Establishment of a Potential Serum Biomarker Panel for the Diagnosis and Prognosis of Cholangiocarcinoma Using Decision Tree Algorithms
Abstract
:1. Introduction
2. Materials and Methods
2.1. Patients and Serum Samples
2.2. The Detection of Candidate Proteins in Sera by Sandwich ELISA
2.3. The Detection of CA19-9 in Sera by Automated ELECSYS COBAS
2.4. Decision Tree Construction for CCA Biomarkers Panel
- Start with the root node (t = 1).
- Search for a split s* among the set if all possible candidate ’s’ the give the purest decrease in impurity.
- Split node t = 1 into two nodes (t = 2 and t = 3) using the split s*.
- Repeat the split search process, by following the steps 1–3, for the obtained nodes (t = 2 and t = 3) until the tree grows fully or the stopping rules are met.
2.5. Statistical Analysis
3. Results
3.1. The Validation of Candidate Biomarkers in Sera of CCA Patients
3.2. The Correlation between Serum Candidate Biomarkers Level with Clinicopathological Data of CCA Patients
3.3. The Overall Survival Analysis of Candidate Biomarkers in Sera of CCA Patients
3.4. The Combination of Candidate Biomarkers to Establish the Biomarkers Panel for CCA Diagnosis by Logistic Regression Models
3.5. The Predictive Value of Candidate Biomarkers for Diagnosis CCA
3.6. The Diagnostic Accuracy of Candidate Biomarkers in CCA Patients with Low CA19-9 Levels
3.7. The Analysis of Candidate Biomarkers as Potential Prognostic Biomarkers in CCA Patients
3.8. Decision Tree Construction and Their Diagnostic Performance for CCA Biomarkers Panel
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
ACC | accuracy |
ALP | alkaline phosphatase |
AUC | area under the ROC curve |
BBD | benign biliary diseases |
CA19-9 | carbohydrate antigen 19-9 |
CART | Classification and Regression Tree |
CCA | cholangiocarcinoma |
CI | confidence interval |
DT | decision tree |
ECLIA | electrochemiluminescence immunoassay |
ELISA | enzyme-linked immunosorbent assay |
GI | gastrointestinal cancers |
HCC | hepatocellular carcinoma |
LR | likelihood ratio |
MUC5AC | mucin 5AC |
NPV | negative predictive value |
OD | optical density |
OR | odd ratios |
PPV | positive predictive value |
ROC | receiver operating characteristic curve |
S100A9 | S100 calcium binding protein A9 |
SN | sensitivity |
SP | specificity |
TGF-β1 | transforming growth factor β1 |
TMB | tetramethylbenzidine |
YI | Youden index |
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Variables | Normal | Non-CCA | CCA | |||
---|---|---|---|---|---|---|
HCC | CA Gallbladder | CA Pancreas | Liver Metastasis | |||
Total (n) | 40 | 23 | 7 | 5 | 5 | 40 |
Male: Female | 7:33 | 19:4 | 1:6 | 3:2 | 3:2 | 27:13 |
Age (years) | 60 (42–84) | 54 (28–76) | 61 (32–76) | 56 (47–73) | 61 (45–78) | 62 (39–82) |
Subtype | ||||||
iCCA | - | - | - | - | - | 27 |
pCCA | - | - | - | - | - | 12 |
dCCA | - | - | - | - | - | 1 |
CA19-9 (U/mL) | 8.2 | 12.6 | 4 | 9.2 | 7.4 | 351.2 |
(2–29) | (0.6–1000) | (0.6–168) | (0.6–555) | (0.6–1000) | (0.6–1000) | |
CA19-9 > 37 U/mL (%) | 0/40 | 1/23 | 2/7 | 2/5 | 2/5 | 28/40 |
(0%) | (4%) | (29%) | (40%) | (40%) | (70%) |
Variables | S100A9 (ng/mL) | MUC5AC (ng/mL) | Angiopoietin-2 (pg/mL) | TGF-β1 (ng/mL) | CA19-9 (U/mL) | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
OR a | Mean ± S.D. (n) | p Value | ORa | Mean ± S.D. (n) | p Value | OR a | Mean ± S.D. (n) | p Value | OR a | Mean ± S.D. (n) | p Value | OR a | Mean ± S.D. (n) | p Value | |
Age (Year) | |||||||||||||||
<61 | - | 381.95 ± 231 (n = 18) | 0.807 | - | 144.62 ± 108 (n = 18) | 0.17 | - | 2211.14 ± 1320 (n = 18) | 0.634 | - | 41.62 ± 16 (n = 27) | 0.836 | - | 501.67 ± 458 (n = 18) | 0.946 |
≥61 | 1.042 | 397.19 ± 257 (n = 22) | 0.441 | 116.12 ± 121 (n = 22) | 1.667 | 2323.84 ± 2086 (n = 22) | 0.974 | 40.74 ± 16 (n = 29) | 0.571 | 455.28 ± 433 (n = 22) | |||||
Gender | |||||||||||||||
Female | - | 315.75 ± 178 (n = 13) | 0.22 | - | 97.16 ± 56 (n = 13) | 0.479 | - | 2042.81 ± 679 (n = 13) | 0.87 | - | 41.64 ± 15 (n = 18) | 0.88 | - | 357.23 ± 393 (n = 13) | 0.549 |
Male | 1.486 | 426.24 ± 264 (n = 27) | 1.256 | 144.25 ± 133 (n = 27) | 0.686 | 2384.02 ± 2099 (n = 27) | 0.618 | 40.94 ± 32 (n = 38) | 3.59 | 533.41 ± 456 (n = 27) | |||||
Histological types | |||||||||||||||
Non-Papillary | - | 396.62 ± 261 (n = 26) | 1 | - | 128.11 ± 119 (n = 26) | 0.681 | - | 2457.98 ± 2084 (n = 26) | 0.66 | - | 39.08 ± 15 (n = 33) | 0.24 | - | 472.40 ± 435 (n = 26) | 0.967 |
Papillary | 2.133 | 378.66 ± 213 (n = 14) | 1 | 130.50 ± 111 (n = 14) | 0.758 | 1929.81 ± 878 (n = 14) | 1.146 | 44.16 ± 16 (n = 23) | 1.023 | 483.13 ± 463 (n = 14) | |||||
Recurrence | |||||||||||||||
No | - | 382.94 ± 248 (n = 23) | 0.795 | - | 140.03 ± 133 (n = 23) | 0.662 | - | 2294.07 ± 1187 (n = 23) | 0.194 | - | 39.54 ± 13 (n = 34) | 0.342 | - | 494.04 ± 446 (n = 23) | 0.935 |
Yes | 1.75 | 400.33 ± 243 (n = 17) | 0.952 | 113.94 ± 86 (n = 17) | 0.709 | 2244.78 ± 2374 (n = 17) | 1.382 | 43.68 ± 19 (n = 22) | 0.91 | 451.99 ± 443 (n = 17) | |||||
TNM stages | |||||||||||||||
I, II | - | 311.73 ± 173 (n = 9) | 0.377 | - | 104.59 ± 33 (n = 9) | 0.771 | - | 1453.78 ± 820 (n = 9) | 0.020 * | - | 32.65 ± 9 (n = 11) | 0.045 * | - | 507.11 ± 434 (n = 9) | 0.924 |
III, IV | 1.029 | 413.15 ± 258 (n = 31) | 1.667 | 136.02 ± 129 (n = 31) | 4.846 ** | 2510.10 ± 1897 (n = 31) | 5.333 ** | 43.25 ± 16 (n = 45) | 0.505 | 467.17 ± 447 (n = 31) | |||||
Metastasis | |||||||||||||||
No | - | 361.12 ± 251 (n = 17) | 0.436 | - | 96.25 ± 34 (n = 17) | 0.404 | - | 2262.01 ± 2389 (n = 17) | 0.268 | - | 35.30 ± 15 (n = 22) | 0.024 * | - | 462.92 ± 451 (n = 17) | 0.892 |
Yes | 1.31 | 411.93 ± 240 (n = 23) | 1.857 | 153.11 ± 145 (n = 23) | 1.857 | 2281.34 ± 1164 (n = 23) | 3.467 ** | 44.96 ± 15 (n = 34) | 0.723 | 485.93 ± 440 (n = 23) | |||||
Lymph node metastasis | |||||||||||||||
No | - | 388.94 ± 271 (n = 18) | 0.765 | - | 99.57 ± 36 (n = 18) | 0.644 | - | 2218.06 ± 2325 (n = 18) | 0.201 | - | 36.79 ± 15 (n = 25) | 0.062 | - | 437.24 ± 451 (n = 18) | 0.545 |
Yes | 1.042 | 391.47 ± 224 (n = 22) | 1.5 | 152.98 ± 149 (n = 22) | 2.27 | 2318.18 ± 1178 (n = 22) | 3.111 ** | 44.69 ± 16 (n = 31) | 0.865 | 507.99 ± 438 (n = 22) | |||||
Distant metastasis | |||||||||||||||
No | - | 387.51 ± 239 (n = 34) | 0.88 | - | 124.49 ± 117 (n = 34) | 0.225 | - | 2236.04 ± 1816 (n = 34) | 0.544 | - | 40.85 ± 17 (n = 47) | 0.739 | - | 509.19 ± 444 (n = 34) | 0.197 |
Yes | 1.267 | 406.31 ± 290 (n = 6) | 1.2 | 154.20 ± 108 (n = 6) | 2.25 | 2483.27 ± 1550 (n = 6) | 2.827 | 42.79 ± 9 (n = 9) | 0.225 | 288.93 ± 392 (n = 6) |
Group Comparisons | Biomarkers | Cut-Off | AUC (95% CI) | YI | SN | SP | LR | p Value |
---|---|---|---|---|---|---|---|---|
Normal vs. CCA | S100A9 (ng/mL) | >197.9 | 0.888 (0.818–0.958) | 0.7 | 77.5 | 87.5 | 6.2 | <0.0001 |
MUC5AC (ng/mL) | >104.6 | 0.639 (0.517–0.762) | 0.3 | 52.5 | 77.5 | 2.3 | 0.032 | |
TGF-β1 (ng/mL) | >33.42 | 0.649 (0.535–0.762) | 0.3 | 76.8 | 57.5 | 1.8 | 0.013 | |
Angiopoietin-2 (pg/mL) | >2422 | 0.567 (0.439–0.695) | 0.2 | 35 | 87.5 | 2.8 | 0.303 | |
CA19-9 (U/mL) | >23.34 | 0.768 (0.644–0.893) | 0.7 | 72.5 | 97.5 | 29 | <0.0001 | |
Normal vs. Non-CCA | S100A9 (ng/mL) | >197.9 | 0.832 (0.735–0.928) | 0.6 | 72.5 | 87.5 | 5.8 | <0.0001 |
MUC5AC (ng/mL) | >128 | 0.545 (0.417–0.672) | 0.2 | 32.5 | 82.5 | 1.9 | 0.492 | |
TGF-β1 (ng/mL) | >22.81 | 0.618 (0.495–0.741) | 0.2 | 95 | 27.5 | 1.3 | 0.068 | |
Angiopoietin-2 (pg/mL) | <1312 | 0.530 (0.398–0.662) | 0.3 | 42.5 | 82.5 | 2.4 | 0.644 | |
CA19-9 (U/mL) | >23.50 | 0.573 (0.442–0.703) | 0.3 | 32.5 | 97.5 | 13 | 0.264 | |
Non-CCA vs. CCA | S100A9 (ng/mL) | >87.11 | 0.525 (0.398–0.653) | 0.1 | 97.5 | 15 | 1.1 | 0.697 |
MUC5AC (ng/mL) | >90.51 | 0.581 (0.454–0.708) | 0.3 | 65 | 60 | 1.6 | 0.213 | |
TGF-β1 (ng/mL) | >39.98 | 0.551 (0.432–0.671) | 0.2 | 62.5 | 60 | 1.6 | 0.391 | |
Angiopoietin-2 (pg/mL) | >1008 | 0.581 (0.455–0.708) | 0.2 | 90 | 32.5 | 1.3 | 0.211 | |
CA19-9 (U/mL) | >37.39 | 0.716 (0.595–0.837) | 0.5 | 70 | 82.5 | 4 | 0.0009 |
Comparative Diagnosis | Biomarkers | Crude | p Value | Adjusted | p Value |
---|---|---|---|---|---|
OR (95% CI) | OR * (95% CI) | ||||
Normal vs. CCA | S100A9 < 197.9 vs. ≥ 197.9 ng/mL | 24.11 (7.30–79.68) | <0.0001 | 22.50 (5.77–87.82) | <0.0001 |
MUC5AC < 104.6 vs. ≥ 104.6 ng/mL | 3.81 (1.45–10.02) | 0.007 | 3.78 (1.23–11.57) | 0.02 | |
TGF-β1 < 33.42 vs. ≥ 33.42 ng/mL | 3.16 (1.25–7.93) | 0.015 | 2.84 (0.97–8.28) | 0.055 | |
Angiopoietin-2 < 2422 vs. ≥ 2422 pg/mL | 3.77 (1.21–11.79) | 0.023 | 5.17 (1.35–19.78) | 0.016 | |
CA19-9 < 23.34 vs. ≥ 23.34 U/mL | 102.82 (12.56–841.96) | <0.0001 | 129.44 (12.90–1295.60) | <0.0001 | |
Normal vs. Non-CCA | S100A9 < 197.9 vs. ≥ 197.9 ng/mL | 18.46 (5.75–59.23) | <0.0001 | 30.95 (6.79–141.05) | <0.0001 |
MUC5AC < 128 vs. ≥ 128 ng/mL | 2.27 (0.79–6.49) | 0.126 | 2.08 (0.63–6.88) | 0.23 | |
TGF-β1 < 22.81 vs. ≥ 22.81 ng/mL | 7.21 (1.48–35.06) | 0.014 | 4.98 (0.91–27.31) | 0.064 | |
Angiopoietin-2 > 1312 vs. ≤ 1312 pg/mL | 3.48 (1.25–9.75) | 0.017 | 1.30 (0.36–4.72) | 0.694 | |
CA19-9 < 23.50 vs. ≥ 23.50 U/mL | 18.78 (2.32–152.16) | 0.006 | 40.13 (4.17–385.64) | 0.001 | |
Non-CCA vs. CCA | S100A9 < 87.11 vs. ≥ 87.11 ng/mL | 6.88 (0.79–60.06) | 0.081 | 8.04 (0.87–74.47) | 0.066 |
MUC5AC < 90.51 vs. ≥ 90.51 ng/mL | 2.79 (1.13–6.90) | 0.027 | 3.26 (1.25–8.52) | 0.016 | |
TGF-β1 < 39.98 vs. ≥ 39.98 ng/mL | 1.83 (0.75–4.45) | 1.81 | 0.143 (0.79–5.07) | 2.004 | |
Angiopoietin-2 < 1008 vs. ≥ 1008 pg/mL | 4.33 (1.27–14.78) | 0.019 | 4.78 (1.35–16.96) | 0.015 | |
CA19-9 < 37.39 vs. ≥ 37.39 U/mL | 11 (3.81–31.73) | <0.0001 | 12.7 (4.00–40.31) | <0.0001 |
Parameter | DT I (Normal vs. CCA) | DT II (Normal vs. Non-CCA) | DT III (Non-CCA vs. CCA) |
---|---|---|---|
max_depth | 9 | 9 | 3 |
max_feature | 4 | 1 | 2 |
min_samples_leaf | 3 | 3 | 3 |
min_samples_split | 10 | 14 | 10 |
criterion | ‘gini’ | ‘gini’ | ‘gini’ |
Comparative Diagnosis | Single Biomarkers and DTs | Classification Performance | |||||
---|---|---|---|---|---|---|---|
SN | SP | YI | PPV | NPV | ACC | ||
Normal vs. CCA | S100A9 | 86 | 80 | 0.7 | 86 | 80 | 83 |
MUC5AC | 43 | 90 | 0.3 | 86 | 53 | 63 | |
TGF-β1 | 71 | 60 | 0.3 | 71 | 60 | 67 | |
Angiopoietin-2 | 14 | 100 | 0.1 | 100 | 45 | 50 | |
CA19-9 | 71 | 100 | 0.7 | 100 | 71 | 83 | |
DT I: CA19-9 and S100A9 | 93 | 80 | 0.7 | 87 | 89 | 88 | |
Normal vs. Non-CCA | S100A9 | 67 | 83 | 0.5 | 80 | 71 | 75 |
MUC5AC | 33 | 67 | 0 | 50 | 50 | 50 | |
TGF-β1 | 100 | 17 | 0.2 | 55 | 100 | 58 | |
Angiopoietin-2 | 50 | 83 | 0.3 | 75 | 63 | 67 | |
CA19-9 | 33 | 92 | 0.3 | 80 | 58 | 63 | |
DT II: angiopoietin-2, TGF-β1, and S100A9 | 92 | 67 | 0.6 | 73 | 89 | 79 | |
Non-CCA vs. CCA | S100A9 | 100 | 23 | 0.2 | 52 | 100 | 58 |
MUC5AC | 91 | 54 | 0.5 | 63 | 88 | 71 | |
TGF-β1 | 36 | 54 | 0 | 40 | 50 | 46 | |
Angiopoietin-2 | 82 | 62 | 0.4 | 64 | 80 | 71 | |
CA19-9 | 73 | 100 | 0.7 | 100 | 81 | 88 | |
DT III: TGF-β1, CA19-9, angiopoietin-2, and MUC5AC | 82 | 92 | 0.7 | 90 | 86 | 88 |
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Kimawaha, P.; Jusakul, A.; Junsawang, P.; Thanan, R.; Titapun, A.; Khuntikeo, N.; Techasen, A. Establishment of a Potential Serum Biomarker Panel for the Diagnosis and Prognosis of Cholangiocarcinoma Using Decision Tree Algorithms. Diagnostics 2021, 11, 589. https://doi.org/10.3390/diagnostics11040589
Kimawaha P, Jusakul A, Junsawang P, Thanan R, Titapun A, Khuntikeo N, Techasen A. Establishment of a Potential Serum Biomarker Panel for the Diagnosis and Prognosis of Cholangiocarcinoma Using Decision Tree Algorithms. Diagnostics. 2021; 11(4):589. https://doi.org/10.3390/diagnostics11040589
Chicago/Turabian StyleKimawaha, Phongsaran, Apinya Jusakul, Prem Junsawang, Raynoo Thanan, Attapol Titapun, Narong Khuntikeo, and Anchalee Techasen. 2021. "Establishment of a Potential Serum Biomarker Panel for the Diagnosis and Prognosis of Cholangiocarcinoma Using Decision Tree Algorithms" Diagnostics 11, no. 4: 589. https://doi.org/10.3390/diagnostics11040589