.4 (1.2; 1.5)
Total2.0 (648)1.6 (747) 1.3 (1.1; 1.4)
Venezuela1996–201340–591.6 (652)1.3 (571) 1.2 (1.1; 1.4)
60+8.3 (1386)6.8 (1371) 1.2 (1.1; 1.3)
Total1.3 (2109)1.0 (1988) 1.3 (1.2; 1.4)

95% confidence interval.

Age standardized mortality rate (ASMR) per 100,000, number (N) of deaths and mortality rate ratio (SMR) for multiple myeloma, by sex and age‐group, for 17 Latin American populations, in the period 1995–2013 95% confidence interval. Of the 17 studied countries, there was no clear pattern in mortality trends (Fig. 3). For the age‐group over 60 years old, increases were observed in men of seven countries (Brazil, Colombia, Costa Rica, Ecuador, Guatemala, Paraguay, and Uruguay), and decreases were observed in four countries (Argentina, Chile, Panama, and Peru). In women, eight countries presented increasing trends (Brazil, Colombia, Costa Rica, Ecuador, Guatemala, Mexico, Paraguay, and Uruguay), while four countries (Argentina, Chile, Nicaragua, and Peru) presented decreasing trends. The highest decline was observed for men, in Panama (−2.2%; 95% CI:−2.8;−1.5), while the highest increase was verified in Guatemala (15.1% [95% CI: 13.1; 17.2] in men; 10.2% [95% CI: 8.9; 11.4] in women) (Table 3).
Figure 3

Temporal trends in multiple myeloma mortality, according to sex, and age above 60 years, in 17 Latin American countries, for the period 1995–2013. (A) Male; (B) Female.

Table 3

Multiple myeloma mortality trends, by sex and age‐group, for 17 Latin American populations, in the period 1995–2013

PopulationData availabilityAge‐groups (years)AAPC (95% CI)
MaleFemale
Argentina1997–201340–59 −0.8 (−1.0; −0.6) −2.0 (−2.1; −1.8)
60+ −0.6 (−0.7; −0.5) −1.0 (−1.1; −0.9)
Total −0.6 (−0.7; −0.5) −1.1 (−1.2; −1.0)
Brazil1996–201340–59 0.4 (0.3; 0.6) 0.2 (−0.0; 0.5)
60+ 1.8 (1.7; 1.9) 1.2 (1.1; 1.3)
Total 1.4 (1.3; 1.5) 0.9 (0.8; 1.0)
Chile1997–201340–59 −0.9 (−1.2; −0.5) −1.1 (−1.6; −0.6)
60+ −0.3 (−0.5; −0.1) −0.5 (−0.8; −0.1)
Total −0.4 (−0.7; −0.2) −0.6 (−0.9; −0.3)
Colombia1997–201340–59 −0.9 (−1.2; −0.5) −0.6 (−1.0; −0.1)
60+ 0.7 (0.5; 0.8) 1.3 (1.1; 1.5)
Total 0.3 (0.1; 0.4) 0.8 (0.6; 1.0)
Costa Rica1997–201340–59 1.9 (0.8; 2.9) −0.2 (−0.8; 0.4)
60+ 1.0 (0.5; 1.5) 0.8 (0.4; 1.2)
Total 1.1 (0.5; 1.6) 0.6 (0.3; 1.0)
Ecuador1997–201340–59 3.1 (2.2; 4.1) 5.5 (5.2; 5.9)
60+ 6.8 (6.3; 7.2) 3.2 (2.5; 3.9)
Total 5.5 (5.0; 6.0) 3.7 (3.1; 4.3)
Guatemala2000–201340–59 9.2 (7.5; 10.9) 9.3 (6.9; 11.8)
60+ 15.1 (13.1; 17.2) 10.2 (8.9; 11.4)
Total 12.5 (10.6; 14.5) 8.8 (7.8; 9.8)
Mexico1998–201340–59 0.4 (0.1; 0.6) −0.1 (−0.3; 0.2)
60+0.0 (−0.1; 0.2) 1.0 (0.8; 1.1)
Total0.0 (−0.1; 0.2) 0.5 (0.4; 0.7)
Nicaragua1997–201340–59−0.4 (−2.0; 1.2) 7.2 (6.0; 8.5)
60+0.6 (−0.4; 1.5) −2.2 (−3.1; −1.3)
Total−0.1 (−0.9; 0.8) 1.1 (0.6; 1.6)
Panama1998–201340–59 −5.2 (−6.5; −4.0) 0.2 (−1.3; 1.8)
60+ −2.2 (−2.8; −1.5) 0.3(−0.4; 0.9)
Total −2.6 (−3.2; −2.1) 0.2 (−0.3; 0.8)
Paraguay1996–201340–590.9 (−0.3; 2.2)−0.4 (−1.9; 1.0)
60+ 4.0 (2.8; 5.2) 4.4 (3.0; 5.9)
Total 2.9 (2.3; 3.5) 3.2 (2.1; 4.3)
Peru1999–201340–59−0.2 (−0.8; 0.4)0.1 (−0.5; 0.6)
60+ −0.6 (−1.0; −0.1) −0.6 (−1.0; −0.2)
Total−0.4 (−0.8; 0.1)−0.1 (−0.5; 0.2)
Uruguay1997–201040–59 −1.1 (−2.0; −0.2) 3.6 (2.4; 4.8)
60+ 2.3 (1.7; 2.8) 0.7 (0.3; 1.1)
Total1.6 (0.9; 2.2) 1.6 (1.1; 2.0)
Venezuela1996–201340–59 1.3 (1.0; 1.7) 0.8 (0.4; 1.2)
60+−0.2 (−0.5; 0.1) 0.2 (0.0; 0.3)
Total0.2 (0.0; 0.4) 0.3 (0.2; 0.4)

AAPC, average annual percentage of change.

Temporal trends in multiple myeloma mortality, according to sex, and age above 60 years, in 17 Latin American countries, for the period 1995–2013. (A) Male; (B) Female. Multiple myeloma mortality trends, by sex and age‐group, for 17 Latin American populations, in the period 1995–2013 AAPC, average annual percentage of change.

Discussion

The incidence of multiple myeloma in Cali (Colombia), Costa Rica, and Quito (Ecuador) occurred more frequently in the age‐group over 60 years of age, with higher rates in men, similar to other studies 9, 10. The known epidemiological characteristics of MM include higher incidence in males and the elderly (≥60 years of age). Increasing incidence trends were detected in Cali and in Quito for men; decreasing trends were verified in Costa Rica, for both genders, and in Quito, for women. Risk factors associated with MM include family history of lymphoid malignancy and ethnicity, being more common in the Black race. Other risk factors include occupational and environmental exposure to benzene, pesticides, DDT, petroleum derivative, and ionizing radiation [19, 20, 21, 22, 23]. The accepted risk factors for multiple myeloma are aging, male gender, Black race, and positive family history. Possible associated risk factors are overweight and obesity, low consumption of fish and green vegetables, AIDS, and herpes zoster 22, 23, 24, 25. Consumption of tobacco 26 was inconclusive, while alcohol consumption could be associated with reduced risk 27. An ecological study that analyzed data from 175 countries identified an association between low ultraviolet B and vitamin D and higher incidence of MM 28, which could explain the differences in incidence across countries. In Latin America, a case–control from Uruguay indicated elevated risk of MM in those who consumed more processed meat, red meat, and milk—the pattern of risk food was driven by red meat 29. The different prevalence of these risk factors could partially explain the differences observed in LA countries 30, 31. This heterogeneous pattern of MM incidence and mortality could reflect limited access to diagnosis and treatment, and maybe some incompleteness of the PBCRs and in mortality databases. Increased incidence in European countries, in the United States, and in China indicates that access to health services leads to more precise diagnosis and early treatment, which could explain the increase in incidence 9, 10, 32. Another hypothesis for the differences between incidence and mortality is racial composition. An American study demonstrated increased MM incidence, which is higher in non‐Hispanic White individuals, for both sexes, and in Black men 10. Black patients in America were found to be 37% less likely to undergo stem cell transplantation and 21% less likely to be treated with bortezomib and lenalidomide 33, 34, and therefore, mortality rates are higher in people of the Black race. The highest MM mortality rates were observed in men over the age of 60, increasing with age, similar to incidence. However, heterogeneity in mortality and incidence rates suggests gender differences could be due to delays in access to diagnosis and treatment 35, 36. A Brazilian study showed the effectiveness of reference centers for patients with multiple myeloma, with reduced waiting times until bone marrow transplantation 37. The increase in incident rates over the age of 60 is related to increased life expectancies. 38, 39. Changes in MM treatment have recently affected mortality. Studies have shown an increase in survival rates, when stratifying by periods according to the available treatments 40, 41, 42, 43. However, stratification by age and ethnic group revealed that only patients under the age of 65 and non‐Hispanic White individuals presented significantly better survival 10. Also, the introduction of new medications, for example bortezomib, favored the increase in survival in intermediate‐ or high‐risk myeloma cases 41, 42, 43, 44, 45, although new medications are expensive and not affordable to all patients. Access to new drugs and differences in regulations across Latin American countries could have also influenced the differences observed in mortality 46. The increasing incidence and mortality trends in the three cities (Cali, Quito, and Costa Rica) indicate a clear necessity of better organizing access to diagnosis and treatment for this malignancy. In Latin America, fragmented structures are present with consequent unequal allocation of human and material resources in large urban centers 47, 48. Moreover, there are few hematologists in Latin America, with estimates of 0.9 hematologists per 100,000 inhabitants, while the US counts with 2.2/100,000 49. Brazilian, Mexican, and Peruvian studies indicate that delays in pathological evaluations affect considerably diagnosis and treatment 50, reducing survival rates. Regarding mortality data quality, differences were detected in coverage and completeness in the 17 countries studied herein, varying from 55% completeness in the Dominican Republic to 90% in Argentina, Chile, Costa Rica, Mexico, Uruguay, and Venezuela. Moreover, the percentage of ill‐defined deaths varied from 5% (Costa Rica and Mexico) to 24% (El Salvador) 16. Despite these differences, data were validated by International Organizations 1, 2, 3 and can be used to describe MM mortality in 17 Latin American countries. An ecological study was presented herein, with scarce data on incidence and more comprehensive data on LA mortality. The existing socioeconomic differences across Latin American countries are reflected in the quality of mortality data 51. For cancer incidence estimates, coverage of LA PBCRs is limited to approximately 20% 46. Despite these limitations, this study described MM incidence in three cities and MM mortality trends for 17 Latin American countries. Both incidence and mortality presented differences, with increasing incidence trends in two of three cities (except Costa Rica). Increasing MM mortality was verified in seven countries, which could be related to late diagnosis and barriers to treatment and new drugs. This study described multiple myeloma incidence in three cities and mortality in 17 Latin American countries. MM is a rare neoplasm that is more frequent in age‐groups over 60 years old. The expected increase in Latin American life expectancy will certainly increase the incidence of MM.

Conflict of Interest

None declared.
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Journal:  Ann Glob Health       Date:  2014 Sep-Oct       Impact factor: 2.462

6.  A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010.

Authors:  Stephen S Lim; Theo Vos; Abraham D Flaxman; Goodarz Danaei; Kenji Shibuya; Heather Adair-Rohani; Markus Amann; H Ross Anderson; Kathryn G Andrews; Martin Aryee; Charles Atkinson; Loraine J Bacchus; Adil N Bahalim; Kalpana Balakrishnan; John Balmes; Suzanne Barker-Collo; Amanda Baxter; Michelle L Bell; Jed D Blore; Fiona Blyth; Carissa Bonner; Guilherme Borges; Rupert Bourne; Michel Boussinesq; Michael Brauer; Peter Brooks; Nigel G Bruce; Bert Brunekreef; Claire Bryan-Hancock; Chiara Bucello; Rachelle Buchbinder; Fiona Bull; Richard T Burnett; Tim E Byers; Bianca Calabria; Jonathan Carapetis; Emily Carnahan; Zoe Chafe; Fiona Charlson; Honglei Chen; Jian Shen Chen; Andrew Tai-Ann Cheng; Jennifer Christine Child; Aaron Cohen; K Ellicott Colson; Benjamin C Cowie; Sarah Darby; Susan Darling; Adrian Davis; Louisa Degenhardt; Frank Dentener; Don C Des Jarlais; Karen Devries; Mukesh Dherani; Eric L Ding; E Ray Dorsey; Tim Driscoll; Karen Edmond; Suad Eltahir Ali; Rebecca E Engell; Patricia J Erwin; Saman Fahimi; Gail Falder; Farshad Farzadfar; Alize Ferrari; Mariel M Finucane; Seth Flaxman; Francis Gerry R Fowkes; Greg Freedman; Michael K Freeman; Emmanuela Gakidou; Santu Ghosh; Edward Giovannucci; Gerhard Gmel; Kathryn Graham; Rebecca Grainger; Bridget Grant; David Gunnell; Hialy R Gutierrez; Wayne Hall; Hans W Hoek; Anthony Hogan; H Dean Hosgood; Damian Hoy; Howard Hu; Bryan J Hubbell; Sally J Hutchings; Sydney E Ibeanusi; Gemma L Jacklyn; Rashmi Jasrasaria; Jost B Jonas; Haidong Kan; John A Kanis; Nicholas Kassebaum; Norito Kawakami; Young-Ho Khang; Shahab Khatibzadeh; Jon-Paul Khoo; Cindy Kok; Francine Laden; Ratilal Lalloo; Qing Lan; Tim Lathlean; Janet L Leasher; James Leigh; Yang Li; John Kent Lin; Steven E Lipshultz; Stephanie London; Rafael Lozano; Yuan Lu; Joelle Mak; Reza Malekzadeh; Leslie Mallinger; Wagner Marcenes; Lyn March; Robin Marks; Randall Martin; Paul McGale; John McGrath; Sumi Mehta; George A Mensah; Tony R Merriman; Renata Micha; Catherine Michaud; Vinod Mishra; Khayriyyah Mohd Hanafiah; Ali A Mokdad; Lidia Morawska; Dariush Mozaffarian; Tasha Murphy; Mohsen Naghavi; Bruce Neal; Paul K Nelson; Joan Miquel Nolla; Rosana Norman; Casey Olives; Saad B Omer; Jessica Orchard; Richard Osborne; Bart Ostro; Andrew Page; Kiran D Pandey; Charles D H Parry; Erin Passmore; Jayadeep Patra; Neil Pearce; Pamela M Pelizzari; Max Petzold; Michael R Phillips; Dan Pope; C Arden Pope; John Powles; Mayuree Rao; Homie Razavi; Eva A Rehfuess; Jürgen T Rehm; Beate Ritz; Frederick P Rivara; Thomas Roberts; Carolyn Robinson; Jose A Rodriguez-Portales; Isabelle Romieu; Robin Room; Lisa C Rosenfeld; Ananya Roy; Lesley Rushton; Joshua A Salomon; Uchechukwu Sampson; Lidia Sanchez-Riera; Ella Sanman; Amir Sapkota; Soraya Seedat; Peilin Shi; Kevin Shield; Rupak Shivakoti; Gitanjali M Singh; David A Sleet; Emma Smith; Kirk R Smith; Nicolas J C Stapelberg; Kyle Steenland; Heidi Stöckl; Lars Jacob Stovner; Kurt Straif; Lahn Straney; George D Thurston; Jimmy H Tran; Rita Van Dingenen; Aaron van Donkelaar; J Lennert Veerman; Lakshmi Vijayakumar; Robert Weintraub; Myrna M Weissman; Richard A White; Harvey Whiteford; Steven T Wiersma; James D Wilkinson; Hywel C Williams; Warwick Williams; Nicholas Wilson; Anthony D Woolf; Paul Yip; Jan M Zielinski; Alan D Lopez; Christopher J L Murray; Majid Ezzati; Mohammad A AlMazroa; Ziad A Memish
Journal:  Lancet       Date:  2012-12-15       Impact factor: 79.321

7.  Hematology in Latin America: where are we? Analysis of the reports of Societies of Hematology associated organization of the Highlights of ASH in Latin America.

Authors:  Raul Gabús; Sebastian Galeano; Carmino Antonio de Souza; Scott Howard; Jorge Horacio Millone; Mario Luis Tejerina Del Valle; Jorge Alfaro Lucero; Carmen Rosales; Maria de Los Angeles Del Campo Martinez; José Zarza; Fernando Cauvi; Gabriel Borelli; Mercedes Prieto
Journal:  Rev Bras Hematol Hemoter       Date:  2011

8.  Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012.

Authors:  Jacques Ferlay; Isabelle Soerjomataram; Rajesh Dikshit; Sultan Eser; Colin Mathers; Marise Rebelo; Donald Maxwell Parkin; David Forman; Freddie Bray
Journal:  Int J Cancer       Date:  2014-10-09       Impact factor: 7.396

9.  Occupational cancer in Britain. Haematopoietic malignancies: leukaemia, multiple myeloma, non-Hodgkins lymphoma.

Authors:  Terry Brown; Lesley Rushton
Journal:  Br J Cancer       Date:  2012-06-19       Impact factor: 7.640

10.  Racial disparity in utilization of therapeutic modalities among multiple myeloma patients: a SEER-medicare analysis.

Authors:  Sikander Ailawadhi; Ryan D Frank; Pooja Advani; Abhisek Swaika; M'hamed Temkit; Richa Menghani; Mayank Sharma; Zahara Meghji; Shumail Paulus; Nandita Khera; Shahrukh K Hashmi; Aneel Paulus; Tanya S Kakar; David O Hodge; Dorin T Colibaseanu; Michael R Vizzini; Vivek Roy; Gerardo Colon-Otero; Asher A Chanan-Khan
Journal:  Cancer Med       Date:  2017-11-03       Impact factor: 4.452

View more
  9 in total

1.  Measuring the global, regional, and national burden of multiple myeloma from 1990 to 2019.

Authors:  Linghui Zhou; Qin Yu; Guoqing Wei; Linqin Wang; Yue Huang; Kejia Hu; Yongxian Hu; He Huang
Journal:  BMC Cancer       Date:  2021-05-25       Impact factor: 4.430

2.  Expression of Krüppel-like factor 9 in breast cancer patients and its effect on prognosis.

Authors:  Zirong Jiang; Zhiping Xu; Tinghui Hu; Bin Song; Feng Li; Kaiyin Wang
Journal:  Oncol Lett       Date:  2020-05-29       Impact factor: 2.967

Review 3.  Cannabis, One Health, and Veterinary Medicine: Cannabinoids' Role in Public Health, Food Safety, and Translational Medicine.

Authors:  Sivan Ritter; Lilach Zadik-Weiss; Osnat Almogi-Hazan; Reuven Or
Journal:  Rambam Maimonides Med J       Date:  2020-01-30

4.  Multiple myeloma treatment patterns and clinical outcomes in the Latin America Haemato-Oncology (HOLA) Observational Study, 2008-2016.

Authors:  Vania Tietsche de Moraes Hungria; Deborah M Martínez-Baños; Christian R Peñafiel; Carlos E Miguel; Jorge Vela-Ojeda; Guillermina Remaggi; Fernando B Duarte; Carmen Cao; Maria S Cugliari; Telma Santos; Gerardo Machnicki; Mariana Fernandez; Mariana Grings; Eric M Ammann; Jennifer H Lin; Yen-Wen Chen; Yu-Ning Wong; Paula Barreyro
Journal:  Br J Haematol       Date:  2019-08-07       Impact factor: 6.998

5.  Prevalence and Incidence of Multiple Myeloma in Urban Area in China: A National Population-Based Analysis.

Authors:  Shengfeng Wang; Lu Xu; Jingnan Feng; Yang Liu; Lili Liu; Jinxi Wang; Jack Liu; Xiaojun Huang; Pei Gao; Jin Lu; Siyan Zhan
Journal:  Front Oncol       Date:  2020-01-24       Impact factor: 6.244

6.  Construction of a Prognosis Model of the Pyroptosis-Related Gene in Multiple Myeloma and Screening of Core Genes.

Authors:  Can Li; Hongzheng Liang; Sicheng Bian; Xiaoxu Hou; Yanping Ma
Journal:  ACS Omega       Date:  2022-09-15

7.  The mortality burden of hematological malignancies in Ecuador.

Authors:  David Garrido; Andrés Orquera; Johanna Rojas; Manuel Granja
Journal:  Nepal J Epidemiol       Date:  2021-06-30

8.  Incidence and mortality of multiple myeloma in China, 2006-2016: an analysis of the Global Burden of Disease Study 2016.

Authors:  Jiangmei Liu; Weiping Liu; Lan Mi; Xinying Zeng; Cai Cai; Jun Ma; Lijun Wang
Journal:  J Hematol Oncol       Date:  2019-12-10       Impact factor: 17.388

9.  Association between interleukin gene polymorphisms and multiple myeloma susceptibility.

Authors:  Muhamaad Naveed Shahzad; Iqra Ijaz; Syed Shah Zaman Haider Naqvi; Cheng Yan; Fanli Lin; Shutan Li; Chunlan Huang
Journal:  Mol Clin Oncol       Date:  2020-01-16
  9 in total

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