Elevated serum gamma-glutamyl transferase level as a predictor of mortality in patients with anti-MDA5 antibody-positive dermatomyositis

Elevated serum gamma-glutamyl transferase level as a predictor of mortality in patients with anti-MDA5 antibody-positive dermatomyositis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Elevated serum gamma-glutamyl transferase level as a predictor of mortality in patients with anti-MDA5 antibody-positive dermatomyositis Wenlu Hu, Panpan Zhang, Yanxia Ding, Fang Dong, Tianqi Li, Lu Yang, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4431215/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Gamma-glutamyl transferase (GGT) has been identified to correlate with systemic inflammation in autoimmune diseases, while the role of GGT in anti-melanoma differentiation-associated protein 5 antibody-positive dermatomyositis (MDA5 + DM) remains unknown. This study aimed to investigate the clinical and prognostic significance of serum GGT in MDA5 + DM patients. Methods Patients with MDA5 + DM admitted to the First Affiliated Hospital of Zhengzhou University between February 2019 and May 2023 were retrospectively analyzed. We compared the clinical features and prognosis between MDA5 + DM patients with elevated serum GGT levels and those with normal serum GGT levels. Cox regression analysis was performed to identify independent factors associated with mortality. Results A total of 299 MDA5 + DM patients were enrolled in this study. During the median follow-up time of 13.1(4.4–28.1) months, 153(51.2%) patients developed rapidly progressive interstitial lung disease (RP-ILD) and 75(25.1%) patients died within 6 months after disease onset. Serum GGT levels were significantly higher in the death group compared to the survival group [95(56–165) vs 45(26–90) U/L, p 58U/L, n = 144). Compared with the normal GGT group, patients in the elevated GGT group had increased incidences of skin ulcer and RP-ILD, higher levels of lactate dehydrogenase (LDH), Krebs Von den Lungen-6 (KL-6), ferritin and C-reactive protein (CRP), while lower levels of albumin and lymphocyte counts. Moreover, the Kaplan–Meier survival analysis demonstrated that the cumulative survival rate was significantly lower in the elevated GGT group than that in the normal GGT group (log-rank p 58U/L, LDH>345U/L, CRP>5mg/L and anti-Ro52 antibody positivity were independent risk factors of mortality in MDA5 + DM patients. Conclusions Elevated serum GGT level was an independent risk factor for mortality in MDA5 + DM patients. As a novel and readily available predictor, serum GGT level may help clinicians in guiding prognostic stratification and personalized treatment. Dermatomyositis Anti-MDA5 antibody Gamma-glutamyl transferase Mortality Figures Figure 1 Figure 2 Figure 3 Background Anti-melanoma differentiation-associated protein 5 (MDA5) antibody-positive dermatomyositis (MDA5 + DM) is a unique subtype of dermatomyositis characterized by typical skin lesions, rapidly progressive interstitial lung disease (RP-ILD) and less or absent muscle involvement[ 1 ]. Due to its high incidence of RP-ILD, patients with MDA5 + DM have a significantly higher mortality rate than other dermatomyositis subtypes[ 2 , 3 ]. In recent years, several studies have been conducted to investigate the potential risk factors of mortality in MDA5 + DM patients to guide prognostic stratification and personalized treatment. It has been identified that old age, RP-ILD, anti-Ro52 antibody positivity, lymphocytopenia and high levels of serum ferritin, C-reactive protein (CRP), Krebs von den Lungen-6 (KL-6) and lactate dehydrogenase (LDH) are predictors of poor prognosis in patients with MDA5 + DM[ 2 – 6 ]. However, previous studies about the associations between liver function indicators and prognosis in MDA5 + DM patients primarily focused on serum levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST) and albumin (ALB). While research about serum GGT levels among MDA5 + DM patients was limited. A retrospective study that enrolled 14 cases of MDA5 + DM patients showed that serum GGT levels were higher in dead patients compared with alive patients[ 7 ]. Additionally, a recent retrospective study that included 34 MDA5 + DM patients indicated that serum GGT levels in the RP-ILD group were higher than in the non-RPILD group[ 8 ]. Thus, it is necessary to further explore the clinical and prognostic significance of serum GGT in MDA5 + DM patients. Gamma-glutamyl transferase (GGT) is a key enzyme that plays a vital role in glutathione metabolism[ 9 ] and has been proven to be involved in oxidative stress and inflammation[ 10 ]. Some studies revealed that serum GGT levels positively correlate with serum CRP concentrations in patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA) and systemic lupus erythematosus (SLE)[ 10 – 14 ]. Moreover, elevated serum GGT levels may be a risk factor for SLE aggravation[ 14 ]. Therefore, serum GGT levels may reflect systemic inflammation or disease activity in autoimmune diseases. However, the role of GGT in MDA5 + DM remains unknown. Studies regarding the associations of serum GGT levels with clinical characteristics and prognosis in MDA5 + DM patients are still lacking. In this study, our first aim was to compare the clinical features and prognosis between MDA5 + DM patients with elevated serum GGT levels and those with normal serum GGT levels based on a large retrospective cohort. The secondary aim of the study was to investigate the predictive value of serum GGT level for mortality in patients with MDA5 + DM. Methods Patients This was a retrospective study conducted at the First Affiliated Hospital of Zhengzhou University. We included consecutive patients who were hospitalized and diagnosed as MDA5 + DM for the first time from February 2019 to May 2023. All the patients fulfilled the European Neuromuscular Center (ENMC) 2018 DM classification criteria[ 15 ] and were positive for anti-MDA5 antibody. Exclusion criteria for this study were (1) age of onset < 18 years old; (2) complicated with viral hepatitis, autoimmune liver disease, alcohol abuse, alcoholic steatohepatitis, drug-induced liver injury, chronic liver diseases or other diseases that might affect liver function; (3) overlapped with other connective tissue diseases; (4) suffered from lethal malignancies; (5) incomplete clinical, laboratory or follow-up data necessary for this study. This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the First Affiliated Hospital of Zhengzhou University (2021-KY-1101). Data collection We collected demographic, clinical, laboratory and imaging data at diagnosis and during follow-up from electronic medical records. The baseline was defined as the first-time diagnosis of MDA5 + DM. Demographic data included the age of disease onset, gender, disease duration and smoking status. The primary laboratory parameters contained complete blood counts and the serum levels of ALT (normal range: 0-40U/L), AST (normal range: 0-40U/L), GGT (normal range: 0-58U/L), alkaline phosphatase (ALP, normal range: 35-105U/L), total bilirubin (normal range: 0–25µmol/L), ALB (normal range: 35-55g/L), creatine kinase (CK, normal range: 26-192U/L), LDH (normal range: 26-192U/L), KL-6 (normal range:0-500U/mL), ferritin (normal range:15-150ng/mL), erythrocyte sedimentation rate (ESR, normal range: male 0-15mm/H, female 0-20mm/H) and CRP (normal range:0-5mg/L). The neutrophil-to-lymphocyte ratio (NLR) was calculated as absolute neutrophil count divided by absolute lymphocyte count. Anti‐MDA5 antibodies were measured by enzyme-linked immunosorbent assay (MBL, Japan) in all patients. In addition, the follow-up data were obtained from electronic medical records or through contacting the patients or their families by telephone. Survival status until 1 February 2024 for each patient was documented. Definitions RP-ILD was defined as either progressive dyspnea, hypoxemia, and worsening of the radiological interstitial change within 1 month, or deterioration to respiratory failure within 3 months since the onset of respiratory symptoms[ 16 , 17 ]. Elevated serum GGT level was defined as serum GGT level higher than the upper limit of the normal range (58U/L). Outcomes The primary outcomes were overall mortality and survival time after disease onset. The second outcomes included the occurrence of RP-ILD, 3-month mortality and 6-month mortality. Statistical analysis Continuous variables were presented as mean ± standard deviation (SD) or median and interquartile range (IQR) according to the distribution. Categoric variables were expressed as frequency (percentage). Categorical data were compared using the chi-square test and continuous data using the student t-test or Mann-Whitney test when appropriate. Survival analysis was performed by the Kaplan-Meier (K-M) method and tested by the log-rank test. Univariate and multivariate Cox regression analysis was performed to identify independent factors associated with death. Variables exhibiting significant differences in univariate Cox regression analysis were further included in multivariate Cox regression analysis (Forward: LR method). The prediction performance was measured by the receiver operating characteristics curve (ROC) and the area under the ROC curve (AUC). A p -value < 0.05 was considered statistically significant. Correlations were assessed by the Spearman rank test. Statistical analysis and plotting were performed using SPSS (version 26.0), GraphPad Prism (version 9.0) or R software (version 4.3.2). Results Clinical characteristics of MDA5 + DM patients A total of 299 MDA5 + DM patients were enrolled in this study. Detailed baseline characteristics of these patients were displayed in Table 1 . The median age was 52(45–59) years and 192(64.2%) patients were female. The median disease duration at diagnosis was 2.1(1.1–3.3) months and the median follow-up time was 13.1(4.4–28.1) months. Among the 299 patients, 153(51.2%) patients developed RP-ILD and 75(25.1%) patients died within 6 months. The most common cause of death was respiratory failure. Comparisons of clinical characteristics between the survival and death group According to the survival conditions at 6 months after onset, the patients were divided into the death group (n = 75) and the survival group (n = 224). The comparisons of baseline clinical characteristics between the two groups were shown in Table 1 . Patients in the death group were significantly older and had shorter disease duration than the survival group. In the death group, skin ulcer, ILD, RP-ILD and fever occurred more commonly, but myalgia, myasthenia and arthralgia occurred less frequently compared with the survival group. Furthermore, patients in the death group exhibited obviously higher levels of NLR, ALT, AST, ALP, GGT, LDH, KL-6, ferritin, ESR and CRR, while lower levels of ALB and lymphocyte counts than those in the survival group. In addition, it was noteworthy that serum GGT levels were significantly elevated in the death group compared to the survival group [95(56–165) vs 45(26–90) U/L, p <0.001]. Similarly, patients with RP-ILD had evidently higher serum GGT levels than patients without RP-ILD [75(46–140) vs 36(23–79) U/L, p <0.001]. Table 1 Baseline characteristics of MDA5 + DM patients and comparisons between the survival and death group. Variables Total (n = 299) Survival group (n = 224) Death group (n = 75) P -value Demographic characteristics Age at onset, years 52(45–59) 51(43–58) 56(51–66) <0.001 Female, n (%) 192(64.2) 148(66.1) 44(58.7) 0.247 Smoking history, n (%) 33(11.0) 19(8.5) 14(18.7) 0.015 Disease duration, months 2.1(1.1–3.3) 2.1(1.2–4.1) 1.3(0.9–2.2) <0.001 Clinical manifestations Skin ulcer, n (%) 54(18.1) 33(14.7) 21(28.0) 0.010 Heliotrope rash, n (%) 189(63.2) 147(65.6) 42(56.0) 0.135 Gottron sign, n (%) 161(53.8) 124(55.4) 37(49.3) 0.365 Mechanic’s hands, n (%) 68(22.7) 53(23.7) 15(20.0) 0.513 Myalgia, n (%) 101(33.8) 83(37.1) 18(24.0) 0.039 Myasthenia, n (%) 109(36.5) 92(41.1) 17(22.7) 0.004 ILD, n (%) 284(95.0) 210(93.8) 74(98.7) 0.167 RP-ILD, n (%) 153(51.2) 82(36.6) 71(94.7) <0.001 Fever, n (%) 156(52.2) 102(45.5) 54(72.0) <0.001 Arthralgia, n (%) 140(46.8) 117(52.2) 23(30.7) 0.001 Weight loss, n (%) 111(37.1) 78(34.8) 33(44.0) 0.154 Laboratory parameters Lymphocytes, ×10 9 /L 0.75(0.48–1.11) 0.81(0.54–1.11) 0.53(0.35–0.81) <0.001 NLR 5.1(3.1–8.9) 4.3(2.9–6.8) 8.9(4.8–16.0) <0.001 ALT, U/L 42(24–75) 40(21–67) 56(30–99) 0.002 AST, U/L 50(32–86) 45(28–82) 68(47–104) <0.001 GGT, U/L 52(28–121) 45(26–90) 95(56–165) <0.001 ALP, U/L 76(61–97) 73(60–92) 88(67–108) 0.001 Total bilirubin, µmol/L 7.2(5.4–9.6) 7.1(5.3-9.0) 7.9(5.8–11.1) 0.022 ALB, g/L 33.6 ± 5.2 34.8 ± 5.0 30.2 ± 3.9 <0.001 CK, U/L 71(37–130) 69(37–122) 74(39–157) 0.348 LDH, U/L 345(291–433) 327(274–400) 421(342–606) <0.001 KL-6, U/mL 966(663–1539) 842(615–1304) 1287(857–2052) <0.001 Serum ferritin, ng/mL 876(415–1877) 756(352–1312) 1651(734-29111) <0.001 ESR, mm/H 30(18–49) 27(16–45) 44(28–60) <0.001 CRP, mg/L 4.3(1.5–18.7) 3.1(1.5–10.5) 14.3(5.2–43.3) <0.001 ANA positive, n (%) 129(43.1) 95(42.4) 34(45.3) 0.658 Anti-Ro52 antibody positive, n (%) 174(58.2) 117(52.2) 57(76.0) <0.001 Anti-MDA5 antibody levels, U/mL 179(151–202) 175(145–201) 181(162–205) 0.079 ALB, albumin; ALP, alkaline phosphatase; ALT, alanine aminotransferase; ANA, antinuclear antibody; AST, aspartate aminotransferase; CK, creatine kinase; CRP, C-reactive protein; DM, dermatomyositis; ESR, erythrocyte sedimentation rate; GGT, gamma-glutamyl transpeptidase; ILD, interstitial lung disease; LDH, lactate dehydrogenase; MDA5, melanoma differentiation-associated gene 5; NLR, Neutrophil-to‐lymphocyte ratio; KL-6, Krebs Von den Lungen-6; RPILD, rapidly progressive interstitial lung disease. Statistically significant results ( p < 0.05) are highlighted in bold. Comparisons of clinical characteristics and survival outcomes between the normal GGT group and elevated GGT group Given that serum GGT levels were obviously higher in the death group than in the survival group. Next, based on the serum GGT levels at the time of diagnosis, we divided all the patients into two groups: normal GGT group (GGT ≤ 58U/L, n = 155) and elevated GGT group (GGT>58U/L, n = 144). Considering the convenience of clinical practice, the final cut-off value of GGT was determined by the upper limit of the normal reference range rather than the ROC curve. We further compared the clinical characteristics and outcomes between the two groups (Table 2 ). Table 2 Comparisons of clinical features and survival outcomes between normal GGT group and elevated GGT group. Variables Normal GGT group (n = 155) Elevated GGT group (n = 144) P -value Demographic characteristics Age at onset, years 51(43–59) 53(48–59) 0.178 Female, n (%) 107(69.0) 85(59.0) 0.071 Smoking history, n (%) 13(8.4) 23(13.9) 0.129 Disease duration, months 2.3(1.2–4.3) 1.5(1.0-2.3) <0.001 Clinical manifestations Skin ulcer, n (%) 21(14.2) 33(22.2) 0.035 Heliotrope rash, n (%) 98(63.2) 91(63.2) 0.996 Gottron sign, n (%) 84(54.2) 77(53.5) 0.901 Mechanic’s hands, n (%) 33(21.3) 35(24.3) 0.534 Myalgia, n (%) 57(36.8) 44(30.6) 0.256 Myasthenia, n (%) 60(38.7) 49(34.0) 0.401 ILD, n (%) 142(91.6) 142(98.6) 0.006 RP-ILD, n (%) 57(36.8) 96(66.7) <0.001 Fever, n (%) 69(44.5) 87(60.4) 0.006 Arthralgia, n (%) 81(52.3) 59(41.0) 0.051 Weight loss, n (%) 59(38.1) 52(36.1) 0.727 Laboratory parameters Lymphocytes, ×10 9 /L 0.81(0.53–1.11) 0.72(0.45–0.96) 0.047 NLR 4.00(2.92–6.55) 6.57(3.72–11.49) <0.001 ALT, U/L 30(18–44) 68(37–111) <0.001 AST, U/L 40(24–63) 68(45–110) <0.001 GGT, U/L 28(21–43) 124(79–187) <0.001 ALP, U/L 68(57–80) 92(67–113) <0.001 Total bilirubin, µmol/L 6.9(5.3–8.7) 7.9(5.5–10.8) 0.003 ALB, g/L 35.0 ± 4.9 32.2 ± 5.1 <0.001 CK, U/L 64(35–113) 79(38–152) 0.132 LDH, U/L 320(265–411) 374(306–466) <0.001 KL-6, U/mL 823(575–1237) 1159(730–1773) <0.001 Serum ferritin, ng/mL 580(225–1179) 1203(736–2281) <0.001 ESR, mm/H 27(16–44) 34(21–57) 0.021 CRP, mg/L 3.4(1.5–11.6) 6.1(1.5–28.0) 0.026 Anti-Ro52 antibody positive, n (%) 76(49.0) 98(68.1) 0.001 Survival outcomes 3-month mortality, n/N (%) 16(10.3) 35(24.3) 0.001 6-month mortality, n/N (%) 19(12.3) 56(38.9) <0.001 ALB, albumin; ALP, alkaline phosphatase; ALT, alanine aminotransferase; AST, aspartate aminotransferase; CK, creatine kinase; CRP, C-reactive protein; DM, dermatomyositis; ESR, erythrocyte sedimentation rate; GGT, gamma-glutamyl transpeptidase; ILD, interstitial lung disease; LDH, lactate dehydrogenase; MDA5, melanoma differentiation-associated gene 5; NLR, Neutrophil-to‐lymphocyte ratio; KL-6, Krebs Von den Lungen-6; RPILD, rapidly progressive interstitial lung disease. Statistically significant results ( p < 0.05) are highlighted in bold. Compared with the normal GGT group, the incidence rate of skin ulcer, RP-ILD and fever was higher in the elevated GGT group. Moreover, patients with elevated GGT levels had significantly increased levels of ALT, AST, ALP, LDH, ferritin, KL-6, ESR and CRP, but obviously decreased levels of ALB and lymphocyte counts than the normal GGT group (Fig. 1 A-E). In terms of survival outcomes, the 3-month and 6-month mortality were both evidently higher in the elevated GGT group than that in the normal GGT group (24.3% vs 10.3%, p = 0.001; 38.9% vs 12.3, p<0.001) (Fig. 1 F). Likewise, the Kaplan–Meier survival analysis demonstrated that the cumulative survival rate was significantly lower in the elevated GGT group than that in the normal GGT group (log-rank p < 0.001, Fig. 2 ). Factors associated with mortality in MDA5 + DM patients Cox regression analysis was conducted to explore the factors associated with death in MDA5 + DM patients. The optimal cut-off values of age, disease duration, lymphocyte count, ALT, AST, ALP, ALB, LDH, CRP, KL-6 and ferritin were determined based on the maximum Youden index. Univariable Cox regression analysis showed that age at onset > 51 years, disease duration ≤ 3 months, smoking history, skin ulcer, fever, RP-ILD, lymphocyte count ≤ 0.6×109/L, ALT > 45U/L, AST > 47U/L, GGT > 58U/L, ALP > 75U/L, Total bilirubin > 10µmol/L, ALB ≤ 33g/L, LDH > 345U/L, CRP > 5mg/L, KL-6 > 808U/mL, ferritin > 1484ng/mL and anti-Ro52 antibody positivity were risk factors associated with death for MDA5 + DM patients, while myalgia, myasthenia and arthralgia were protective factors of death. Further multivariate Cox regression analysis revealed that RP-ILD (HR 9.260, 95%CI 3.287–26.092), GGT>58U/L (HR 1.885, 95%CI 1.047–3.394), LDH>345U/L (HR 2.252, 95%CI 1.221–4.154), CRP>5mg/L (HR 2.985, 95%CI 1.582–5.632) and anti-Ro52 antibody positivity (HR 1.983, 95%CI 1.018–3.863) were independent risk factors of mortality (Table 3 ). Therefore, elevated serum GGT level, defined as serum GGT level>58U/L, was an independent risk factor for mortality in MDA5 + DM patients. Table 3 Variables associated with death in MDA5 + DM patients from univariable and multivariate Cox regression analysis. Univariate Multivariate HR (95%CI) P -value HR (95%CI) P -value Age at onset > 51 years 2.741(1.682–4.465) < 0.001 Disease duration ≤ 3 months 2.925(1.646–5.197) < 0.001 Smoking history 1.964(1.105–3.491) 0.022 Skin ulcer 2.282(1.426–3.651) 0.001 Myalgia 0.593(0.361–0.972) 0.038 Myasthenia 0.514(0.313–0.843) 0.008 Arthralgia 0.494(0.313–0.778) 0.002 Fever 2.153(1.359–3.409) 0.001 RP-ILD 20.331(8.222–50.274) < 0.001 9.260(3.287–26.092) <0.001 Lymphocyte ≤ 0.6×10 9 /L 2.928(1.890–4.538) 45U/L 2.024(1.304–3.144) 0.002 AST > 47U/L 3.279(1.981–5.425) 58U/L 3.334(2.060–5.397) 75U/L 2.510(1.561–4.037) < 0.001 ALB ≤ 33g/L 5.315(3.116–9.065) 10µmol/L 2.204(1.402–3.465) 0.001 LDH > 345U/L 3.966(2.393–6.570) 5mg/L 4.656(2.747–7.892) 808U/mL 2.378(1.359–4.161) 0.002 Serum ferritin > 1484ng/mL 3.302(2.026–5.382) < 0.001 Anti-Ro52 antibody positivity 2.727(1.634–4.553) < 0.001 1.983(1.018–3.863) 0.044 ALB, albumin; ALP, alkaline phosphatase; ALT, alanine aminotransferase; AST, aspartate aminotransferase; CI, confidence interval; CRP, C-reactive protein; DM, dermatomyositis; GGT, gamma-glutamyl transpeptidase; HR, hazard ratio; LDH, lactate dehydrogenase; MDA5, melanoma differentiation-associated gene 5; KL-6, Krebs Von den Lungen-6; RPILD, rapidly progressive interstitial lung disease. Predictive value of serum GGT level for mortality Previous studies suggested that some laboratory parameters including lymphocyte counts and serum LDH, CRP, and ferritin levels could predict mortality in MDA5 + DM patients. We further compared the predictive value of serum GGT level for mortality with the above prognostic biomarkers. ROC curves indicated that the AUC of CRP, LDH, GGT, lymphocyte counts and ferritin levels for predicting 6-month mortality were 0.725(95%CI 0.653–0.796), 0.719(95%CI 0.650–0.788), 0.711(95%CI 0.647–0.774), 0.680(95%CI 0.610–0.751) and 0.676(95%CI 0.594–0.757) respectively (Fig. 3 ). These results indicated that serum GGT level exhibited a comparable predictive value for mortality in MDA5 + DM patients. In addition, Spearman correlation analysis was employed to determine the correlations between serum GGT levels and these prognostic biomarkers. Serum GGT levels showed positive correlations with serum ferritin, LDH and KL-6 levels ( r = 0.475, p <0.001; r = 0.311, p <0.001; r = 0.295, p <0.001 respectively), while negatively associated with ALB concentrations ( r =-0.368, p <0.001). Discussion In this large retrospective cohort study, 48.2% of MDA5 + DM patients presented with elevated levels of serum GGT. Compared with the normal GGT group, patients in the elevated GGT group had an increased incidence of skin ulcer and RP-ILD, higher levels of CRP, LDH, ferritin and KL-6, while lower lymphocyte counts. Moreover, patients with elevated serum GGT levels had significantly higher 3-month and 6-month mortality. To the best of our knowledge, this is the first study to identify that elevated serum GGT level is a reliable and readily available predictor for mortality in patients with MDA5 + DM. Several studies have been dedicated to exploring the predictors of mortality in MDA5 + DM patients. It has been demonstrated that old age, RP-ILD, anti-Ro52 antibody positivity, lymphocytopenia and high levels of ferritin, CRP, LDH and KL-6 are risk factors for mortality in patients with MDA5 + DM[ 1 – 4 , 18 ]. Consistent with previous studies, our study indicated that RP-ILD, anti-Ro52 antibody positivity, elevated serum LDH and CRP levels were independent risk factors of mortality in MDA5 + DM patients. In addition to the above well-known predictors, we first revealed that elevated serum GGT level is a novel risk factor that has not been reported previously. At present, studies regarding the relationships between serum GGT levels and prognosis in MDA5 + DM patients are limited. A small sample-sized retrospective study indicated that serum GGT levels were obviously higher in dead patients compared with alive patients[ 7 ]. In line with this study, we found that patients with elevated serum GGT levels had a significantly higher incidence of RP-ILD and short-term mortality. Furthermore, patients in the elevated GGT group presented with evidently higher levels of LDH, KL-6, ferritin, CRP, anti-Ro52 antibody positivity and lower lymphocyte counts. All the laboratory parameters mentioned above were associated with poor prognosis in MDA5 + DM patients. GGT in the serum mainly originates from the liver. Serum GGT as a common indicator of liver function is easily accessible in routine clinical practice. In our study, compared with other previously known laboratory predictors, serum GGT shows comparable and satisfactory prediction performance. Therefore, serum GGT level is a reliable and readily available predictor for mortality in MDA5 + DM patients. This study provides clinicians with a novel and easily available prognostic biomarker, which is helpful for better prognosis evaluation and risk stratification. In recent years, accumulated evidences have demonstrated that serum elevated GGT level is associated with cardiovascular diseases, metabolic syndrome, diabetes mellitus, cancer, chronic kidney disease, fractures, cardiovascular mortality and all-cause mortality[ 9 , 19 – 24 ]. GGT as a key transferase enzyme plays a vital role in the resynthesis of glutathione (GSH), which is an important intracellular antioxidant protecting cells against oxidative damage [ 22 , 25 ]. GGT levels may elevate in order to produce more GSH in response to oxidative stress[ 26 ]. Therefore, GGT has become a well-established biomarker of oxidative stress[ 9 , 25 ]. However, studies regarding the link between oxidative stress and MDA5 + DM are still limited. A recent study suggested oxidative stress may exist in MDA5 + DM[ 27 ]. Our study provides more evidence that oxidative stress may be involved in the development of MDA5 + DM. Further studies are still needed to confirm the role of oxidative stress in the pathogenesis of MDA5 + DM. In addition, oxidative stress and inflammation are closely related and tightly linked pathophysiological processes[ 28 ]. Serum GGT level is also considered as a biomarker of systemic inflammation[ 14 ]. Previous studies have reported that serum GGT levels positively correlate with serum CRP concentration in patients with RA, PsA and SLE[ 10 – 14 ]. Moreover, elevated serum GGT level may indicate an increased risk of SLE aggravation[ 14 ]. Similarly, our present study found that serum GGT level is positively correlated with CRP level and disease severity in patients with MDA5 + DM. Therefore, serum GGT may become a promising biomarker of systemic inflammation and oxidative stress among MDA5 + DM patients. Furthermore, several studies have confirmed that macrophage activation may play a vital role in the pathogenesis of MDA5 + DM[ 1 , 7 ]. Thus, we speculate that excessive activation of hepatic macrophages may cause hepatic injury including elevated serum GGT levels[ 29 ]. Moreover, our study identified that serum GGT levels correlated positively with serum concentrations of ferritin, which is a well-known biomarker of macrophage activation[ 7 ]. Therefore, GGT may also serve as a biomarker of macrophage activation in MDA5 + DM patients. Our study has some limitations. First, this was a single-center retrospective study, which inevitably had a risk of selection bias. Second, although we had tried to exclude the possible factors influencing serum GGT levels, the effects of drugs on liver enzymes could not be ruled out completely owing to some patients might have received non-steroidal anti-inflammatory drugs to relieve the symptoms of fever or arthralgia before MDA5 + DM was diagnosed. Further multi-center prospective studies are still required to validate our findings. Conclusions In conclusion, this study revealed that MDA5 + DM patients with elevated serum GGT levels had a higher short-term mortality rate. Elevated serum GGT level was an independent risk factor for mortality in MDA5 + DM patients. As a novel and readily available predictor, serum GGT level may help clinicians in identifying MDA5 + DM patients at high risk of death. List Of Abbreviations ALB Albumin ALP Alkaline phosphatase ALT Alanine aminotransferase ANA Antinuclear antibody AST Aspartate aminotransferase CI Confidence interval CK Creatine kinase CRP C-reactive protein DM Dermatomyositis ESR Erythrocyte sedimentation rate GGT Gamma-glutamyl transpeptidase HR Hazard ratio ILD Interstitial lung disease LDH Lactate dehydrogenase MDA5 Melanoma differentiation-associated gene 5 NLR Neutrophil-to‐lymphocyte ratio KL-6 ROC Krebs Von den Lungen-6 Receiver operation characteristic RP-ILD Rapidly progressive interstitial lung disease Declarations Ethics approval and consent to participate This study was approved by the Ethical Committee of the First Affiliated Hospital of Zhengzhou University (approval number: 2021-KY-1101). Written informed consents were waived because of the retrospective nature of the study. Consent for publication Not applicable Availability of data and materials Data sets generated during the current study are available from the corresponding author on reasonable request, but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Competing interests The authors declare that they have no competing interests. Funding This study was supported by the National Natural Science Foundation of China (No. 82302051, No. 82371819) and a Joint project of Medical Science and Technology Key Program of Henan Province (LHGJ20210278, LHGJ20230175). Authors' contributions YZ, SL, TL and WH designed this study. Material preparation, data collection and analysis were performed by WH, YZ, PZ, FD, YD, TL, LY, LL and LZ. WH drafted the manuscript. PZ and YZ revised the manuscript. All authors read and approved the final manuscript. Acknowledgements Not applicable. References Lu X, Peng Q, Wang G. Anti-MDA5 antibody-positive dermatomyositis: pathogenesis and clinical progress. Nat Rev Rheumatol. 2024;20(1):48–62. Xie H, Zhang D, Wang Y, Shi Y, Yuan Y, Wang L, et al. Risk factors for mortality in patients with anti-MDA5 antibody-positive dermatomyositis: A meta-analysis and systematic review. Semin Arthritis Rheum. 2023;62:152231. You H, Wang L, Wang J, Lv C, Xu L, Yuan F, et al. Time-dependent changes in RPILD and mortality risk in anti-MDA5 + DM patients: a cohort study of 272 cases in China. Rheumatology (Oxford). 2023;62(3):1216–26. Gono T, Masui K, Nishina N, Kawaguchi Y, Kawakami A, Ikeda K et al. Risk Prediction Modeling Based on a Combination of Initial Serum Biomarker Levels in Polymyositis/Dermatomyositis-Associated Interstitial Lung Disease. Arthritis & rheumatology (Hoboken, NJ). 2021;73(4):677–86. Wu W, Xu W, Sun W, Zhang D, Zhao J, Luo Q, et al. Forced vital capacity predicts the survival of interstitial lung disease in anti-MDA5 positive dermatomyositis: a multi-centre cohort study. Rheumatology (Oxford). 2021;61(1):230–9. Wang H, Chen X, Du Y, Wang L, Wang Q, Wu H, et al. Mortality risk in patients with anti-MDA5 dermatomyositis is related to rapidly progressive interstitial lung disease and anti-Ro52 antibody. Arthritis Res therapy. 2023;25(1):127. Gono T, Kawaguchi Y, Satoh T, Kuwana M, Katsumata Y, Takagi K, et al. Clinical manifestation and prognostic factor in anti-melanoma differentiation-associated gene 5 antibody-associated interstitial lung disease as a complication of dermatomyositis. Rheumatology (Oxford). 2010;49(9):1713–9. Lian L, Tong JJ, Xu SQ. Clinical features and prognostic factors of anti-melanoma differentiation-associated gene 5 antibody-positive dermatomyositis with rapidly progressive interstitial lung disease in Chinese patients. Immun Inflamm Dis. 2023;11(6):e882. Brennan PN, Dillon JF, Tapper EB. Gamma-Glutamyl Transferase (γ-GT) - an old dog with new tricks? Liver Int. 2022;42(1):9–15. Wang X, Mao Y, Ji S, Hu H, Li Q, Liu L, et al. Gamma-glutamyl transpeptidase and indirect bilirubin may participate in systemic inflammation of patients with psoriatic arthritis. Adv Rheumatol. 2023;63(1):53. Lee DH, Jacobs DR Jr. Association between serum gamma-glutamyltransferase and C-reactive protein. Atherosclerosis. 2005;178(2):327–30. Lowe JR, Pickup ME, Dixon JS, Leatham PA, Rhind VM, Wright V, et al. Gamma glutamyl transpeptidase levels in arthritis: a correlation with clinical and laboratory indices of disease activity. Ann Rheum Dis. 1978;37(5):428–31. Vergneault H, Vandebeuque E, Codullo V, Allanore Y, Avouac J. Disease Activity Score in 28 Joints Using GGT Permits a Dual Evaluation of Joint Activity and Cardiovascular Risk. J Rhuematol. 2020;47(12):1738–45. Zhang W, Tang Z, Shi Y, Ji L, Chen X, Chen Y, et al. Association Between Gamma-Glutamyl Transferase, Total Bilirubin and Systemic Lupus Erythematosus in Chinese Women. Front Immunol. 2021;12:682400. Mammen AL, Allenbach Y, Stenzel W, Benveniste O. 239th ENMC International Workshop: Classification of dermatomyositis, Amsterdam, the Netherlands, 14–16 December 2018. Neuromuscular disorders: NMD. 2020;30(1):70–92. Sato S, Hirakata M, Kuwana M, Suwa A, Inada S, Mimori T, et al. Autoantibodies to a 140-kd polypeptide, CADM-140, in Japanese patients with clinically amyopathic dermatomyositis. Arthritis Rheum. 2005;52(5):1571–6. Moghadam-Kia S, Oddis CV, Sato S, Kuwana M, Aggarwal R. Anti-Melanoma Differentiation-Associated Gene 5 Is Associated With Rapidly Progressive Lung Disease and Poor Survival in US Patients With Amyopathic and Myopathic Dermatomyositis. Arthritis Care Res. 2016;68(5):689–94. Jin Q, Fu L, Yang H, Chen X, Lin S, Huang Z, et al. Peripheral lymphocyte count defines the clinical phenotypes and prognosis in patients with anti-MDA5-positive dermatomyositis. J Intern Med. 2023;293(4):494–507. Kunutsor SK. Gamma-glutamyltransferase-friend or foe within? Liver Int. 2016;36(12):1723–34. Yi SW, Lee SH, Hwang HJ, Yi JJ. Gamma-glutamyltransferase and cardiovascular mortality in Korean adults: A cohort study. Atherosclerosis. 2017;265:102–9. Lai SW. Gamma-glutamyl-transferase and hip fracture. Osteoporos Int. 2022;33(8):1825–6. Yoon HE, Mo EY, Shin SJ, Moon SD, Han JH, Kim ES. Serum gamma-glutamyltransferase is not associated with subclinical atherosclerosis in patients with type 2 diabetes. Cardiovasc Diabetol. 2016;15(1):108. Long Y, Zeng F, Shi J, Tian H, Chen T. Gamma-glutamyltransferase predicts increased risk of mortality: a systematic review and meta-analysis of prospective observational studies. Free Radic Res. 2014;48(6):716–28. Kazemi-Shirazi L, Endler G, Winkler S, Schickbauer T, Wagner O, Marsik C. Gamma glutamyltransferase and long-term survival: is it just the liver? Clin Chem. 2007;53(5):940–6. Whitfield JB. Gamma glutamyl transferase. Crit Rev Clin Lab Sci. 2001;38(4):263–355. Sridhar SB, Xu F, Darbinian J, Quesenberry CP, Ferrara A, Hedderson MM. Pregravid liver enzyme levels and risk of gestational diabetes mellitus during a subsequent pregnancy. Diabetes Care. 2014;37(7):1878–84. Huang W, Chen D, Wang Z, Ren F, Luo L, Zhou J, et al. Evaluating the value of superoxide dismutase in anti-MDA5-positive dermatomyositis associated with interstitial lung disease. Rheumatology (Oxford). 2023;62(3):1197–203. Biswas SK. Does the Interdependence between Oxidative Stress and Inflammation Explain the Antioxidant Paradox? Oxid Med Cell Longev. 2016;2016:5698931. Nagashima T, Kamata Y, Iwamoto M, Okazaki H, Fukushima N, Minota S. Liver dysfunction in anti-melanoma differentiation-associated gene 5 antibody-positive patients with dermatomyositis. Rheumatol Int. 2019;39(5):901–9. 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Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwklEQVRIiWNgGAWjYDACCSDmAWJ+ZubDD0jTItnOlmZAmhaD8zwKEkTpkJ/dfOzBm4q6xM2HeRgMGGpsoglqYZxzLN1wzhm2xG2HeQ88YDiWlttASAuzRI6ZNG8bD1ALX4IBY8NhwlrYJPK/SfP+k0jc3MxjIEGUFh6JHDZp3gaDxA3MxGqRkEgzk5xzLMF4xmFgICcQ4xf5GcnPJN7U1Mn29x8+/OBDjQ1hLTDgCFaZQKxyELAnRfEoGAWjYBSMMAAAtT06enc6GkgAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0001-5977-4842","institution":"The First Affiliated Hospital of Zhengzhou University","correspondingAuthor":true,"prefix":"","firstName":"Yusheng","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2024-05-16 12:59:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4431215/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4431215/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":60619437,"identity":"e31f64a0-3aa4-4d48-bb10-36d6149fd292","added_by":"auto","created_at":"2024-07-18 20:45:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":271550,"visible":true,"origin":"","legend":"\u003cp\u003eComparisons of laboratory parameters and mortality between the normal GGT group and elevated GGT group.Patients with elevated GGT levels had lower lymphocyte count (A), higher serum concentrations of CRP, LDH, ferritin and KL-6 (B-E) and significantly increased 6-month mortality (F).\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-4431215/v1/078c92f26365c70e28b2594e.png"},{"id":60619436,"identity":"1911793b-c6a6-4cf7-954b-eaa9be96c3a9","added_by":"auto","created_at":"2024-07-18 20:45:08","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":59338,"visible":true,"origin":"","legend":"\u003cp\u003eSurvival curves of MDA5+DM patients in normal GGT group and elevated GGT group. The \u003cem\u003eP\u003c/em\u003e-value was calculated using the log-rank test.\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-4431215/v1/36142bd7c87f46c986e7d68a.png"},{"id":60619438,"identity":"bd7c69ca-65f6-4e16-8693-54c143f879ca","added_by":"auto","created_at":"2024-07-18 20:45:09","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":151200,"visible":true,"origin":"","legend":"\u003cp\u003eROC curves of serum GGT levels and other prognostic biomarkers formortality in MDA5+DM patients.\u003c/p\u003e","description":"","filename":"Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-4431215/v1/d966f319eaa3ec53b1b6feea.png"},{"id":62460353,"identity":"1c7bc7ad-e8fd-4c97-8fcc-2ef357cbdf80","added_by":"auto","created_at":"2024-08-14 12:24:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1296711,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4431215/v1/53c834ae-ddbf-49f1-89a5-ce675b2f0664.pdf"}],"financialInterests":"","formattedTitle":"Elevated serum gamma-glutamyl transferase level as a predictor of mortality in patients with anti-MDA5 antibody-positive dermatomyositis","fulltext":[{"header":"Background","content":"\u003cp\u003eAnti-melanoma differentiation-associated protein 5 (MDA5) antibody-positive dermatomyositis (MDA5\u0026thinsp;+\u0026thinsp;DM) is a unique subtype of dermatomyositis characterized by typical skin lesions, rapidly progressive interstitial lung disease (RP-ILD) and less or absent muscle involvement[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Due to its high incidence of RP-ILD, patients with MDA5\u0026thinsp;+\u0026thinsp;DM have a significantly higher mortality rate than other dermatomyositis subtypes[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn recent years, several studies have been conducted to investigate the potential risk factors of mortality in MDA5\u0026thinsp;+\u0026thinsp;DM patients to guide prognostic stratification and personalized treatment. It has been identified that old age, RP-ILD, anti-Ro52 antibody positivity, lymphocytopenia and high levels of serum ferritin, C-reactive protein (CRP), Krebs von den Lungen-6 (KL-6) and lactate dehydrogenase (LDH) are predictors of poor prognosis in patients with MDA5\u0026thinsp;+\u0026thinsp;DM[\u003cspan additionalcitationids=\"CR3 CR4 CR5\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, previous studies about the associations between liver function indicators and prognosis in MDA5\u0026thinsp;+\u0026thinsp;DM patients primarily focused on serum levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST) and albumin (ALB). While research about serum GGT levels among MDA5\u0026thinsp;+\u0026thinsp;DM patients was limited. A retrospective study that enrolled 14 cases of MDA5\u0026thinsp;+\u0026thinsp;DM patients showed that serum GGT levels were higher in dead patients compared with alive patients[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Additionally, a recent retrospective study that included 34 MDA5\u0026thinsp;+\u0026thinsp;DM patients indicated that serum GGT levels in the RP-ILD group were higher than in the non-RPILD group[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Thus, it is necessary to further explore the clinical and prognostic significance of serum GGT in MDA5\u0026thinsp;+\u0026thinsp;DM patients.\u003c/p\u003e \u003cp\u003eGamma-glutamyl transferase (GGT) is a key enzyme that plays a vital role in glutathione metabolism[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] and has been proven to be involved in oxidative stress and inflammation[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Some studies revealed that serum GGT levels positively correlate with serum CRP concentrations in patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA) and systemic lupus erythematosus (SLE)[\u003cspan additionalcitationids=\"CR11 CR12 CR13\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Moreover, elevated serum GGT levels may be a risk factor for SLE aggravation[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Therefore, serum GGT levels may reflect systemic inflammation or disease activity in autoimmune diseases. However, the role of GGT in MDA5\u0026thinsp;+\u0026thinsp;DM remains unknown. Studies regarding the associations of serum GGT levels with clinical characteristics and prognosis in MDA5\u0026thinsp;+\u0026thinsp;DM patients are still lacking.\u003c/p\u003e \u003cp\u003eIn this study, our first aim was to compare the clinical features and prognosis between MDA5\u0026thinsp;+\u0026thinsp;DM patients with elevated serum GGT levels and those with normal serum GGT levels based on a large retrospective cohort. The secondary aim of the study was to investigate the predictive value of serum GGT level for mortality in patients with MDA5\u0026thinsp;+\u0026thinsp;DM.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003eThis was a retrospective study conducted at the First Affiliated Hospital of Zhengzhou University. We included consecutive patients who were hospitalized and diagnosed as MDA5\u0026thinsp;+\u0026thinsp;DM for the first time from February 2019 to May 2023. All the patients fulfilled the European Neuromuscular Center (ENMC) 2018 DM classification criteria[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] and were positive for anti-MDA5 antibody. Exclusion criteria for this study were (1) age of onset\u0026thinsp;\u0026lt;\u0026thinsp;18 years old; (2) complicated with viral hepatitis, autoimmune liver disease, alcohol abuse, alcoholic steatohepatitis, drug-induced liver injury, chronic liver diseases or other diseases that might affect liver function; (3) overlapped with other connective tissue diseases; (4) suffered from lethal malignancies; (5) incomplete clinical, laboratory or follow-up data necessary for this study. This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the First Affiliated Hospital of Zhengzhou University (2021-KY-1101).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData collection\u003c/h2\u003e \u003cp\u003eWe collected demographic, clinical, laboratory and imaging data at diagnosis and during follow-up from electronic medical records. The baseline was defined as the first-time diagnosis of MDA5\u0026thinsp;+\u0026thinsp;DM. Demographic data included the age of disease onset, gender, disease duration and smoking status. The primary laboratory parameters contained complete blood counts and the serum levels of ALT (normal range: 0-40U/L), AST (normal range: 0-40U/L), GGT (normal range: 0-58U/L), alkaline phosphatase (ALP, normal range: 35-105U/L), total bilirubin (normal range: 0\u0026ndash;25\u0026micro;mol/L), ALB (normal range: 35-55g/L), creatine kinase (CK, normal range: 26-192U/L), LDH (normal range: 26-192U/L), KL-6 (normal range:0-500U/mL), ferritin (normal range:15-150ng/mL), erythrocyte sedimentation rate (ESR, normal range: male 0-15mm/H, female 0-20mm/H) and CRP (normal range:0-5mg/L). The neutrophil-to-lymphocyte ratio (NLR) was calculated as absolute neutrophil count divided by absolute lymphocyte count. Anti‐MDA5 antibodies were measured by enzyme-linked immunosorbent assay (MBL, Japan) in all patients.\u003c/p\u003e \u003cp\u003eIn addition, the follow-up data were obtained from electronic medical records or through contacting the patients or their families by telephone. Survival status until 1 February 2024 for each patient was documented.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eDefinitions\u003c/h2\u003e \u003cp\u003eRP-ILD was defined as either progressive dyspnea, hypoxemia, and worsening of the radiological interstitial change within 1 month, or deterioration to respiratory failure within 3 months since the onset of respiratory symptoms[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Elevated serum GGT level was defined as serum GGT level higher than the upper limit of the normal range (58U/L).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eOutcomes\u003c/h2\u003e \u003cp\u003eThe primary outcomes were overall mortality and survival time after disease onset. The second outcomes included the occurrence of RP-ILD, 3-month mortality and 6-month mortality.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) or median and interquartile range (IQR) according to the distribution. Categoric variables were expressed as frequency (percentage). Categorical data were compared using the chi-square test and continuous data using the student t-test or Mann-Whitney test when appropriate. Survival analysis was performed by the Kaplan-Meier (K-M) method and tested by the log-rank test. Univariate and multivariate Cox regression analysis was performed to identify independent factors associated with death. Variables exhibiting significant differences in univariate Cox regression analysis were further included in multivariate Cox regression analysis (Forward: LR method). The prediction performance was measured by the receiver operating characteristics curve (ROC) and the area under the ROC curve (AUC). A \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. Correlations were assessed by the Spearman rank test. Statistical analysis and plotting were performed using SPSS (version 26.0), GraphPad Prism (version 9.0) or R software (version 4.3.2).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eClinical characteristics of MDA5\u0026thinsp;+\u0026thinsp;DM patients\u003c/h2\u003e \u003cp\u003eA total of 299 MDA5\u0026thinsp;+\u0026thinsp;DM patients were enrolled in this study. Detailed baseline characteristics of these patients were displayed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The median age was 52(45\u0026ndash;59) years and 192(64.2%) patients were female. The median disease duration at diagnosis was 2.1(1.1\u0026ndash;3.3) months and the median follow-up time was 13.1(4.4\u0026ndash;28.1) months. Among the 299 patients, 153(51.2%) patients developed RP-ILD and 75(25.1%) patients died within 6 months. The most common cause of death was respiratory failure.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eComparisons of clinical characteristics between the survival and death group\u003c/h2\u003e \u003cp\u003eAccording to the survival conditions at 6 months after onset, the patients were divided into the death group (n\u0026thinsp;=\u0026thinsp;75) and the survival group (n\u0026thinsp;=\u0026thinsp;224). The comparisons of baseline clinical characteristics between the two groups were shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Patients in the death group were significantly older and had shorter disease duration than the survival group. In the death group, skin ulcer, ILD, RP-ILD and fever occurred more commonly, but myalgia, myasthenia and arthralgia occurred less frequently compared with the survival group. Furthermore, patients in the death group exhibited obviously higher levels of NLR, ALT, AST, ALP, GGT, LDH, KL-6, ferritin, ESR and CRR, while lower levels of ALB and lymphocyte counts than those in the survival group. In addition, it was noteworthy that serum GGT levels were significantly elevated in the death group compared to the survival group [95(56\u0026ndash;165) vs 45(26\u0026ndash;90) U/L, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001]. Similarly, patients with RP-ILD had evidently higher serum GGT levels than patients without RP-ILD [75(46\u0026ndash;140) vs 36(23\u0026ndash;79) U/L, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of MDA5\u0026thinsp;+\u0026thinsp;DM patients and comparisons between the survival and death group.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;299)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSurvival group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;224)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDeath group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;75)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDemographic characteristics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at onset, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52(45\u0026ndash;59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51(43\u0026ndash;58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56(51\u0026ndash;66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e192(64.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e148(66.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44(58.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.247\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking history, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33(11.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19(8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14(18.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.015\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease duration, months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.1(1.1\u0026ndash;3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.1(1.2\u0026ndash;4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.3(0.9\u0026ndash;2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical manifestations\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSkin ulcer, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54(18.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33(14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21(28.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.010\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeliotrope rash, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e189(63.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e147(65.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42(56.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGottron sign, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e161(53.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e124(55.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37(49.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.365\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMechanic\u0026rsquo;s hands, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68(22.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53(23.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15(20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.513\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyalgia, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e101(33.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83(37.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18(24.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.039\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyasthenia, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e109(36.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92(41.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17(22.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eILD, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e284(95.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e210(93.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74(98.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.167\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRP-ILD, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e153(51.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82(36.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71(94.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFever, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e156(52.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e102(45.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54(72.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArthralgia, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e140(46.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e117(52.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23(30.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight loss, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e111(37.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78(34.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33(44.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.154\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLaboratory parameters\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocytes, \u0026times;10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.75(0.48\u0026ndash;1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.81(0.54\u0026ndash;1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.53(0.35\u0026ndash;0.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.1(3.1\u0026ndash;8.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.3(2.9\u0026ndash;6.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.9(4.8\u0026ndash;16.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT, U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42(24\u0026ndash;75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40(21\u0026ndash;67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56(30\u0026ndash;99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST, U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50(32\u0026ndash;86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45(28\u0026ndash;82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68(47\u0026ndash;104)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGGT, U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52(28\u0026ndash;121)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45(26\u0026ndash;90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95(56\u0026ndash;165)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALP, U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76(61\u0026ndash;97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73(60\u0026ndash;92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88(67\u0026ndash;108)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal bilirubin, \u0026micro;mol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.2(5.4\u0026ndash;9.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.1(5.3-9.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.9(5.8\u0026ndash;11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.022\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALB, g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.6\u0026thinsp;\u0026plusmn;\u0026thinsp;5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCK, U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71(37\u0026ndash;130)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69(37\u0026ndash;122)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74(39\u0026ndash;157)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.348\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDH, U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e345(291\u0026ndash;433)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e327(274\u0026ndash;400)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e421(342\u0026ndash;606)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKL-6, U/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e966(663\u0026ndash;1539)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e842(615\u0026ndash;1304)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1287(857\u0026ndash;2052)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum ferritin, ng/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e876(415\u0026ndash;1877)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e756(352\u0026ndash;1312)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1651(734-29111)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eESR, mm/H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30(18\u0026ndash;49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27(16\u0026ndash;45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44(28\u0026ndash;60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP, mg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.3(1.5\u0026ndash;18.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.1(1.5\u0026ndash;10.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.3(5.2\u0026ndash;43.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eANA positive, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e129(43.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95(42.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34(45.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.658\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnti-Ro52 antibody positive, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e174(58.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e117(52.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57(76.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnti-MDA5 antibody levels, U/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e179(151\u0026ndash;202)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e175(145\u0026ndash;201)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e181(162\u0026ndash;205)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eALB, albumin; ALP, alkaline phosphatase; ALT, alanine aminotransferase; ANA, antinuclear antibody; AST, aspartate aminotransferase; CK, creatine kinase; CRP, C-reactive protein; DM, dermatomyositis; ESR, erythrocyte sedimentation rate; GGT, gamma-glutamyl transpeptidase; ILD, interstitial lung disease; LDH, lactate dehydrogenase; MDA5, melanoma differentiation-associated gene 5; NLR, Neutrophil-to‐lymphocyte ratio; KL-6, Krebs Von den Lungen-6; RPILD, rapidly progressive interstitial lung disease.\u003c/p\u003e \u003cp\u003eStatistically significant results (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) are highlighted in bold.\u003c/p\u003e \u003cp\u003e \u003cb\u003eComparisons of clinical characteristics and survival outcomes between the normal GGT group and elevated GGT group\u003c/b\u003e \u003c/p\u003e \u003cp\u003eGiven that serum GGT levels were obviously higher in the death group than in the survival group. Next, based on the serum GGT levels at the time of diagnosis, we divided all the patients into two groups: normal GGT group (GGT\u0026thinsp;\u0026le;\u0026thinsp;58U/L, n\u0026thinsp;=\u0026thinsp;155) and elevated GGT group (GGT\u0026gt;58U/L, n\u0026thinsp;=\u0026thinsp;144). Considering the convenience of clinical practice, the final cut-off value of GGT was determined by the upper limit of the normal reference range rather than the ROC curve. We further compared the clinical characteristics and outcomes between the two groups (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparisons of clinical features and survival outcomes between normal GGT group and elevated GGT group.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal GGT group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;155)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eElevated GGT group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;144)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDemographic characteristics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at onset, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51(43\u0026ndash;59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53(48\u0026ndash;59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.178\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e107(69.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85(59.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking history, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13(8.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23(13.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.129\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease duration, months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.3(1.2\u0026ndash;4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5(1.0-2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical manifestations\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSkin ulcer, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21(14.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33(22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.035\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeliotrope rash, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98(63.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91(63.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGottron sign, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84(54.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77(53.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.901\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMechanic\u0026rsquo;s hands, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33(21.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35(24.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.534\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyalgia, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57(36.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44(30.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.256\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyasthenia, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60(38.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49(34.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.401\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eILD, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e142(91.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e142(98.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRP-ILD, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57(36.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96(66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFever, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69(44.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87(60.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArthralgia, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81(52.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59(41.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight loss, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59(38.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52(36.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.727\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLaboratory parameters\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocytes, \u0026times;10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.81(0.53\u0026ndash;1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.72(0.45\u0026ndash;0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.047\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.00(2.92\u0026ndash;6.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.57(3.72\u0026ndash;11.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT, U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30(18\u0026ndash;44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68(37\u0026ndash;111)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST, U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40(24\u0026ndash;63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68(45\u0026ndash;110)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGGT, U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28(21\u0026ndash;43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e124(79\u0026ndash;187)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALP, U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68(57\u0026ndash;80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92(67\u0026ndash;113)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal bilirubin, \u0026micro;mol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.9(5.3\u0026ndash;8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.9(5.5\u0026ndash;10.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALB, g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35.0\u0026thinsp;\u0026plusmn;\u0026thinsp;4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCK, U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64(35\u0026ndash;113)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79(38\u0026ndash;152)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDH, U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e320(265\u0026ndash;411)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e374(306\u0026ndash;466)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKL-6, U/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e823(575\u0026ndash;1237)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1159(730\u0026ndash;1773)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum ferritin, ng/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e580(225\u0026ndash;1179)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1203(736\u0026ndash;2281)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eESR, mm/H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27(16\u0026ndash;44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34(21\u0026ndash;57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.021\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP, mg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.4(1.5\u0026ndash;11.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.1(1.5\u0026ndash;28.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.026\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnti-Ro52 antibody positive, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76(49.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98(68.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSurvival outcomes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3-month mortality, n/N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16(10.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35(24.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6-month mortality, n/N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19(12.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56(38.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eALB, albumin; ALP, alkaline phosphatase; ALT, alanine aminotransferase; AST, aspartate aminotransferase; CK, creatine kinase; CRP, C-reactive protein; DM, dermatomyositis; ESR, erythrocyte sedimentation rate; GGT, gamma-glutamyl transpeptidase; ILD, interstitial lung disease; LDH, lactate dehydrogenase; MDA5, melanoma differentiation-associated gene 5; NLR, Neutrophil-to‐lymphocyte ratio; KL-6, Krebs Von den Lungen-6; RPILD, rapidly progressive interstitial lung disease.\u003c/p\u003e \u003cp\u003eStatistically significant results (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) are highlighted in bold.\u003c/p\u003e \u003cp\u003eCompared with the normal GGT group, the incidence rate of skin ulcer, RP-ILD and fever was higher in the elevated GGT group. Moreover, patients with elevated GGT levels had significantly increased levels of ALT, AST, ALP, LDH, ferritin, KL-6, ESR and CRP, but obviously decreased levels of ALB and lymphocyte counts than the normal GGT group (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA-E). In terms of survival outcomes, the 3-month and 6-month mortality were both evidently higher in the elevated GGT group than that in the normal GGT group (24.3% vs 10.3%, p\u0026thinsp;=\u0026thinsp;0.001; 38.9% vs 12.3, p\u0026lt;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). Likewise, the Kaplan\u0026ndash;Meier survival analysis demonstrated that the cumulative survival rate was significantly lower in the elevated GGT group than that in the normal GGT group (log-rank \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eFactors associated with mortality in MDA5\u0026thinsp;+\u0026thinsp;DM patients\u003c/h2\u003e \u003cp\u003eCox regression analysis was conducted to explore the factors associated with death in MDA5\u0026thinsp;+\u0026thinsp;DM patients. The optimal cut-off values of age, disease duration, lymphocyte count, ALT, AST, ALP, ALB, LDH, CRP, KL-6 and ferritin were determined based on the maximum Youden index. Univariable Cox regression analysis showed that age at onset\u0026thinsp;\u0026gt;\u0026thinsp;51 years, disease duration\u0026thinsp;\u0026le;\u0026thinsp;3 months, smoking history, skin ulcer, fever, RP-ILD, lymphocyte count\u0026thinsp;\u0026le;\u0026thinsp;0.6\u0026times;109/L, ALT\u0026thinsp;\u0026gt;\u0026thinsp;45U/L, AST\u0026thinsp;\u0026gt;\u0026thinsp;47U/L, GGT\u0026thinsp;\u0026gt;\u0026thinsp;58U/L, ALP\u0026thinsp;\u0026gt;\u0026thinsp;75U/L, Total bilirubin\u0026thinsp;\u0026gt;\u0026thinsp;10\u0026micro;mol/L, ALB\u0026thinsp;\u0026le;\u0026thinsp;33g/L, LDH\u0026thinsp;\u0026gt;\u0026thinsp;345U/L, CRP\u0026thinsp;\u0026gt;\u0026thinsp;5mg/L, KL-6\u0026thinsp;\u0026gt;\u0026thinsp;808U/mL, ferritin\u0026thinsp;\u0026gt;\u0026thinsp;1484ng/mL and anti-Ro52 antibody positivity were risk factors associated with death for MDA5\u0026thinsp;+\u0026thinsp;DM patients, while myalgia, myasthenia and arthralgia were protective factors of death.\u003c/p\u003e \u003cp\u003eFurther multivariate Cox regression analysis revealed that RP-ILD (HR 9.260, 95%CI 3.287\u0026ndash;26.092), GGT\u0026gt;58U/L (HR 1.885, 95%CI 1.047\u0026ndash;3.394), LDH\u0026gt;345U/L (HR 2.252, 95%CI 1.221\u0026ndash;4.154), CRP\u0026gt;5mg/L (HR 2.985, 95%CI 1.582\u0026ndash;5.632) and anti-Ro52 antibody positivity (HR 1.983, 95%CI 1.018\u0026ndash;3.863) were independent risk factors of mortality (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Therefore, elevated serum GGT level, defined as serum GGT level\u0026gt;58U/L, was an independent risk factor for mortality in MDA5\u0026thinsp;+\u0026thinsp;DM patients.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVariables associated with death in MDA5\u0026thinsp;+\u0026thinsp;DM patients from univariable and multivariate Cox regression analysis.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eUnivariate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eMultivariate\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at onset\u0026thinsp;\u0026gt;\u0026thinsp;51 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.741(1.682\u0026ndash;4.465)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease duration\u0026thinsp;\u0026le;\u0026thinsp;3 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.925(1.646\u0026ndash;5.197)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking history\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.964(1.105\u0026ndash;3.491)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSkin ulcer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.282(1.426\u0026ndash;3.651)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyalgia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.593(0.361\u0026ndash;0.972)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyasthenia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.514(0.313\u0026ndash;0.843)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArthralgia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.494(0.313\u0026ndash;0.778)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.153(1.359\u0026ndash;3.409)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRP-ILD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20.331(8.222\u0026ndash;50.274)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.260(3.287\u0026ndash;26.092)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocyte\u0026thinsp;\u0026le;\u0026thinsp;0.6\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.928(1.890\u0026ndash;4.538)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT\u0026thinsp;\u0026gt;\u0026thinsp;45U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.024(1.304\u0026ndash;3.144)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST\u0026thinsp;\u0026gt;\u0026thinsp;47U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.279(1.981\u0026ndash;5.425)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGGT\u0026thinsp;\u0026gt;\u0026thinsp;58U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.334(2.060\u0026ndash;5.397)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.885(1.047\u0026ndash;3.394)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALP\u0026thinsp;\u0026gt;\u0026thinsp;75U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.510(1.561\u0026ndash;4.037)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALB\u0026thinsp;\u0026le;\u0026thinsp;33g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.315(3.116\u0026ndash;9.065)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal bilirubin\u0026thinsp;\u0026gt;\u0026thinsp;10\u0026micro;mol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.204(1.402\u0026ndash;3.465)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDH\u0026thinsp;\u0026gt;\u0026thinsp;345U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.966(2.393\u0026ndash;6.570)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.252(1.221\u0026ndash;4.154)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP\u0026thinsp;\u0026gt;\u0026thinsp;5mg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.656(2.747\u0026ndash;7.892)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.985(1.582\u0026ndash;5.632)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKL-6\u0026thinsp;\u0026gt;\u0026thinsp;808U/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.378(1.359\u0026ndash;4.161)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum ferritin\u0026thinsp;\u0026gt;\u0026thinsp;1484ng/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.302(2.026\u0026ndash;5.382)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnti-Ro52 antibody positivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.727(1.634\u0026ndash;4.553)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.983(1.018\u0026ndash;3.863)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eALB, albumin; ALP, alkaline phosphatase; ALT, alanine aminotransferase; AST, aspartate aminotransferase; CI, confidence interval; CRP, C-reactive protein; DM, dermatomyositis; GGT, gamma-glutamyl transpeptidase; HR, hazard ratio; LDH, lactate dehydrogenase; MDA5, melanoma differentiation-associated gene 5; KL-6, Krebs Von den Lungen-6; RPILD, rapidly progressive interstitial lung disease.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003ePredictive value of serum GGT level for mortality\u003c/h2\u003e \u003cp\u003ePrevious studies suggested that some laboratory parameters including lymphocyte counts and serum LDH, CRP, and ferritin levels could predict mortality in MDA5\u0026thinsp;+\u0026thinsp;DM patients. We further compared the predictive value of serum GGT level for mortality with the above prognostic biomarkers. ROC curves indicated that the AUC of CRP, LDH, GGT, lymphocyte counts and ferritin levels for predicting 6-month mortality were 0.725(95%CI 0.653\u0026ndash;0.796), 0.719(95%CI 0.650\u0026ndash;0.788), 0.711(95%CI 0.647\u0026ndash;0.774), 0.680(95%CI 0.610\u0026ndash;0.751) and 0.676(95%CI 0.594\u0026ndash;0.757) respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These results indicated that serum GGT level exhibited a comparable predictive value for mortality in MDA5\u0026thinsp;+\u0026thinsp;DM patients.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn addition, Spearman correlation analysis was employed to determine the correlations between serum GGT levels and these prognostic biomarkers. Serum GGT levels showed positive correlations with serum ferritin, LDH and KL-6 levels (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.475, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001; \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.311, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001; \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.295, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001 respectively), while negatively associated with ALB concentrations (\u003cem\u003er\u003c/em\u003e=-0.368, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this large retrospective cohort study, 48.2% of MDA5\u0026thinsp;+\u0026thinsp;DM patients presented with elevated levels of serum GGT. Compared with the normal GGT group, patients in the elevated GGT group had an increased incidence of skin ulcer and RP-ILD, higher levels of CRP, LDH, ferritin and KL-6, while lower lymphocyte counts. Moreover, patients with elevated serum GGT levels had significantly higher 3-month and 6-month mortality. To the best of our knowledge, this is the first study to identify that elevated serum GGT level is a reliable and readily available predictor for mortality in patients with MDA5\u0026thinsp;+\u0026thinsp;DM.\u003c/p\u003e \u003cp\u003eSeveral studies have been dedicated to exploring the predictors of mortality in MDA5\u0026thinsp;+\u0026thinsp;DM patients. It has been demonstrated that old age, RP-ILD, anti-Ro52 antibody positivity, lymphocytopenia and high levels of ferritin, CRP, LDH and KL-6 are risk factors for mortality in patients with MDA5\u0026thinsp;+\u0026thinsp;DM[\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Consistent with previous studies, our study indicated that RP-ILD, anti-Ro52 antibody positivity, elevated serum LDH and CRP levels were independent risk factors of mortality in MDA5\u0026thinsp;+\u0026thinsp;DM patients. In addition to the above well-known predictors, we first revealed that elevated serum GGT level is a novel risk factor that has not been reported previously.\u003c/p\u003e \u003cp\u003eAt present, studies regarding the relationships between serum GGT levels and prognosis in MDA5\u0026thinsp;+\u0026thinsp;DM patients are limited. A small sample-sized retrospective study indicated that serum GGT levels were obviously higher in dead patients compared with alive patients[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In line with this study, we found that patients with elevated serum GGT levels had a significantly higher incidence of RP-ILD and short-term mortality. Furthermore, patients in the elevated GGT group presented with evidently higher levels of LDH, KL-6, ferritin, CRP, anti-Ro52 antibody positivity and lower lymphocyte counts. All the laboratory parameters mentioned above were associated with poor prognosis in MDA5\u0026thinsp;+\u0026thinsp;DM patients.\u003c/p\u003e \u003cp\u003eGGT in the serum mainly originates from the liver. Serum GGT as a common indicator of liver function is easily accessible in routine clinical practice. In our study, compared with other previously known laboratory predictors, serum GGT shows comparable and satisfactory prediction performance. Therefore, serum GGT level is a reliable and readily available predictor for mortality in MDA5\u0026thinsp;+\u0026thinsp;DM patients. This study provides clinicians with a novel and easily available prognostic biomarker, which is helpful for better prognosis evaluation and risk stratification.\u003c/p\u003e \u003cp\u003eIn recent years, accumulated evidences have demonstrated that serum elevated GGT level is associated with cardiovascular diseases, metabolic syndrome, diabetes mellitus, cancer, chronic kidney disease, fractures, cardiovascular mortality and all-cause mortality[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan additionalcitationids=\"CR20 CR21 CR22 CR23\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. GGT as a key transferase enzyme plays a vital role in the resynthesis of glutathione (GSH), which is an important intracellular antioxidant protecting cells against oxidative damage [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. GGT levels may elevate in order to produce more GSH in response to oxidative stress[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Therefore, GGT has become a well-established biomarker of oxidative stress[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. However, studies regarding the link between oxidative stress and MDA5\u0026thinsp;+\u0026thinsp;DM are still limited. A recent study suggested oxidative stress may exist in MDA5\u0026thinsp;+\u0026thinsp;DM[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Our study provides more evidence that oxidative stress may be involved in the development of MDA5\u0026thinsp;+\u0026thinsp;DM. Further studies are still needed to confirm the role of oxidative stress in the pathogenesis of MDA5\u0026thinsp;+\u0026thinsp;DM.\u003c/p\u003e \u003cp\u003eIn addition, oxidative stress and inflammation are closely related and tightly linked pathophysiological processes[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Serum GGT level is also considered as a biomarker of systemic inflammation[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Previous studies have reported that serum GGT levels positively correlate with serum CRP concentration in patients with RA, PsA and SLE[\u003cspan additionalcitationids=\"CR11 CR12 CR13\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Moreover, elevated serum GGT level may indicate an increased risk of SLE aggravation[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Similarly, our present study found that serum GGT level is positively correlated with CRP level and disease severity in patients with MDA5\u0026thinsp;+\u0026thinsp;DM. Therefore, serum GGT may become a promising biomarker of systemic inflammation and oxidative stress among MDA5\u0026thinsp;+\u0026thinsp;DM patients.\u003c/p\u003e \u003cp\u003eFurthermore, several studies have confirmed that macrophage activation may play a vital role in the pathogenesis of MDA5\u0026thinsp;+\u0026thinsp;DM[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Thus, we speculate that excessive activation of hepatic macrophages may cause hepatic injury including elevated serum GGT levels[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Moreover, our study identified that serum GGT levels correlated positively with serum concentrations of ferritin, which is a well-known biomarker of macrophage activation[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Therefore, GGT may also serve as a biomarker of macrophage activation in MDA5\u0026thinsp;+\u0026thinsp;DM patients.\u003c/p\u003e \u003cp\u003eOur study has some limitations. First, this was a single-center retrospective study, which inevitably had a risk of selection bias. Second, although we had tried to exclude the possible factors influencing serum GGT levels, the effects of drugs on liver enzymes could not be ruled out completely owing to some patients might have received non-steroidal anti-inflammatory drugs to relieve the symptoms of fever or arthralgia before MDA5\u0026thinsp;+\u0026thinsp;DM was diagnosed. Further multi-center prospective studies are still required to validate our findings.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, this study revealed that MDA5\u0026thinsp;+\u0026thinsp;DM patients with elevated serum GGT levels had a higher short-term mortality rate. Elevated serum GGT level was an independent risk factor for mortality in MDA5\u0026thinsp;+\u0026thinsp;DM patients. As a novel and readily available predictor, serum GGT level may help clinicians in identifying MDA5\u0026thinsp;+\u0026thinsp;DM patients at high risk of death.\u003c/p\u003e"},{"header":"List Of Abbreviations","content":" \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eALB\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eAlbumin\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eALP\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eAlkaline phosphatase\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eALT\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eAlanine aminotransferase\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eANA\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eAntinuclear antibody\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eAST\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eAspartate aminotransferase\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eCI\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eConfidence interval\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eCK\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eCreatine kinase\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eCRP\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eC-reactive protein\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eDM\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eDermatomyositis\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eESR\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eErythrocyte sedimentation rate\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eGGT\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eGamma-glutamyl transpeptidase\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eHR\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eHazard ratio\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eILD\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eInterstitial lung disease\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eLDH\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eLactate dehydrogenase\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eMDA5\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eMelanoma differentiation-associated gene 5\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eNLR\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eNeutrophil-to‐lymphocyte ratio\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eKL-6\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003eROC\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eKrebs Von den Lungen-6\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003eReceiver operation characteristic\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eRP-ILD\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eRapidly progressive interstitial lung disease\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003cbr/\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eThis study was approved by the Ethical Committee of the First Affiliated Hospital of Zhengzhou University (approval number: 2021-KY-1101). Written informed consents were waived because of the retrospective nature of the study.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\n\u003cp\u003eData sets generated during the current study are available from the corresponding author on reasonable request, but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis study was supported by the National Natural Science Foundation of China (No. 82302051, No. 82371819) and a Joint project of Medical Science and Technology Key Program of Henan Province (LHGJ20210278, LHGJ20230175).\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026apos; contributions\u003c/h2\u003e\n\u003cp\u003eYZ, SL, TL and WH designed this study. Material preparation, data collection and analysis were performed by WH, YZ, PZ, FD, YD, TL, LY, LL and LZ. WH drafted the manuscript.\u0026nbsp;PZ and YZ\u0026nbsp;revised the manuscript.\u0026nbsp;All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLu X, Peng Q, Wang G. Anti-MDA5 antibody-positive dermatomyositis: pathogenesis and clinical progress. Nat Rev Rheumatol. 2024;20(1):48\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXie H, Zhang D, Wang Y, Shi Y, Yuan Y, Wang L, et al. Risk factors for mortality in patients with anti-MDA5 antibody-positive dermatomyositis: A meta-analysis and systematic review. Semin Arthritis Rheum. 2023;62:152231.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYou H, Wang L, Wang J, Lv C, Xu L, Yuan F, et al. Time-dependent changes in RPILD and mortality risk in anti-MDA5\u0026thinsp;+\u0026thinsp;DM patients: a cohort study of 272 cases in China. Rheumatology (Oxford). 2023;62(3):1216\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGono T, Masui K, Nishina N, Kawaguchi Y, Kawakami A, Ikeda K et al. Risk Prediction Modeling Based on a Combination of Initial Serum Biomarker Levels in Polymyositis/Dermatomyositis-Associated Interstitial Lung Disease. Arthritis \u0026amp; rheumatology (Hoboken, NJ). 2021;73(4):677\u0026ndash;86.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu W, Xu W, Sun W, Zhang D, Zhao J, Luo Q, et al. Forced vital capacity predicts the survival of interstitial lung disease in anti-MDA5 positive dermatomyositis: a multi-centre cohort study. Rheumatology (Oxford). 2021;61(1):230\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang H, Chen X, Du Y, Wang L, Wang Q, Wu H, et al. Mortality risk in patients with anti-MDA5 dermatomyositis is related to rapidly progressive interstitial lung disease and anti-Ro52 antibody. Arthritis Res therapy. 2023;25(1):127.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGono T, Kawaguchi Y, Satoh T, Kuwana M, Katsumata Y, Takagi K, et al. Clinical manifestation and prognostic factor in anti-melanoma differentiation-associated gene 5 antibody-associated interstitial lung disease as a complication of dermatomyositis. Rheumatology (Oxford). 2010;49(9):1713\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLian L, Tong JJ, Xu SQ. Clinical features and prognostic factors of anti-melanoma differentiation-associated gene 5 antibody-positive dermatomyositis with rapidly progressive interstitial lung disease in Chinese patients. Immun Inflamm Dis. 2023;11(6):e882.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrennan PN, Dillon JF, Tapper EB. Gamma-Glutamyl Transferase (γ-GT) - an old dog with new tricks? Liver Int. 2022;42(1):9\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang X, Mao Y, Ji S, Hu H, Li Q, Liu L, et al. Gamma-glutamyl transpeptidase and indirect bilirubin may participate in systemic inflammation of patients with psoriatic arthritis. Adv Rheumatol. 2023;63(1):53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee DH, Jacobs DR Jr. Association between serum gamma-glutamyltransferase and C-reactive protein. Atherosclerosis. 2005;178(2):327\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLowe JR, Pickup ME, Dixon JS, Leatham PA, Rhind VM, Wright V, et al. Gamma glutamyl transpeptidase levels in arthritis: a correlation with clinical and laboratory indices of disease activity. Ann Rheum Dis. 1978;37(5):428\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVergneault H, Vandebeuque E, Codullo V, Allanore Y, Avouac J. Disease Activity Score in 28 Joints Using GGT Permits a Dual Evaluation of Joint Activity and Cardiovascular Risk. J Rhuematol. 2020;47(12):1738\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang W, Tang Z, Shi Y, Ji L, Chen X, Chen Y, et al. Association Between Gamma-Glutamyl Transferase, Total Bilirubin and Systemic Lupus Erythematosus in Chinese Women. Front Immunol. 2021;12:682400.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMammen AL, Allenbach Y, Stenzel W, Benveniste O. 239th ENMC International Workshop: Classification of dermatomyositis, Amsterdam, the Netherlands, 14\u0026ndash;16 December 2018. Neuromuscular disorders: NMD. 2020;30(1):70\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSato S, Hirakata M, Kuwana M, Suwa A, Inada S, Mimori T, et al. Autoantibodies to a 140-kd polypeptide, CADM-140, in Japanese patients with clinically amyopathic dermatomyositis. Arthritis Rheum. 2005;52(5):1571\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoghadam-Kia S, Oddis CV, Sato S, Kuwana M, Aggarwal R. Anti-Melanoma Differentiation-Associated Gene 5 Is Associated With Rapidly Progressive Lung Disease and Poor Survival in US Patients With Amyopathic and Myopathic Dermatomyositis. Arthritis Care Res. 2016;68(5):689\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJin Q, Fu L, Yang H, Chen X, Lin S, Huang Z, et al. Peripheral lymphocyte count defines the clinical phenotypes and prognosis in patients with anti-MDA5-positive dermatomyositis. J Intern Med. 2023;293(4):494\u0026ndash;507.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKunutsor SK. Gamma-glutamyltransferase-friend or foe within? Liver Int. 2016;36(12):1723\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYi SW, Lee SH, Hwang HJ, Yi JJ. Gamma-glutamyltransferase and cardiovascular mortality in Korean adults: A cohort study. Atherosclerosis. 2017;265:102\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLai SW. Gamma-glutamyl-transferase and hip fracture. Osteoporos Int. 2022;33(8):1825\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYoon HE, Mo EY, Shin SJ, Moon SD, Han JH, Kim ES. Serum gamma-glutamyltransferase is not associated with subclinical atherosclerosis in patients with type 2 diabetes. Cardiovasc Diabetol. 2016;15(1):108.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLong Y, Zeng F, Shi J, Tian H, Chen T. Gamma-glutamyltransferase predicts increased risk of mortality: a systematic review and meta-analysis of prospective observational studies. Free Radic Res. 2014;48(6):716\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKazemi-Shirazi L, Endler G, Winkler S, Schickbauer T, Wagner O, Marsik C. Gamma glutamyltransferase and long-term survival: is it just the liver? Clin Chem. 2007;53(5):940\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWhitfield JB. Gamma glutamyl transferase. Crit Rev Clin Lab Sci. 2001;38(4):263\u0026ndash;355.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSridhar SB, Xu F, Darbinian J, Quesenberry CP, Ferrara A, Hedderson MM. Pregravid liver enzyme levels and risk of gestational diabetes mellitus during a subsequent pregnancy. Diabetes Care. 2014;37(7):1878\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang W, Chen D, Wang Z, Ren F, Luo L, Zhou J, et al. Evaluating the value of superoxide dismutase in anti-MDA5-positive dermatomyositis associated with interstitial lung disease. Rheumatology (Oxford). 2023;62(3):1197\u0026ndash;203.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBiswas SK. Does the Interdependence between Oxidative Stress and Inflammation Explain the Antioxidant Paradox? Oxid Med Cell Longev. 2016;2016:5698931.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNagashima T, Kamata Y, Iwamoto M, Okazaki H, Fukushima N, Minota S. Liver dysfunction in anti-melanoma differentiation-associated gene 5 antibody-positive patients with dermatomyositis. Rheumatol Int. 2019;39(5):901\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Dermatomyositis, Anti-MDA5 antibody, Gamma-glutamyl transferase, Mortality","lastPublishedDoi":"10.21203/rs.3.rs-4431215/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4431215/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eGamma-glutamyl transferase (GGT) has been identified to correlate with systemic inflammation in autoimmune diseases, while the role of GGT in anti-melanoma differentiation-associated protein 5 antibody-positive dermatomyositis (MDA5\u0026thinsp;+\u0026thinsp;DM) remains unknown. This study aimed to investigate the clinical and prognostic significance of serum GGT in MDA5\u0026thinsp;+\u0026thinsp;DM patients.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003ePatients with MDA5\u0026thinsp;+\u0026thinsp;DM admitted to the First Affiliated Hospital of Zhengzhou University between February 2019 and May 2023 were retrospectively analyzed. We compared the clinical features and prognosis between MDA5\u0026thinsp;+\u0026thinsp;DM patients with elevated serum GGT levels and those with normal serum GGT levels. Cox regression analysis was performed to identify independent factors associated with mortality.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 299 MDA5\u0026thinsp;+\u0026thinsp;DM patients were enrolled in this study. During the median follow-up time of 13.1(4.4\u0026ndash;28.1) months, 153(51.2%) patients developed rapidly progressive interstitial lung disease (RP-ILD) and 75(25.1%) patients died within 6 months after disease onset. Serum GGT levels were significantly higher in the death group compared to the survival group [95(56\u0026ndash;165) vs 45(26\u0026ndash;90) U/L, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001]. Based on the serum GGT levels at the time of diagnosis, we divided all the patients into two groups: normal GGT group (GGT\u0026thinsp;\u0026le;\u0026thinsp;58U/L, n\u0026thinsp;=\u0026thinsp;155) and elevated GGT group (GGT\u0026gt;58U/L, n\u0026thinsp;=\u0026thinsp;144). Compared with the normal GGT group, patients in the elevated GGT group had increased incidences of skin ulcer and RP-ILD, higher levels of lactate dehydrogenase (LDH), Krebs Von den Lungen-6 (KL-6), ferritin and C-reactive protein (CRP), while lower levels of albumin and lymphocyte counts. Moreover, the Kaplan\u0026ndash;Meier survival analysis demonstrated that the cumulative survival rate was significantly lower in the elevated GGT group than that in the normal GGT group (log-rank \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Multivariate Cox regression analysis revealed that RP-ILD, GGT\u0026gt;58U/L, LDH\u0026gt;345U/L, CRP\u0026gt;5mg/L and anti-Ro52 antibody positivity were independent risk factors of mortality in MDA5\u0026thinsp;+\u0026thinsp;DM patients.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eElevated serum GGT level was an independent risk factor for mortality in MDA5\u0026thinsp;+\u0026thinsp;DM patients. As a novel and readily available predictor, serum GGT level may help clinicians in guiding prognostic stratification and personalized treatment.\u003c/p\u003e","manuscriptTitle":"Elevated serum gamma-glutamyl transferase level as a predictor of mortality in patients with anti-MDA5 antibody-positive dermatomyositis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-18 20:45:04","doi":"10.21203/rs.3.rs-4431215/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f8787f12-3c4a-4409-8a8e-9f5ed6ee424c","owner":[],"postedDate":"July 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-08-14T12:16:15+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-18 20:45:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4431215","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4431215","identity":"rs-4431215","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}