Please wait a minute...
Shopping Cart Email List Chinese
Advanced Search Fig/Tab
Frontiers of Medicine

ISSN 2095-0217

ISSN 2095-0225(Online)

CN 11-5983/R

Postal Subscription Code 80-967

2018 Impact Factor: 1.847

Featured Articles  |  Most Downloaded  |  Most Reading
Online Submission Subscribe to Our RSS Content Feed
Front. Med.    2021, Vol. 15 Issue (4) : 585-593    https://doi.org/10.1007/s11684-020-0817-2
RESEARCH ARTICLE
Cohort study of patients with Stevens--Johnson syndrome and toxic epidermal necrolysis in China: evaluation of risk models and new predictor of pulmonary consolidation on computed tomography
Yanhong Shou1, Lu Yang1, Yongsheng Yang1(), Xiaohua Zhu1, Feng Li1, Bo Yin2, Yingyan Zheng2, Jinhua Xu1,3()
1. Department of Dermatology, Huashan Hospital, Fudan University, Shanghai 200040, China
2. Department of Radiology, Huashan Hospital, Fudan University, Shanghai 200040, China
3. Shanghai Institute of Dermatology, Shanghai 200040, China
 Download: PDF(339 KB)   HTML
 Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks
Abstract

Stevens--Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are rare but severe diseases. This study aimed to validate the predictive ability of risk models in patients with SJS/TEN and propose possible refinement in China. Patients in the Department of Dermatology of Huashan Hospital from January 2008 to January 2019 were included. Results showed that the severity-of-illness score for TEN (SCORTEN) had a good discrimination (area under the receiver operating characteristic curve (AUC), 0.78), and it was superior to auxiliary score (AS) and ABCD-10, which indicates age, bicarbonate level, cancer, dialysis, and 10% involved body surface area (AUC, 0.69 and 0.68, respectively). The calibration of SCORTEN (Hosmer–Lemeshow goodness-of-fit test, P = 0.69) was also better than that of AS (P = 0.25) and ABCD-10 (P = 0.55). SCORTEN and ABCD-10 were similar (Brier score (BS), 0.04 and 0.04) in terms of accuracy of predictions. In addition, the imaging appearance of pulmonary consolidation on computed tomography was associated with high mortality. Refined models were formed using the variables and this imaging appearance. The refined AS and ABCD-10 models were similar in discrimination compared with the original SCORTEN (0.74 vs. 0.78, P = 0.23; 0.74 vs. 0.78, P = 0.30, respectively). Therefore, SCORTEN showed good discrimination performance, calibration, and accuracy, and refined AS or ABCD-10 model may be an option when SCORTEN variables are not available.
Keywords Stevens–Johnson syndrome      toxic epidermal necrolysis      auxiliary score      ABCD-10      pulmonary consolidation     
Corresponding Author(s): Yongsheng Yang,Jinhua Xu   
Just Accepted Date: 17 November 2020   Online First Date: 02 March 2021    Issue Date: 23 September 2021
 Cite this article:   
Yanhong Shou,Lu Yang,Yongsheng Yang, et al. Cohort study of patients with Stevens--Johnson syndrome and toxic epidermal necrolysis in China: evaluation of risk models and new predictor of pulmonary consolidation on computed tomography[J]. Front. Med., 2021, 15(4): 585-593.
 URL:  
https://academic.hep.com.cn/fmd/EN/10.1007/s11684-020-0817-2
https://academic.hep.com.cn/fmd/EN/Y2021/V15/I4/585
SCORTEN
Variables Weight
Age>40 years 1
Involved BSA at day 1>10% 1
Presence of cancer or malignancy 1
Heart rate>120 beats per minute 1
Serum urea level>10 mmol/L 1
Serum bicarbonate level<20mmol/L 1
Serum glucose level>14 mmol/L 1
Range of score 0–7
AS
Variables Weight
Age 31–55 years 1
Age 56–75 years 2
Age>75 years 3
TEN (involved BSA>30%) 1
Presence of cancer or malignancy 1
Range of score 0–5
ABCD-10
Variables Weight
Age≥50 years 1
Involved BSA at day 1≥10% 1
Serum bicarbonate level<20 mmol/L 1
Active/ongoing cancer 2
Dialysis prior to admission 3
Range of score 0–6
Tab.1  Criteria for SCORTEN, AS, and ABCD-10
Patients Observed mortality, n (%) Expected mortality, n (%) P
Overall 217 9 (4) 17.80 (8.2) 0.11
Per SCORTEN value
0 50 0 (0) 0.50 (1) 1
1 93 3 (3) 3.70 (4) 1
2 55 1 (2) 6.60 (12) 0.06
3 13 2 (15) 4.20 (32) 0.65
4 5 2 (40) 3.10 (62) 1
5 1 1 (100) 0.90 (85) 1
6 0 - -
7 0 - -
Per severity grade
SJS 145 2 (1) 11.30 (8)
SJS/TEN overlap 19 3 (16) 4.90 (26)
TEN 53 4 (8) 11.20 (21)
Tab.2  Comparison of observed and expected mortality of SCORTEN
Model AUC (95% CI) Brier score P value of Hosmer–Lemeshow statistic
SCORTEN 0.78 (0.61–0.96) 0.04 0.69
AS 0.69 (0.53–0.85) 0.07 0.25
ABCD-10 0.68 (0.50–0.86) 0.04 0.55
Refined SCORTEN 0.79 (0.62–0.95) 0.03 0.61
Refined AS 0.74 (0.56–0.92) 0.04 0.67
Refined ABCD-10 0.74 (0.55–0.92) 0.04 0.57
Tab.3  Comparison of different models
Fig.1  AUCs for SCORTEN, AS, and ABCD-10 (n = 217; AUC= 0.78, 0.69, and 0.68, respectively). Abbreviations: AUC, area under the receiver operating characteristic curve; SCORTEN, score of toxic epidermal necrolysis; AS, auxiliary score; ABCD-10 indicates age, bicarbonate level, cancer, dialysis, and 10% involved body surface area.
　
　		 Patients
　		 Observed mortality,
n (%)		 Expected mortality,
n (%)		 P value　
Overall 217 9 (5) 39.10 (18) 0.00
Per AS value
0 37 0 (0) 1.50 (4) 1
1 65 2 (3) 6.50 (10) 0.27
2 84 4 (5) 17.60 (21) 0.01
3 28 2 (7) 11.20 (40) 0.01
4 3 1 (33) 1.90 (63) 1
5 − − − 　
Tab.4  Comparison of observed and expected mortality of AS
　 Patients Observed mortality Expected mortality P
　 　 n (%) n (%) 　
Overall 217 9 (5) 15.20 (7) 0.29
Per ABCD-10 value
0 72 1 (2) 1.40 (2) 1
1 108 5 (5) 5.40 (5) 1
2 29 0 (0) 3.50 (12) 0.24
3 7 2 (3) 1.80 (26) 1
4 1 1 (100) 0.50 (45) 1
5 —— —— —— 　
Tab.5  Comparison of observed and expected mortality of ABCD-10 model
Characteristic Survived to discharge (n = 208) Died in the hospital (n = 9) OR (95% CI) P value
Demographics
?Female, n (%) 96 (46.15) 3 (33.33) 1.74 (0.42–7.16) 0.44
?Age, mean (SD), year 47.77 (18.27) 57.44 (19.05) 1.03 (0.99–1.07) 0.13
Disease severity
?BSA at day 0, median% (IQR) 29.56 (−7.68–66.80) 53.33 (9.35–97.31) 1.01 (0.99–1.03) 0.08
?BSA by category, n (%)
??SJS (<10%) 144 (69.23) 3 (33.33) REF
??SJS/TEN overlap (10%–30%) 19 (9.13) 2 (22.22) 5.52 (0.86–35.47) 0.07
??TEN (>30%) 54 (25.96) 4 (44.44) 3.76 (0.81–17.39) 0.09
SCORTEN variables at day 1, n (%)
?Age >40 years 135 (64.90) 8 (88.89) 4.32 (0.53–35.26) 0.17
?Heart rate >120 bpm 3 (0.01) 1 (11.11) 8.54 (0.79–91.54) 0.08
?Cancer 10 (4.90) 1 (11.11) 2.48 (0.28–21.76) 0.41
?BSA at day 1 >10% 67 (32.21) 6 (66.67) 4.21 (1.02–17.34) 0.05
?Serum urea level >10 mmol/L 19 (9.13) 5 (55.56) 12.43 (2.07–50.26) 0
?Serum bicarbonate level <20 mmol/L 0 (0) 2 (22.22) 1.92 (0.48–7.70) 0.08
?Serum glucose level >14 mmol/L 7 (0.03) 1 (11.11) 3.59 (0.39–32.76) 0.26
AS variables, n (%)
?Age by category
??<31 years 47 (22.59) 1 (11.11) REF
??31–55 years 84 (40.38) 4 (44.44) 1.70 (0.17–16.86) 0.65
??56–75 years 73 (35.10) 2 (22.22) 1.97 (0.20–19.54) 0.56
??>75 years 13 (6.25) 2 (22.22) 8.36 (0.69–100.77) 0.1
?TEN 50 (24.04) 4 (44.44) 2.53 (0.65–9.78) 0.18
ABCD-10 variables, n (%)
?Age ≥50 years 96 (46.15) 5 (55.56) 1.45 (0.38–5.58) 0.58
?Dialysis prior to admission 3 (0.01) 1 (11.11) 8.54 (0.80–91.45) 0.08
Medical comorbidities present on admission, n (%)
?Coronary heart disease 4 (0.02) 1 (11.11) 1.73 (0.20–14.85) 0.12
?Gout 14 (6.73) 1 (11.11) 1.69 (0.48–6.03) 0.62
?Cardiac dysfunction 7 (3.37) 1 (11.11) 3.59 (0.39–32.76) 0.26
?Diabetes 20 (9.62) 1 (11.11) 1.15 (0.13–9.67) 0.9
?Chronic kidney disease 7 (3.37) 2 (22.22) 8.20 (1.44–46.87) 0.02
?Hepatitis 6 (0.03) 0 (0) 0.96 (0.93–0.99) 0.77
?Inflammatory bowel disease 2 (0.01) 0 (0) 0.99 (0.98–1.00) 0.92
?Pulmonary infection 18 (8.65) 1 (11.11) 1.40 (0.17–11.90) 0.76
?Pulmonary consolidation on CT 14 (6.73) 2 (22.22) 7.50 (1.68–33.46) 0.01
Tab.6  Univariate analysis of potential prognostic factors for mortality in patients with SJS/TEN
Case No./age (year)/sex Length of hospital stay Causative drug Severity of disease Comorbidities Cause of death
1/66/M 12 Salvia miltiorrhiza SJS Gout, hypertension, and arrhythmia No
2/55/M 12 Gabapentin SJS Pulmonary infection No
3/74/M 18 Allopurinol SJS Gout, hypertension, diabetes, and chronic renal failure No
4/27/M 27 Penicillin SJS Pulmonary infection No
5/25/F 17 Acetaminophen SJS Pulmonary infection No
6/70/M 14 Oxcarbazepine SJS/TEN Brain metastasis of No
lung cancer, coronary heart disease, bronchiectasis, and pulmonary infection
7/76/M 5 Acetaminophen SJS/TEN Hypertension and chronic obstructive pulmonary disease Acute renal dysfunction
8/49/F 19 Salvia miltiorrhiza SJS/TEN Pulmonary infection No
9/58/M 13 Salazosulfapyridine SJS/TEN Ankylosing spondylitis and pulmonary infection No
10/46/F 14 Combination of drugs TEN Hypertension, chronic hepatitis B, and chronic kidney disease Multiple organ dysfunction syndrome
11/50/M 5 Valproate sodium TEN Acute liver failure, electrolyte disturbance, chronic anemia, and pulmonary infection Multiple organ dysfunction syndrome
12/68/M 15 Combination of drugs TEN Arrhythmia and pulmonary infection No
13/16/F 18 Combination of drugs TEN Pulmonary infection No
14/61/F 21 Allopurinol TEN Hypertension, hypothyroidism, and pulmonary infection No
15/54/M 19 Combination of drugs TEN Follicular lymphoma IV, behcetsyndrome, pulmonary infection, and bronchiectasis No
16/37/M 20 Combination of drugs TEN Pulmonary infection No
Tab.7  Cases with imaging appearance of pulmonary consolidation on CT
Fig.2  Area under the curve was similar for refined SCORTEN and SCORTEN, refined AS and AS, and refined ABCD-10 and ABCD-10 (n = 217; 0.79 vs. 0.78, P = 0.54; 0.74 vs. 0.69, P = 0.18; 0.74 vs. 0.68, P = 0.20, respectively). Abbreviations:SCORTEN, score of toxic epidermal necrolysis; AS, auxiliary score; ABCD-10 indicates age, bicarbonate level, cancer, dialysis, and 10% involved body surface area.
1 J Schneck, JP Fagot, P Sekula, B Sassolas, JC Roujeau, M Mockenhaupt. Effects of treatments on the mortality of Stevens−Johnson syndrome and toxic epidermal necrolysis: a retrospective study on patients included in the prospective EuroSCAR Study. J Am Acad Dermatol 2008; 58(1): 33–40
https://doi.org/10.1016/j.jaad.2007.08.039 pmid: 17919775
2 S Bastuji-Garin, B Rzany, RS Stern, NH Shear, L Naldi, JC Roujeau. Clinical classification of cases of toxic epidermal necrolysis, Stevens−Johnson syndrome, and erythema multiforme. Arch Dermatol 1993; 129(1): 92–96
https://doi.org/10.1001/archderm.1993.01680220104023 pmid: 8420497
3 J Diphoorn, S Cazzaniga, C Gamba, J Schroeder, A Citterio, AL Rivolta, GD Vighi, L, Naldi   REACT-Lombardia study group. Incidence, causative factors and mortality rates of Stevens−Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) in northern Italy: data from the REACT registry. Pharmacoepidemiol Drug Saf 2016; 25(2): 196–203
https://doi.org/10.1002/pds.3937 pmid: 26687641
4 DY Hsu, J Brieva, NB Silverberg, JI Silverberg. Morbidity and mortality of Stevens−Johnson syndrome and toxic epidermal necrolysis in United States adults. J Invest Dermatol 2016; 136(7): 1387–1397
https://doi.org/10.1016/j.jid.2016.03.023 pmid: 27039263
5 S Bastuji-Garin, N Fouchard, M Bertocchi, JC Roujeau, J Revuz, P Wolkenstein. SCORTEN: a severity-of-illness score for toxic epidermal necrolysis. J Invest Dermatol 2000; 115(2): 149–153
https://doi.org/10.1046/j.1523-1747.2000.00061.x pmid: 10951229
6 RG Micheletti, Z Chiesa-Fuxench, MH Noe, S Stephen, M Aleshin, A Agarwal, J Boggs, AR Cardones, JK Chen, J Cotliar, MDP Davis, A Dominguez, LP Fox, S Gordon, R Hamrick, B Ho, LC Hughey, LM Jones, BH Kaffenberger, K Kindley, D Kroshinsky, BY Kwong, DD Miller, A Mostaghimi, A Musiek, AG Ortega-Loayza, R Patel, A Posligua, M Rani, S Saluja, VR Sharon, K Shinkai, JS John, N Strickland, EM Summers, N Sun, KA Wanat, DA Wetter, S Worswick, C Yang, DJ Margolis, JM Gelfand, M Rosenbach. Stevens−Johnson syndrome/toxic epidermal necrolysis: a multicenter retrospective study of 377 adult patients from the United States. J Invest Dermatol 2018; 138(11): 2315–2321
https://doi.org/10.1016/j.jid.2018.04.027 pmid: 29758282
7 P Sekula, Y Liss, B Davidovici, A Dunant, JC Roujeau, S Kardaun, L Naldi, M Schumacher, M Mockenhaupt. Evaluation of SCORTEN on a cohort of patients with Stevens−Johnson syndrome and toxic epidermal necrolysis included in the RegiSCAR study. J Burn Care Res 2011; 32(2): 237–245
https://doi.org/10.1097/BCR.0b013e31820aafbc pmid: 21228709
8 L Wang, XL Mei. Retrospective analysis of Stevens−Johnson syndrome and toxic epidermal necrolysis in 88 Chinese patients. Chin Med J (Engl) 2017; 130(9): 1062–1068
https://doi.org/10.4103/0366-6999.204929 pmid: 28469101
9 PD Mahar, J Wasiak, H Cleland, D Watters, E Paul, P Marsh, D Gin. Mortality and use of the auxiliary score in extensive toxic epidermal necrolysis patients admitted to an adult burns referral centre. Dermatology 2013; 227(2): 180–185
https://doi.org/10.1159/000354264 pmid: 24080507
10 MH Noe, M Rosenbach, RA Hubbard, A Mostaghimi, AR Cardones, JK Chen, J Cotliar, MDP Davis, A Dominguez, LP Fox, LC Hughey, BH Kaffenberger, D Kroshinsky, BY Kwong, DD Miller, A Musiek, AG Ortega-Loayza, VR Sharon, K Shinkai, EM Summers, KA Wanat, DA Wetter, S Worswick, DJ Margolis, JM Gelfand, RG Micheletti. Development and validation of a risk prediction model for in-hospital mortality among patients with Stevens−Johnson syndrome/toxic epidermal necrolysis-ABCD-10. JAMA Dermatol 2019; 155(4): 448–454
https://doi.org/10.1001/jamadermatol.2018.5605 pmid: 30840032
11 MS Yang, JY Lee, J Kim, GW Kim, BK Kim, JY Kim, HW Park, SH Cho, KU Min, HR Kang. Incidence of Stevens−Johnson syndrome and toxic epidermal necrolysis: a nationwide population-based study using national health insurance database in Korea. PLoS One 2016; 11(11): e0165933
https://doi.org/10.1371/journal.pone.0165933 pmid: 27835661
12 SS Vaishampayan, AL Das, R Verma. SCORTEN: does it need modification? Indian J Dermatol Venereol Leprol 2008; 74(1): 35–37
https://doi.org/10.4103/0378-6323.38405 pmid: 18187821
13 BF Firoz, JS Henning, LA Zarzabal, BH Pollock. Toxic epidermal necrolysis: five years of treatment experience from a burn unit. J Am Acad Dermatol 2012; 67(4): 630–635
https://doi.org/10.1016/j.jaad.2011.12.014 pmid: 22285617
14 C Weinand, W Xu, W Perbix, R Lefering, M Maegele, M Rathert, G Spilker. 27 years of a single burn centre experience with Stevens−Johnson syndrome and toxic epidermal necrolysis: analysis of mortality risk for causative agents. Burns 2013; 39(7): 1449–1455
https://doi.org/10.1016/j.burns.2013.03.011 pmid: 23702222
15 CH Hu, NJ Chang, EKW Liu, SS Chuang, WH Chung, JY Yang. SCORTEN and impaired renal function related to mortality of toxic epidermal necrolysis syndrome patients in the Asian population. J Eur Acad Dermatol Venereol 2013; 27(5): 628–633
https://doi.org/10.1111/j.1468-3083.2012.04502.x pmid: 22452516
16 N Xu, X Chen, S Wu, M Ye, M Zhang, L Tong, X Zhu, J Liu, F Hu, C Bai. Chronic pulmonary complications associated with toxic epidermal necrolysis: a case report and literature review. Exp Ther Med 2018; 16(3): 2027–2031
https://doi.org/10.3892/etm.2018.6357 pmid: 30186435
17 JA Hanley, BJ McNeil. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 1982; 143(1): 29–36
https://doi.org/10.1148/radiology.143.1.7063747 pmid: 7063747
18 S Lemeshow, DW Hosmer Jr. A review of goodness of fit statistics for use in the development of logistic regression models. Am J Epidemiol 1982; 115(1): 92–106
https://doi.org/10.1093/oxfordjournals.aje.a113284 pmid: 7055134
19 TA Gerds, T Cai, M Schumacher. The performance of risk prediction models. Biom J 2008; 50(4): 457–479
https://doi.org/10.1002/bimj.200810443 pmid: 18663757
20 PC Austin, JV Tu. Bootstrap methods for developing predictive models. Am Stat 2004; 58(2): 131–137
https://doi.org/10.1198/0003130043277
21 L Yang, Y Shou, F Li, X Zhu, Y Yang, J Xu. Retrospective study of 213 cases of Stevens–Johnson syndrome and toxic epidermal necrolysis from China. Burns 2020; 46(4): 959–969
pmid: 31898979
22 CM Walker, GF Abbott, RE Greene, JA Shepard, D Vummidi, SR Digumarthy. Imaging pulmonary infection: classic signs and patterns. AJR Am J Roentgenol 2014; 202(3): 479–492
https://doi.org/10.2214/AJR.13.11463 pmid: 24555584
23 P Sekula, A Dunant, M Mockenhaupt, L Naldi, JN Bouwes Bavinck, S Halevy, S Kardaun, A Sidoroff, Y Liss, M Schumacher, Jean-Claude Roujeau for the RegiSCAR study group. Comprehensive survival analysis of a cohort of patients with Stevens–Johnson syndrome and toxic epidermal necrolysis. J Invest Dermatol 2013; 133(5): 1197–1204
https://doi.org/10.1038/jid.2012.510 pmid: 23389396
24 R Cartotto, M Mayich, D Nickerson, M Gomez. SCORTEN accurately predicts mortality among toxic epidermal necrolysis patients treated in a burn center. J Burn Care Res 2008; 29(1): 141–146
https://doi.org/10.1097/BCR.0b013e31815f3865 pmid: 18182912
25 B Lipový, J Holoubek, M Hanslianová, M Cvanová, L Klein, I Grossová, R Zajíček, P Bukovčan, J Koller, M Baran, P Lengyel, L Eimer, M Jandová, M Košťál, P Brychta, CELESTE Study Group. Toxic epidermal necrolysis data from the CELESTE multinational registry. Part II: specific systemic and local risk factors for the development of infectious complications. Burns 2018; 44(6): 1561–1572
https://doi.org/10.1016/j.burns.2018.03.006 pmid: 29903602
26 SD Imahara, JH Holmes 4th, DM Heimbach, LE Engrav, S Honari, MB Klein, NS Gibran. SCORTEN overestimates mortality in the setting of a standardized treatment protocol. J Burn Care Res 2006; 27(3): 270–275
https://doi.org/10.1097/01.BCR.0000216532.71360.9B pmid: 16679892
27 M Diao, C Thapa, X Ran, Y Ran, X Lv. A retrospective analysis of infections and antibiotic treatment in patients with Stevens-Johnson syndrome and toxic epidermal necrolysis. J Dermatolog Treat 2020; 31(1): 61–65 DOI: 10.1080/09546634.2018.1509047
pmid: 30095319
28 N de Prost, A Mekontso-Dessap, L Valeyrie-Allanore, JT Van Nhieu, TA Duong, O Chosidow, P Wolkenstein, C Brun-Buisson, B Maître. Acute respiratory failure in patients with toxic epidermal necrolysis: clinical features and factors associated with mechanical ventilation. Crit Care Med 2014; 42(1): 118–128
https://doi.org/10.1097/CCM.0b013e31829eb94f pmid: 23989174
29 S Guégan, S Bastuji-Garin, E Poszepczynska-Guigné, JC Roujeau, J Revuz. Performance of the SCORTEN during the first five days of hospitalization to predict the prognosis of epidermal necrolysis. J Invest Dermatol 2006; 126(2): 272–276
https://doi.org/10.1038/sj.jid.5700068 pmid: 16374461
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed