424
Scand J Rheumatol 2014;43:424–433
LETTERS
NSAID use during pregnancy: maternal characteristics and prescription patterns. A nationwide cohort study V Cejvanovic1,2, E Jimenez-Solem1,2, HE Poulsen1,2,3, JT Andersen1,2
Scand J Rheumatol Downloaded from informahealthcare.com by University of Massachusetts on 04/05/15 For personal use only.
1 Laboratory of Clinical Pharmacology, Copenhagen University Hospital Rigshospitalet, 2Department of Clinical Pharmacology, Copenhagen University Hospital Bispebjerg, and 3Faculty of Health Sciences, University of Copenhagen, Denmark
Non-steroidal anti-inflammatory drugs (NSAIDs) are among the most widely used drugs (1). To identify the characteristics of pregnant women who redeemed at least one prescription of an NSAID, we performed a nationwide cohort study including all registered pregnancies
resulting in a birth in Denmark from 1997 to 2010. All births were identified using the Medical Birth Registry (2). Information on women redeeming an NSAID was retrieved from the National Prescription Register (3). Information on diseases of the musculoskeletal system
Table 1. Basic maternal characteristics.
Total number Age (years) < 20 20–24 25–29 30–34 35 Education (no. of months) < 144 144–155 156–179 > 179 Income (quartiles) Lowest quartile Low quartile Medium quartile High quartile Parity 1 2 3 4 Number of offspring 1 2 3 Body mass index (kg/m2)* < 18.5 18.5–24.9 25.0–29.9 30.0–34.9 35 Smoking during pregnancy Disease of the musculoskeletal system and connective tissue †
Use of NSAIDs
No use of NSAIDs
24 841
886 728
Adjusted p-value 0.0008
446 (1.8) 3705 (14.9) 8258 (33.2) 8041 (32.4) 4391 (17.7 )
13 101 299 318 153
167 (1.5) 741 (11.5) 924 (33.8) 849 (36.0) 047 (17.3)
9162 (37.8) 3803 (15.7) 6601 (27.3) 4655 (19.2)
200 137 253 262
881 (23.9) 556 (16.0) 721 (29.5) 751 (30.6)
7768 (31.3) 7090 (28.5) 5509 (22.2) 4474 (18.0)
220 220 222 223
343 (24.9) 726 (24.9) 313 (25.1) 346 (25.2)
9858 (39.9) 8482 (34.4) 4112 (16.7) 2228 (9.0)
388 324 122 45
217 (44.0) 946 (36.8) 976 (14.0) 024 (5.1)
< 0.0001
< 0.0001
< 0.0001
0.016 23 892 (96.2) 915 (3.7) 34 (0.1)
849 172 (95.8) 36 626 (4.1) 930 (0.1)
424 (3.7) 5998 (52.5) 2726 (23.8) 1348 (11.8) 934 (8.2) 6939 (27.9) 230 (0.9)
17 638 (4.3) 258 918 (63.2) 85 208 (20.8) 31 493 (7.7) 16 325 (4.0) 156 886 (17.8) 1906 (0.2)
< 0.0001
< 0.0001 < 0.0001
* Information on pre-gestational body mass index only available from 2004 to 2010. † Defined as a diagnosis of a disease of the musculoskeletal system and connective tissue within the ICD-10 classification system in the 5-year period before birth. © 2014 Informa Healthcare on license from Scandinavian Rheumatology Research Foundation
www.scandjrheumatol.dk
DOI: 10.3109/03009742.2014.902099
Letters
425 Figure 1. Number of pregnant women giving birth redeeming one or more prescriptions of non-steroidal anti-inflammatory drugs (NSAIDs) during pregnancy between 1997 and 2010. The total number of pregnant women in the period was 911 569. The y-axis represents the percentage of all pregnant women.
3.5 3.0 2.5 2.0 % 1.5
any NSAID ibuprofen diclofenac naproxen other NSAIDs
1.0
Scand J Rheumatol Downloaded from informahealthcare.com by University of Massachusetts on 04/05/15 For personal use only.
0.5 0.0 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Year
and connective tissue (ICD-10 DM group) were from the National Hospital Register (4). Differences in baseline characteristics between exposed and unexposed were calculated using a logistic regression model where maternal age, education, parity, number of offspring in the current pregnancy, smoking during pregnancy, diagnosis of a disease of the musculoskeletal system and connective tissue, and year of birth were included in the model. As information on body mass index (BMI) was only available from 2004, a separate logistic regression model was constructed further including BMI. For all analyses, a p-value of < 0.05 was considered statistically significant. The Danish Data Protection Agency approved the study (No. 2008-41-2517). We identified 911 569 pregnancies resulting in a birth between 1997 and 2010. A total of 24841 (2.7%) redeemed at least one prescription of an NSAID, mainly ibuprofen (63%), at some point during pregnancy. Women redeeming NSAID prescriptions were characterized by being younger, having a lower educational level, lower household income, more prior pregnancies, fewer multiple births, higher BMI, and smoked more during pregnancy compared to unexposed women (Table 1). It is known that, for example, low socio-economic status is associated with higher disease prevalence, which could partly explain our findings (5). Women exposed to NSAIDs were more likely to have a diagnosis of a disease of the musculoskeletal system and connective tissue (0.9%) than unexposed (0.2%), which was to be expected because NSAIDs are often used in the treatment of rheumatic diseases. The rates could be underestimated because they are solely based on hospital diagnoses. From 1997 to 2004 the overall exposure to any NSAID increased from 2.4% to 3.1% (p < 0.0001) and decreased to 2.3% in 2010 (p < 0.0001) (Figure 1). In 2004, The Danish Medicines Agency drew attention to a possible small increased risk of birth defects for NSAID during pregnancy, and the patient information leaflets were
edited (6). This awareness could explain the decrease in exposure to NSAIDs. Fewer women were exposed to an NSAID during pregnancy than before pregnancy (p < 0.0001). The exposure rates decreased throughout pregnancy (1.9% in the first, 0.6% in the second, and 0.4% in the third trimester) compared to before pregnancy (4.4%) and increased again after delivery (3.2%). This decline is probably due to guidelines warning about risk of harmful effects to the foetus, or general fear of medication during pregnancy. Exposure in early pregnancy has been associated with increased risk of miscarriage and birth defects, although the findings are conflicting (1).It is therefore recommended to use NSAID during the first and second trimesters with caution (7). Women with unrecognized pregnancies could account for some of the exposure seen during the first trimester. NSAID exposure in late pregnancy has been associated with adverse foetal effects (1) and NSAID use is contraindicated during the third trimester (7). However, 0.4% of the women in our cohort were exposed to an NSAID during the third trimester. This could indicate a need for NSAID use during the third trimester, despite contraindications, because some inflammatory conditions such as ankylosing spondylitis may, without pharmacological treatment, worsen during pregnancy (8). Furthermore, some women suffering from migraine continue to use NSAIDs during pregnancy (9). Another reason for NSAID exposure in pregnancy is lack of knowledge of potential adverse effects (10). The registers used in the present study have previously been validated and found to be accurately recorded. More than 99% of all births in Denmark have been recorded in the Medical Birth Registry (11) and the completeness of the National Prescription Register has been estimated to be 98% (12). Unfortunately, we have no information on adherence, dosage, and treatment indication, or on overthe-counter drugs.
www.scandjrheumatol.dk
426
In conclusion, we found that women redeeming at least one NSAID prescription during pregnancy differed in several characteristics compared to unexposed. Furthermore, NSAID exposure during pregnancy increased until 2004, and then decreased. Despite NSAIDs being contraindicated in the third trimester, several thousand women were exposed in this period of the pregnancy.
Scand J Rheumatol Downloaded from informahealthcare.com by University of Massachusetts on 04/05/15 For personal use only.
References 1. Bloor M, Paech M. Nonsteroidal anti-inflammatory drugs during pregnancy and the initiation of lactation. Anesth Analg 2013;116:1063–75. 2. Knudsen LB, Olsen J. The Danish Medical Birth Registry. Dan Med Bull 1998;45:320–3. 3. Kildemoes HW, Sørensen HT, Hallas J. The Danish National Prescription Registry. Scand J Public Health 2011;39:38–41. 4. Andersen TF, Madsen M, Jørgensen J, Mellemkjoer L, Olsen JH. The Danish National Hospital Register. A valuable source of data for modern health sciences. Dan Med Bull 1999;46:263–8. 5. Calixto O-J, Anaya J-M. Socioeconomic status. The relationship with health and autoimmune diseases. Autoimmun Rev. Published online: 10 January 2014. doi: 10.1016/j.autrev.2013.12.002. 6. http:\\www.irf.dk/dk/nyheder/nsaid_og_graviditet.htm.
Letters 7. http:\\www.produktresume.dk/docushare/dsweb/GetRendition/ Document-29832/html#bmk1. 8. Ostensen M, Villiger PM, Förger F. Interaction of pregnancy and autoimmune rheumatic disease. Autoimmun Rev 2012;11:A437–46. 9. Nezvalová-Henriksen K, Spigset O, Nordeng H. Maternal characteristics and migraine pharmacotherapy during pregnancy: cross-sectional analysis of data from a large cohort study. Cephalalgia 2009;29:1267–76. 10. Damase-Michel C, Christaud J, Berrebi A, Lacroix I, Montastruc J-L. What do pregnant women know about non-steroidal anti-inflammatory drugs? Pharmacoepidemiol Drug Saf 2009; 18:1034–8. 11. Kristensen J, Langhoff-Roos J, Skovgaard LT, Kristensen FB. Validation of the Danish Birth Registration. J Clin Epidemiol 1996;49:893–7. 12. Sørensen HT, Hansen I, Ejlersen E, Sabroe S, Hamburger H. Identification of patients treated with strong analgesics: an assessment of two Danish information systems with respect to epidemiological research. J Med Syst1996;20:57–65.
Vanja Cejvanovic, Laboratory of Clinical Pharmacology Q7642, Copenhagen University Hospital Rigshospitalet, Tagensvej 20, DK-2200 Copenhagen, Denmark. E-mail: [email protected] Accepted 4 March 2014
Identification of susceptibility genes for systemic lupus erythematosus with a genome-wide gene-based association study S-F Lei1,2, F-Y Deng1,2 1 Centre for Genetic Epidemiology and Genomics, and 2Department of Epidemiology, School of Public Health, Soochow University, Suzhou, Jiangsu, P. R. China
Systemic lupus erythematosus (SLE) is a chronic autoimmune disease. A number of SLE-associated loci have been identified in genome-wide association studies (GWASs) (1–8). Typically, these GWASs used a single nucleotide polymorphism (SNP) as the basic analysis unit. Because of the large number of SNPs tested in GWAS, a stringent significant threshold (typically < 5.0 108) was adopted to control for false positive associations. Consequently, a large number of SNPs with moderate effects might be missed. GATES (Gene-based Association Test using Extended Simes procedure), a rapid and powerful genebased association test (9), can rapidly combine the p-values of SNPs within a gene without relying on raw, individual phenotype and genotype data, and assess the gene-level significance of a statistical association. Based on the publicly available SNP-based p-values from the database of Genotypes and Phenotypes (dbGaP; accession numbers: phs000122 and phs000202) (2, 6), we performed an initial gene-based GWAS in 1311 SLE cases and 3340 controls and a follow-up replication
www.scandjrheumatol.dk
study in 767 SLE patients and 383 non-SLE patients. As shown in Figure 1, the degree of departure in the quantilequantile (QQ) plots is stronger for gene-based p-values than for SNP-based p-values inside the gene, which suggests that the gene-based association analysis is more powerful in detecting the association than the SNPbased analysis. In total, 24 638 genes were tested. The significance level for the Benjamini-Hochberg false discovery rate (FDR) test to control an overall error rate of 0.05 on the whole genome is 2.8 104. According to the significance level, we identified a total of 138 significant genes, with the most significant signal at human leucocyte antigen (HLA)-DQA1 (p = 2.71 1021). As expected, the majority of these associations (120 genes) were mapped to the HLA region. About 72% of the significant genes were replicated in the associations. According to the annotation of the downloaded raw SNP-based p-values, 120 SNPs were significantly associated with SLE after adapting the genome-wide p-value thresholds for significance (p < 5.0 108). These 120
Scand J Rheumatol 2014;43:424–433
LETTERS
NSAID use during pregnancy: maternal characteristics and prescription patterns. A nationwide cohort study V Cejvanovic1,2, E Jimenez-Solem1,2, HE Poulsen1,2,3, JT Andersen1,2
Scand J Rheumatol Downloaded from informahealthcare.com by University of Massachusetts on 04/05/15 For personal use only.
1 Laboratory of Clinical Pharmacology, Copenhagen University Hospital Rigshospitalet, 2Department of Clinical Pharmacology, Copenhagen University Hospital Bispebjerg, and 3Faculty of Health Sciences, University of Copenhagen, Denmark
Non-steroidal anti-inflammatory drugs (NSAIDs) are among the most widely used drugs (1). To identify the characteristics of pregnant women who redeemed at least one prescription of an NSAID, we performed a nationwide cohort study including all registered pregnancies
resulting in a birth in Denmark from 1997 to 2010. All births were identified using the Medical Birth Registry (2). Information on women redeeming an NSAID was retrieved from the National Prescription Register (3). Information on diseases of the musculoskeletal system
Table 1. Basic maternal characteristics.
Total number Age (years) < 20 20–24 25–29 30–34 35 Education (no. of months) < 144 144–155 156–179 > 179 Income (quartiles) Lowest quartile Low quartile Medium quartile High quartile Parity 1 2 3 4 Number of offspring 1 2 3 Body mass index (kg/m2)* < 18.5 18.5–24.9 25.0–29.9 30.0–34.9 35 Smoking during pregnancy Disease of the musculoskeletal system and connective tissue †
Use of NSAIDs
No use of NSAIDs
24 841
886 728
Adjusted p-value 0.0008
446 (1.8) 3705 (14.9) 8258 (33.2) 8041 (32.4) 4391 (17.7 )
13 101 299 318 153
167 (1.5) 741 (11.5) 924 (33.8) 849 (36.0) 047 (17.3)
9162 (37.8) 3803 (15.7) 6601 (27.3) 4655 (19.2)
200 137 253 262
881 (23.9) 556 (16.0) 721 (29.5) 751 (30.6)
7768 (31.3) 7090 (28.5) 5509 (22.2) 4474 (18.0)
220 220 222 223
343 (24.9) 726 (24.9) 313 (25.1) 346 (25.2)
9858 (39.9) 8482 (34.4) 4112 (16.7) 2228 (9.0)
388 324 122 45
217 (44.0) 946 (36.8) 976 (14.0) 024 (5.1)
< 0.0001
< 0.0001
< 0.0001
0.016 23 892 (96.2) 915 (3.7) 34 (0.1)
849 172 (95.8) 36 626 (4.1) 930 (0.1)
424 (3.7) 5998 (52.5) 2726 (23.8) 1348 (11.8) 934 (8.2) 6939 (27.9) 230 (0.9)
17 638 (4.3) 258 918 (63.2) 85 208 (20.8) 31 493 (7.7) 16 325 (4.0) 156 886 (17.8) 1906 (0.2)
< 0.0001
< 0.0001 < 0.0001
* Information on pre-gestational body mass index only available from 2004 to 2010. † Defined as a diagnosis of a disease of the musculoskeletal system and connective tissue within the ICD-10 classification system in the 5-year period before birth. © 2014 Informa Healthcare on license from Scandinavian Rheumatology Research Foundation
www.scandjrheumatol.dk
DOI: 10.3109/03009742.2014.902099
Letters
425 Figure 1. Number of pregnant women giving birth redeeming one or more prescriptions of non-steroidal anti-inflammatory drugs (NSAIDs) during pregnancy between 1997 and 2010. The total number of pregnant women in the period was 911 569. The y-axis represents the percentage of all pregnant women.
3.5 3.0 2.5 2.0 % 1.5
any NSAID ibuprofen diclofenac naproxen other NSAIDs
1.0
Scand J Rheumatol Downloaded from informahealthcare.com by University of Massachusetts on 04/05/15 For personal use only.
0.5 0.0 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Year
and connective tissue (ICD-10 DM group) were from the National Hospital Register (4). Differences in baseline characteristics between exposed and unexposed were calculated using a logistic regression model where maternal age, education, parity, number of offspring in the current pregnancy, smoking during pregnancy, diagnosis of a disease of the musculoskeletal system and connective tissue, and year of birth were included in the model. As information on body mass index (BMI) was only available from 2004, a separate logistic regression model was constructed further including BMI. For all analyses, a p-value of < 0.05 was considered statistically significant. The Danish Data Protection Agency approved the study (No. 2008-41-2517). We identified 911 569 pregnancies resulting in a birth between 1997 and 2010. A total of 24841 (2.7%) redeemed at least one prescription of an NSAID, mainly ibuprofen (63%), at some point during pregnancy. Women redeeming NSAID prescriptions were characterized by being younger, having a lower educational level, lower household income, more prior pregnancies, fewer multiple births, higher BMI, and smoked more during pregnancy compared to unexposed women (Table 1). It is known that, for example, low socio-economic status is associated with higher disease prevalence, which could partly explain our findings (5). Women exposed to NSAIDs were more likely to have a diagnosis of a disease of the musculoskeletal system and connective tissue (0.9%) than unexposed (0.2%), which was to be expected because NSAIDs are often used in the treatment of rheumatic diseases. The rates could be underestimated because they are solely based on hospital diagnoses. From 1997 to 2004 the overall exposure to any NSAID increased from 2.4% to 3.1% (p < 0.0001) and decreased to 2.3% in 2010 (p < 0.0001) (Figure 1). In 2004, The Danish Medicines Agency drew attention to a possible small increased risk of birth defects for NSAID during pregnancy, and the patient information leaflets were
edited (6). This awareness could explain the decrease in exposure to NSAIDs. Fewer women were exposed to an NSAID during pregnancy than before pregnancy (p < 0.0001). The exposure rates decreased throughout pregnancy (1.9% in the first, 0.6% in the second, and 0.4% in the third trimester) compared to before pregnancy (4.4%) and increased again after delivery (3.2%). This decline is probably due to guidelines warning about risk of harmful effects to the foetus, or general fear of medication during pregnancy. Exposure in early pregnancy has been associated with increased risk of miscarriage and birth defects, although the findings are conflicting (1).It is therefore recommended to use NSAID during the first and second trimesters with caution (7). Women with unrecognized pregnancies could account for some of the exposure seen during the first trimester. NSAID exposure in late pregnancy has been associated with adverse foetal effects (1) and NSAID use is contraindicated during the third trimester (7). However, 0.4% of the women in our cohort were exposed to an NSAID during the third trimester. This could indicate a need for NSAID use during the third trimester, despite contraindications, because some inflammatory conditions such as ankylosing spondylitis may, without pharmacological treatment, worsen during pregnancy (8). Furthermore, some women suffering from migraine continue to use NSAIDs during pregnancy (9). Another reason for NSAID exposure in pregnancy is lack of knowledge of potential adverse effects (10). The registers used in the present study have previously been validated and found to be accurately recorded. More than 99% of all births in Denmark have been recorded in the Medical Birth Registry (11) and the completeness of the National Prescription Register has been estimated to be 98% (12). Unfortunately, we have no information on adherence, dosage, and treatment indication, or on overthe-counter drugs.
www.scandjrheumatol.dk
426
In conclusion, we found that women redeeming at least one NSAID prescription during pregnancy differed in several characteristics compared to unexposed. Furthermore, NSAID exposure during pregnancy increased until 2004, and then decreased. Despite NSAIDs being contraindicated in the third trimester, several thousand women were exposed in this period of the pregnancy.
Scand J Rheumatol Downloaded from informahealthcare.com by University of Massachusetts on 04/05/15 For personal use only.
References 1. Bloor M, Paech M. Nonsteroidal anti-inflammatory drugs during pregnancy and the initiation of lactation. Anesth Analg 2013;116:1063–75. 2. Knudsen LB, Olsen J. The Danish Medical Birth Registry. Dan Med Bull 1998;45:320–3. 3. Kildemoes HW, Sørensen HT, Hallas J. The Danish National Prescription Registry. Scand J Public Health 2011;39:38–41. 4. Andersen TF, Madsen M, Jørgensen J, Mellemkjoer L, Olsen JH. The Danish National Hospital Register. A valuable source of data for modern health sciences. Dan Med Bull 1999;46:263–8. 5. Calixto O-J, Anaya J-M. Socioeconomic status. The relationship with health and autoimmune diseases. Autoimmun Rev. Published online: 10 January 2014. doi: 10.1016/j.autrev.2013.12.002. 6. http:\\www.irf.dk/dk/nyheder/nsaid_og_graviditet.htm.
Letters 7. http:\\www.produktresume.dk/docushare/dsweb/GetRendition/ Document-29832/html#bmk1. 8. Ostensen M, Villiger PM, Förger F. Interaction of pregnancy and autoimmune rheumatic disease. Autoimmun Rev 2012;11:A437–46. 9. Nezvalová-Henriksen K, Spigset O, Nordeng H. Maternal characteristics and migraine pharmacotherapy during pregnancy: cross-sectional analysis of data from a large cohort study. Cephalalgia 2009;29:1267–76. 10. Damase-Michel C, Christaud J, Berrebi A, Lacroix I, Montastruc J-L. What do pregnant women know about non-steroidal anti-inflammatory drugs? Pharmacoepidemiol Drug Saf 2009; 18:1034–8. 11. Kristensen J, Langhoff-Roos J, Skovgaard LT, Kristensen FB. Validation of the Danish Birth Registration. J Clin Epidemiol 1996;49:893–7. 12. Sørensen HT, Hansen I, Ejlersen E, Sabroe S, Hamburger H. Identification of patients treated with strong analgesics: an assessment of two Danish information systems with respect to epidemiological research. J Med Syst1996;20:57–65.
Vanja Cejvanovic, Laboratory of Clinical Pharmacology Q7642, Copenhagen University Hospital Rigshospitalet, Tagensvej 20, DK-2200 Copenhagen, Denmark. E-mail: [email protected] Accepted 4 March 2014
Identification of susceptibility genes for systemic lupus erythematosus with a genome-wide gene-based association study S-F Lei1,2, F-Y Deng1,2 1 Centre for Genetic Epidemiology and Genomics, and 2Department of Epidemiology, School of Public Health, Soochow University, Suzhou, Jiangsu, P. R. China
Systemic lupus erythematosus (SLE) is a chronic autoimmune disease. A number of SLE-associated loci have been identified in genome-wide association studies (GWASs) (1–8). Typically, these GWASs used a single nucleotide polymorphism (SNP) as the basic analysis unit. Because of the large number of SNPs tested in GWAS, a stringent significant threshold (typically < 5.0 108) was adopted to control for false positive associations. Consequently, a large number of SNPs with moderate effects might be missed. GATES (Gene-based Association Test using Extended Simes procedure), a rapid and powerful genebased association test (9), can rapidly combine the p-values of SNPs within a gene without relying on raw, individual phenotype and genotype data, and assess the gene-level significance of a statistical association. Based on the publicly available SNP-based p-values from the database of Genotypes and Phenotypes (dbGaP; accession numbers: phs000122 and phs000202) (2, 6), we performed an initial gene-based GWAS in 1311 SLE cases and 3340 controls and a follow-up replication
www.scandjrheumatol.dk
study in 767 SLE patients and 383 non-SLE patients. As shown in Figure 1, the degree of departure in the quantilequantile (QQ) plots is stronger for gene-based p-values than for SNP-based p-values inside the gene, which suggests that the gene-based association analysis is more powerful in detecting the association than the SNPbased analysis. In total, 24 638 genes were tested. The significance level for the Benjamini-Hochberg false discovery rate (FDR) test to control an overall error rate of 0.05 on the whole genome is 2.8 104. According to the significance level, we identified a total of 138 significant genes, with the most significant signal at human leucocyte antigen (HLA)-DQA1 (p = 2.71 1021). As expected, the majority of these associations (120 genes) were mapped to the HLA region. About 72% of the significant genes were replicated in the associations. According to the annotation of the downloaded raw SNP-based p-values, 120 SNPs were significantly associated with SLE after adapting the genome-wide p-value thresholds for significance (p < 5.0 108). These 120
