Jin Ho Choi

Dr. Jin Ho Choi

Seoul National University Hospital
orcid

Research Focus & Metrics

Academic Career Length

26Years (2001-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 September 2001 in Comparative Biochemistry and Physiology Part C: Toxicology & Pharmacology
Verified
Journal Article
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JCJin Ho Choi
Jin Ho Choi
HRHélène Roche
Hélène Roche
TCThierry Caquet
Thierry Caquet

1 June 2019 in Cancer Epidemiology, Biomarkers & Prevention
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Journal Article
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YCYoung Hoon Choi
Young Hoon Choi
JLJae Woo Lee
Jae Woo Lee
Sang Hyub LeeSang Hyub Lee
Sang Hyub Lee
JCJin Ho Choi
Jin Ho Choi
JKJinwoo Kang
Jinwoo Kang
YKYong-Tae Kim
Yong-Tae Kim
Background: Monocyte-to-lymphocyte ratio (MLR), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) have been reported to be prognostic markers in various cancers. However, the prognostic value of these inflammatory biomarkers, particularly MLR, in gallbladder cancer remains to be determined. Methods: From 2005 to 2016, 178 patients with histologically confirmed gallbladder adenocarcinoma who underwent palliative chemotherapy were queried in this study. The association between survival and various clinical and laboratory variables, including MLR, NLR, and PLR, was investigated. The optimal cutoff values for MLR, NLR, and PLR were determined using the maxstat package of R. Results: Patients with high MLR (>0.24) were expected to have shorter progression-free survival [PFS; hazard ratio (HR), 2.100; 95% confidence interval (CI), 1.397–3.157; P < 0.001] and overall survival (OS; HR, 2.533; 95% CI, 1.664–3.856; P < 0.001) compared with patients with low MLR (≤0.24). In multivariate Cox model, CA 19-9, stage, and MLR were independent factors for PFS. MLR was also an independent predictor of OS along with PLR, age, and CA 19-9, whereas NLR was not significantly associated with OS. Time-dependent receiver operating characteristic (ROC) analysis showed that the area under the curve of MLR for predicting OS was greater than that of NLR and PLR at most time points. Conclusions: MLR independently predicts survival in gallbladder cancer patients undergoing chemotherapy. Future prospective studies are needed to validate its value as a prognostic biomarker. Impact: MLR is an inexpensive and easily available biomarker for predicting prognosis in patients with gallbladder cancer undergoing chemotherapy.

5 January 2019 in BMC Cancer
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MYMin Su You
Min Su You
JRJi Kon Ryu
Ji Kon Ryu
YCYoung Hoon Choi
Young Hoon Choi
JCJin Ho Choi
Jin Ho Choi
GHGunn Huh
Gunn Huh
YKYong-Tae Kim
Yong-Tae Kim
Gallbladder cancer (GBC) is likely to be diagnosed at progressive stages and shows a very poor prognosis. Combination therapy with gemcitabine and cisplatin (GEMCIS) has been widely used as first-line palliative chemotherapy for advanced GBC. This study was designed to investigate the efficacy of GEMCIS and identify prognostic factors in patients with unresectable GBC. Patients with GBC who were treated with GEMCIS from January 2008 to June 2017 in a single tertiary hospital were included. All cases of GBC were diagnosed by pathologic findings and extent of the tumour was assessed by imaging tests. Combination chemotherapy consisted of cisplatin 25 mg/m2 and gemcitabine 1000 mg/m2 intravenously on days 1 and 8 every 3 weeks. To determine factors affecting prognosis, Kaplan–Meier survival analysis, log-rank test and the Cox proportional hazard regression linear model were used. All variables with P < 0.1 in univariable analysis were included in the multivariable model. A total of 173 patients received a median of 5.3 ± 4.4 cycles of chemotherapy over 3.8 ± 3.9 months. Most of the patients (94.8%) were stage IVB at the time of diagnosis and the most common site of metastasis was the liver (42.8%). Disease control rate was 59.5%: 2 (1.2%) patients with complete response, 26 (15.0%) patients with partial response and 75 (43.4%) patients with stable disease. Overall survival (OS) and progression-free survival were 8.1 (95% confidence interval [CI], 7.1–10.2) and 5.6 (95% CI 4.5–6.8) months, respectively. Multivariable regression model indicated that metastasis to liver (hazard ratio [HR] = 1.63, 95% CI 1.11–2.40; P = 0.013), neutrophil-to-lymphocyte ratio (NLR) ≥3 (HR 1.65, 95% CI 1.09–2.49; P = 0.017), CEA ≥ 5 ng/mL (HR 1.50, 95% CI 1.02–2.19; P = 0.038), and CA19–9 ≥ 500 U/mL (HR 1.59, 95% CI 1.01–2.50; P = 0.043) were significantly associated with OS. GEMCIS demonstrated a high disease control rate in patients with unresectable GBC. Factors independently related to OS were metastasis to liver, NLR ≥ 3, CEA ≥ 5 ng/mL and CA19–9 ≥ 500 U/mL.

14 August 2021 in Journal of Clinical Medicine
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TKTaewan Kim
Taewan Kim
YCYoung Hoon Choi
Young Hoon Choi
JCJin Ho Choi
Jin Ho Choi
Sang Hyub LeeSang Hyub Lee
Sang Hyub Lee
SLSeungchul Lee
Seungchul Lee
ILIn Seok Lee
In Seok Lee
Differential diagnosis of true gallbladder polyps remains a challenging task. This study aimed to differentiate true polyps in ultrasound images using deep learning, especially gallbladder polyps less than 20 mm in size, where clinical distinction is necessary. A total of 501 patients with gallbladder polyp pathology confirmed through cholecystectomy were enrolled from two tertiary hospitals. Abdominal ultrasound images of gallbladder polyps from these patients were analyzed using an ensemble model combining three convolutional neural network (CNN) models and a 5-fold cross-validation. True polyp diagnosis with the ensemble model that learned only using ultrasonography images achieved an area under receiver operating characteristic curve (AUC) of 0.8960 and accuracy of 83.63%. After adding patient age and polyp size information, the diagnostic performance of the ensemble model improved, with a high specificity of 88.35%, AUC of 0.9082, and accuracy of 87.61%, outperforming the individual CNN models constituting the ensemble model. In the subgroup analysis, the ensemble model showed the best performance with AUC of 0.9131 for polyps larger than 10 mm. Our proposed ensemble model that combines three CNN models classifies gallbladder polyps of less than 20 mm in ultrasonography images with high accuracy and can be useful for avoiding unnecessary cholecystectomy with high specificity.

1 May 2018 in United European Gastroenterology Journal
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Journal Article
Open access
KCKwang Hyun Chung
Kwang Hyun Chung
Sang Hyub LeeSang Hyub Lee
Sang Hyub Lee
JCJin Ho Choi
Jin Ho Choi
JKJinwoo Kang
Jinwoo Kang
WPWoo Hyun Paik
Woo Hyun Paik
YKYong-Tae Kim
Yong-Tae Kim
Background: The role of submucosal injection (SI) in endoscopic papillectomy (EP) is controversial.Objective: This study investigated the effects of SI before EP of ampullary tumors.Methods: All patients who underwent initial curative EP at our institution between March 2006 and March 2014 were retrospectively recruited. The presence of residual tumor after three months, recurrence‐free survival and post‐procedural adverse events were compared between the SI group and non‐injection (NI) group. Propensity‐score matching was performed between the two groups to reduce potential selection bias and confounding.Results: A total of 122 patients were included (SI: 26, NI: 96). Following propensity‐score matching, 25 paired patients were selected. Residual tumor was not shown in the NI group, whereas seven (28.0%) patients in the SI group had residual tumor (p = 0.010). The recurrence‐free survival of the NI group was significantly longer than that of the SI group (p = 0.036). Upon multivariate analysis, pathologic grade (p = 0.026) and SI (p = 0.033) were significantly related to recurrence‐free survival. Post‐procedural adverse events were not significantly different between the two groups.Conclusion: SI before EP of ampullary tumor was related to more frequent residual tumor and shorter recurrence‐free survival and did not reduce post‐procedural adverse events.

1 December 2019 in Hepatobiliary & Pancreatic Diseases International
Verified
Journal Article
Closed access
JCJin Ho Choi
Jin Ho Choi
Sang Hyub LeeSang Hyub Lee
Sang Hyub Lee
YCYoung Hoon Choi
Young Hoon Choi
MYMin Su You
Min Su You
BSBang-Sup Shin
Bang-Sup Shin
YKYong-Tae Kim
Yong-Tae Kim