| Literature DB >> 28211504 |
Kwangwoo Nam1, Dae Wook Hwang2, Ju Hyun Shim3, Tae Jun Song3, Sang Soo Lee3, Dong-Wan Seo3, Sung Koo Lee3, Myung-Hwan Kim3, Ki-Hun Kim4, Shin Hwang4, Kwang-Min Park2, Young-Joo Lee2, Minkyu Han5, Do Hyun Park3.
Abstract
Surgical resection is the treatment of choice for intrahepatic cholangiocarcinoma (IHCC). However, discrepancies between preoperative workup and intraoperative findings can occur, resulting in unexpected and unfavorable surgical outcomes. The aim of this study was to develop a feasible preoperative nomogram to predict futile resection of IHCC. A total of 718 patients who underwent curative-intent surgery for IHCC between January 2005 and December 2014 were included. The patients were divided into a training cohort (2005-2010, n = 377) and validation cohort (2011-2014, n = 341). The predictive accuracy and discriminative ability of the nomogram were determined by the concordance index and calibration curves. In multivariate analysis of the training cohort, tumor number, lymph node enlargement, presence of intrahepatic duct stones, and elevated neutrophil-to-lymphocyte ratio (NLR) (≥2.7) were independently correlated with the risk of futile resection. The predictive nomogram was established based on these factors. The concordance index of the nomogram for the training and the validation cohorts was 0.847 and 0.740, respectively. In this nomogram, the negative predictive value (128 points, probability of futile resection of 36%) in the validation cohort was 93.3%. In conclusion, our novel preoperatively applicable nomogram is a feasible method to predict futile resection of IHCC in curative-intent surgery.Entities:
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Year: 2017 PMID: 28211504 PMCID: PMC5314340 DOI: 10.1038/srep42954
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Clinical characteristics of the training and validation cohort.
| Variables | Training cohort | Validation cohort | |||
|---|---|---|---|---|---|
| (n = 377) | (n = 341) | ||||
| Age, median (IQR) | 60 (53–66) | 62 (56–69) | 0.005 | ||
| Gender, male | 260 | 69.0% | 222 | 65.1% | 0.271 |
| BMI, kg/m2, median (IQR) | 23.3 (21.6–25.4) | 23.7 (21.9–25.6) | 0.159 | ||
| Diabetes | 97 | 25.7% | 65 | 19.1% | 0.033 |
| Hypertension | 113 | 30.0% | 129 | 37.8% | 0.026 |
| Metabolic syndrome | 19 | 5.0% | 5 | 1.5% | 0.008 |
| Underlying liver condition | |||||
| Hepatitis B | 70 | 18.6% | 73 | 21.4% | 0.341 |
| Hepatitis C | 8 | 2.2% | 4 | 1.2% | 0.301 |
| Alcohol consumption | 83 | 22.0% | 100 | 29.3% | 0.025 |
| Liver cirrhosis | 30 | 8.0% | 50 | 14.7% | 0.004 |
| Fatty liver disease | 10 | 2.7% | 5 | 1.5% | 0.267 |
| IHD stones | 30 | 8.0% | 21 | 6.2% | 0.349 |
| Clonorchiasis infestation | 61 | 16.2% | 34 | 10.0% | 0.014 |
| PSC | 1 | 0.3% | 0 | 0% | 1.000 |
| Tumor size, cm, median (IQR) | 5.0 (3.3–7.5) | 4.5 (3.2–6.5) | 0.138 | ||
| Tumor location | 0.500 | ||||
| Right lobe | 168 | 44.6% | 164 | 48.1% | |
| Left lobe | 179 | 47.5% | 147 | 43.1% | |
| Both lobe (central) | 30 | 8.0% | 30 | 8.8% | |
| Tumor number, ≥2 | 45 | 11.9% | 47 | 13.8% | 0.460 |
| Vascular invasion | 89 | 23.6% | 90 | 26.4% | 0.389 |
| Lymph node enlargement | 134 | 35.5% | 107 | 31.4% | 0.238 |
| Laboratory data, median (IQR) | |||||
| Neutrophil, % | 60.8 (53.1–69) | 58.9 (51.5–66.3) | 0.009 | ||
| Lymphocyte, % | 27.6 (19.7–34.3) | 29.0 (22.4–36.5) | 0.004 | ||
| Platelet, 103/uL | 232 (185–290) | 216 (171–271) | 0.005 | ||
| Albumin, g/dL | 3.7 (3.4–4) | 3.7 (3.4–4) | 0.295 | ||
| CRP, mg/dL | 0.2 (0–0.9) | 0.2 (0–0.9) | 0.898 | ||
| AST, U/L | 26 (22–37) | 27 (21–34.5) | 0.851 | ||
| ALT, U/L | 22 (16–35) | 23 (16–37) | 0.510 | ||
| ALP, IU/L | 110 (80.5–165) | 96 (70–154) | 0.005 | ||
| GGT, IU/L | 69 (34–155) | 67 (31–158) | 0.847 | ||
| Total bilirubin, mg/dL | 0.8 (0.6–1) | 0.6 (0.5–0.9) | <0.001 | ||
| Direct bilirubin, mg/dL | 0.2 (0.2–0.3) | 0.2 (0.2–0.3) | 0.898 | ||
| CEA, ug/L | 1.9 (1–5) | 2.8 (1.7–4.9) | <0.001 | ||
| CA-19-9, U/L | 32.5 (8.2–202.5) | 38.1 (10.5–340.3) | 0.106 | ||
| NLR, median (IQR) | 2.2 (1.6–3.6) | 2.0 (1.4–3) | 0.005 | ||
| Surgical outcome | 0.075 | ||||
| R0 | 239 | 63.4% | 241 | 70.7% | |
| R1 | 77 | 20.4% | 62 | 18.2% | |
| R2 | 61 | 16.2% | 38 | 11.1% | |
| Postoperative complication | 43 | 11.4% | 31 | 9.1% | 0.308 |
| Biloma, bile leakage, stricture | 11 | 5 | |||
| Wound dehiscence | 10 | 2 | |||
| Complicated fluid collection | 6 | 10 | |||
| Infection, abscess | 6 | 8 | |||
| Postoperative bleeding | 5 | 4 | |||
| Postoperative adhesion | 2 | ||||
| Bowel perforation | 1 | ||||
| Portal vein stenosis | 1 | ||||
| Pulmonary thromboembolism | 1 | ||||
| Respiratory failure | 1 | ||||
| Acute liver failure | 1 | ||||
| Status | <0.001 | ||||
| Alive | 95 | 25.2% | 166 | 48.7% | |
| Dead | 282 | 74.8% | 175 | 51.3% | |
ALP, alkaline phosphatase; ALT, alanine aminotransaminase; AST, aspartate aminotransferase; BMI, body mass index; CA-19-9, carcinohydrate antigen 19-9; CEA, carcinoembryonic antigen; CRP, C-reactive protein; GGT, gamma-glutamyl transpeptidase; IQR, interquartile range; NLR, neutrophil-to-lymphocyte ratio; PSC, primary sclerosing cholangitis; SD, standard deviation.
Univariate and multivariate analysis of the training cohort.
| Variables | Univariate analysis | Multivariate analysis | ||||
|---|---|---|---|---|---|---|
| OR | 95% CI | OR | 95% CI | |||
| Age, ≥65 | 0.841 | 0.453–1.508 | 0.571 | |||
| Gender, male | 1.430 | 0.799–2.515 | 0.220 | |||
| BMI, ≥25 kg/m2 | 0.770 | 0.398–1.418 | 0.417 | |||
| Metabolic syndrome | 1.926 | 0.603–5.260 | 0.226 | |||
| Alcohol consumption | 1.321 | 0.687–2.443 | 0.387 | |||
| Liver cirrhosis | 0.783 | 0.225–2.105 | 0.660 | |||
| Fatty liver disease | 1.305 | 0.194–5.368 | 0.740 | |||
| Clonorchiasis infestation | 0.506 | 0.136–1.802 | 0.290 | |||
| Tumor size, ≥5.0 cm | 1.075 | 0.991–1.163 | 0.074 | |||
| AST | 1.002 | 0.993–1.010 | 0.704 | |||
| ALT | 1.006 | 0.997–1.013 | 0.171 | |||
| Total bilirubin | 1.141 | 0.839–1.503 | 0.336 | |||
| Albumin, <3.5 | 1.691 | 0.953–2.965 | 0.069 | |||
| CRP, ≥1.0 | 1.419 | 0.756–2.577 | 0.261 | |||
ALP, alkaline phosphatase; ALT, alanine aminotransaminase; AST, aspartate aminotransferase; BMI, body mass index; CA-19-9, carcinohydrate antigen, CI, confidence interval; CRP, C-reactive protein; IHD, intrahepatic duct; LN, lymph node; NLR, neutrophil-to-lymphocyte ratio; OR, odds ratio.
Figure 1Nomogram for futile resection of intrahepatic cholangiocarcinoma in curative-intent surgery.
LN, lymph node; NLR, neutrophil-to-lymphocyte ratio; IHD, intrahepatic duct.
Figure 2Discrimination and validation of nomogram.
The area under the curve of the nomogram was 0.847 in the training cohort (linear line), and 0.740 in the validation cohort (dotted line).
Figure 3Proposed algorithm of the optimal cutoff for curative-intent surgery of intrahepatic cholangiocarcinoma.
EUS-FNA, endoscopic ultrasound-guided fine needle aspiration.