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Aging and disease    2017, Vol. 0 Issue (0000) : 0-     DOI: 10.14336/AD.2017.1016
Original Article |
Prognostic Nomogram Associated with Longer Survival in Amyotrophic Lateral Sclerosis Patients
Qian-Qian Wei, Yongping Chen, Xueping Chen, Bei Cao, RuWei Ou, Lingyu Zhang, Yanbing Hou, Huifang Shang
Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
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Abstract  

Better understanding of survival factors in amyotrophic lateral sclerosis (ALS) could help physicians and patients schedule therapeutic interventions. We conducted a study to evaluate the predictive factors associated with longer survival and construct prognostic nomogram in ALS patients. A total of 553 ALS patients were enrolled and divided into 2 groups: a training set and a validation set. Risk factors for survival were identified using logistic regression analysis, and a nomogram created by R program was performed to predict the probability of longer survival in the training set; then receiver operating characteristic (ROC) analysis was applied to assess predictive value of the nomogram model. The median survival time was 3.2 years for all patients. Multivariate analyses revealed that age of onset, rate of disease progression, hemoglobin A1c (HbA1c) level, body mass index, creatinine, creatine kinase (CK), and non-invasive positive pressure ventilation (NIPPV) were independent predictors of longer survival. A nomogram based on the above seven predictive factors was developed to predict the possibility of longer survival. The ROC curve of the nomogram demonstrated good discrimination ability with an AUC of 0.92 (95% CI: 0.88-0.96) in the validation set. In ALS, serum CK, creatinine and HbA1c levels at baseline were independent biomarkers of longer survival. The prognostic nomogram model that integrated all significant independent factors for those who survived longer than 3 years provides an effective way to predict the probability of longer survival and can help doctors evaluate the disease progression and give personalized treatment recommendations.

Keywords Amyotrophic lateral sclerosis      biomarkers      HbA1c      CK      creatinine      Nomogram     
Issue Date: 07 December 2018
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Articles by authors
Qian-Qian Wei
Yongping Chen
Xueping Chen
Bei Cao
RuWei Ou
Lingyu Zhang
Yanbing Hou
Huifang Shang
Cite this article:   
Qian-Qian Wei,Yongping Chen,Xueping Chen, et al. Prognostic Nomogram Associated with Longer Survival in Amyotrophic Lateral Sclerosis Patients[J]. Aging and disease, 2017, 0(0000): 0-.
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http://www.aginganddisease.org/EN/10.14336/AD.2017.1016     OR     http://www.aginganddisease.org/EN/Y2017/V0/I0000/0
FactorsTraining setValidation setP*
Event 3 (-)
N = 178
Event 3 (+)
N = 209
Total
N = 387
PEvent 3 (-)
N = 70
Event 3 (+)
N =96
Total
N = 166
P
Age of onset, years0.001*0.004*0.287
<4014 (7.9)34 (16.3)48 (12.4)5 (5.1)24 (25.0)29 (17.5)
40-4515 (8.4)36 (17.2)51 (13.2)4 (5.7)14 (14.6)18 (10.8)
45-5016 (9.0)21 (10.0)37 (9.6)3 (4.3)5 (5.2)8 (4.8)
50-5512 (6.7)15 (7.2)27 (7.0)8 (11.4)9 (9.4)17 (10.2)
55-6036 (20.2)45 (21.5)81 (20.9)13 (18.6)18 (18.8)31 (18.7)
60-6535 (19.7)32 (15.3)67 (17.3)16 (22.9)15 (15.6)31 (18.7)
65-7022 (12.4)14 (6.7)36 (9.3)10 (14.3)8 (8.3)18 (10.8)
>7028 (15.7)12 (5.7)40 (10.3)11 (15.7)3 (3.1)14 (8.4)
ALSFRS-R0.003*0.002*0.399
≥4076 (42.7)121 (57.9)197 (50.9)23 (32.9)55 (57.3)78 (47.0)
<40102 (57.3)88 (42.1)190 (49.1)47 (67.1)41 (42.7)88 (53.0)
Disease duration<0.001*<0.001*0.355
≥12 months61 (34.3)151 (72.2)212 (54.8)29 (41.4)69 (71.9)98 (59.0)
<12 months117 (65.7)58 (27.8)175 (45.2)41 (58.6)27 (28.1)68 (41.0)
Disease delay<0.001*0.001*0.285
≥12 months57 (32.0)143 (68.4)200 (51.7)29 (41.4)65 (67.7)94 (56.6)
<12 months121 (68.0)66 (31.6)187 (48.3)41 (58.6)31 (32.3)72 (43.4)
Disease progression<0.001*<0.001*0.991
<0.530 (16.9)121 (57.9)151 (39.0)8 (11.4)53 (55.2)61 (36.7)
0.5-1.066 (37.1)71 (34.0)137 (35.4)26 (37.1)33 (34.4)59 (35.5)
1.0-1.532 (18.0)13 (6.2)45 (11.6)14 (20.0)7 (7.3)21 (12.7)
1.5-2.025 (14.0)4 (1.9)29 (7.5)10 (14.3)3 (3.1)13 (7.8)
2.0-2.510 (5.6)0 (0.0)10 (2.6)4 (5.7)0 (0.0)4 (2.4)
>2.515 (8.4)0 (0.0)15 (3.9)8 (11.4)0 (0.0)8 (4.8)
HbA1c<0.001*<0.001*0.994
<5.016 (9.0)19 (9.1)35 (9.0)4 (5.7)10 (10.4)14 (8.4)
5.0-5.554 (30.3)107 (51.2)161 (41.6)18 (25.7)54 (56.2)72 (43.4)
5.5-6.058 (32.6)55 (26.3)113 (29.2)23 (32.9)25 (26.0)48 (28.9)
6.0-6.530 (16.9)20 (9.6)50 (12.9)14 (20.0)6 (6.2)20 (12.0)
6.5-7.010 (5.6)4 (1.9)14 (3.6)5 (7.1)0 (0.0)5 (3.0)
>7.010 (5.6)4 (1.9)14 (3.6)6 (8.6)1 (1.0)7 (4.2)
BMI<0.001*<0.001*0.088
<1814 (7.9)11 (5.3)25 (6.5)5 (7.1)5 (5.2)10 (6.0)
18-2053 (29.8)25 (12.0)78 (20.2)17 (24.3)7 (7.3)24 (14.5)
20-2265 (36.5)29 (13.9)94 (24.3)35 (50.0)12 (12.5)47 (28.3)
22-2416 (9.0)73 (34.9)89 (23.0)4 (5.7)37 (38.5)41 (24.7)
24-2621 (11.8)45 (21.5)66 (17.1)4 (5.7)21 (21.9)25 (15.1)
26-281 (0.6)2 (1.0)3 (8.3)0 (0.0)7 (7.3)7 (4.2)
>288 (4.5)24 (11.5)32 (8.3)5 (7.1)7 (7.3)12 (7.2)
Creatinine0.0510.0570.879
<4017 (9.6)9 (4.3)26 (6.7)7 (10.0)3 (3.1)10 (6.0)
40-6081 (45.5)84 (40.2)165 (42.6)31 (44.3)36 (37.5)67 (40.4)
60-8059 (33.1)93 (44.5)152 (39.3)25 (35.7)35 (36.5)60 (37.7)
>8021 (11.8)23 (11.0)44 (11.4)7 (10.0)22 (22.9)22 (22.9)
CK0.0580.003*0.592
<5022 (12.4)15 (7.2)37 (9.6)8 (11.4)6 (6.2)14 (8.4)
50-10054 (30.3)53 (25.4)107 (27.6)26 (37.1)20 (20.8)46 (27.7)
100-24078 (43.8)95 (45.5)173 (44.7)29 (41.4)39 (42.0)68 (41.0)
>24024 (13.5)46 (22.0)70 (18.1)7 (10.0)32 (32.3)38 (22.9)
Uric acid0.0730.0550.352
<22029 (16.3)39 (18.7)68 (17.6)8 (11.4)12 (12.5)20 (12.0)
220-30071 (39.9)65 (31.1)136 (35.1)34 (48.6)33 (34.4)67 (40.4)
300-38052 (29.2)55 (26.3)107 (27.6)20 (28.6)24 (25.0)44 (26.5)
>38026 (14.6)50 (23.9)76 (19.6)8 (11.4)27 (28.1)35 (21.1)
Total bilirubin0.034*0.001*0.730
<9.041 (23.0)54 (25.8)95 (24.5)17 (24.3)24 (25.0)41 (24.7)
9.0-11.554 (30.3)48 (23.0)102 (26.4)21 (30.0)19 (19.8)40 (24.1)
11.5-15.049 (27.5)44 (21.1)93 (24.0)26 (37.1)21 (21.9)47 (28.3)
>15.034 (19.1)63 (30.1)97 (25.1)6 (8.6)32 (33.3)38 (22.9)
TP0.031*0.0940.194
<6025 (14.0)15 (7.2)40 (10.3)9 (12.9)4 (4.2)13 (7.8)
60-6544 (24.7)74 (35.4)118 (30.5)18 (25.7)28 (29.2)46 (27.7)
65-7063 (35.4)63 (30.1)126 (32.6)23 (32.9)25 (26.0)48 (28.9)
>7046 (25.8)57 (27.3)103 (26.6)20 (28.6)39 (40.6)59 (35.5)
Hypoproteinemia0.027*0.024*0.803
Yes25 (14.0)15 (7.2)40 (10.3)11 (15.7)5 (5.2)16 (9.6)
No153 (86.0)194 (92.8)347 (89.7)59 (84.3)91 (94.8)150 (90.4)
NIPPV0.048*0.044*0.002*
Yes9 (5.1)22 (10.5)31 (8.0)7 (10.0)21 (21.9)28 (16.9)
No169 (94.9)187 (89.5)356 (92.0)63 (90.0)75 (78.1)138 (83.1)
Table 1  Demographic and disease-related characteristics of the ALS patients related to survival time. N (%)
FactorsUnivariate analysisMultivariate analysis
OR (95%CI)P-valueOR (95%CI)P-value
Age of onset0.793 (0.720-0.873)<0.0010.816 (0.723-0.920)0.001
Disease progression0.310 (0.234-0.410)<0.0010.293 (0.214-0.400)<0.001
HbA1c0.773 (0.646-0.925)0.0050.792 (0.631-0.993)0.044
BMI1.574 (1.353-1.831)<0.0011.565 (1.297-1.888)<0.001
Creatinine1.282 (0.989-1.662)0.0601.470 (1.041-2.075)0.029
CK1.376 (1.088-1.739)0.0081.443 (1.065-1.956)0.018
Uric1.144 (0.936-1.400)0.189--
Total bilirubin1.109 (0.926-1.327)0.260--
TP1.050 (0.853-1.292)0.648--
Hypoproteinemia0.473 (0.241-0.929)0.030--
NIPPV2.209 (0.990-4.931)0.0534.094 (1.300-12.891)0.016
Table 2  Logistic regression analysis of the associated factors of longer survival (beyond 3 years) in ALS patients.
Figure 1.  A nomogram composed of all independent factors to predict the probability of longer survival in ALS patients. The probability of longer survival in ALS is calculated by drawing a line to the point on the axis for each of the following variables: age, BMI, rate of disease progression, HbA1c, CK, creatinine, and NIPPV. The points for each variable are summed and located on the total point line. Next, a vertical line is projected from the total point line to the predicted probability bottom scale to obtain the individual probability of longer survival.
Figure 2.  Predictive accuracy of the nomogram model. A receiver operating characteristics (ROC) curve of the multivariate logistic regression model for predicting longer survival in ALS patients, which had an AUC of 0.92 (95% CI: 0.88-0.96) in the validation set, implying a good concordance and a reliable ability.
Figure 3.  Examples for Nomogram. A) Nomogram of 3 years survival for a patient with an onset age at 48, a BMI value of 23, a disease progression rate of 1.8, an HbA1c value of 5.6, a CK value of 260 IU/L, a creatinine value of 85 µmol/L, and who did not receive NIPPV. B) Nomogram of 3 years survival for a patient with an onset age of 48, a BMI value of 23, a disease progression rate of 1.8, a HbA1c value of 5.6, a CK value of 260 IU/L, a creatinine value of 85 µmol/L, and who received NIPPV.
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