Sin-Ho Jung

Overview:

Design of Clinical Trials
Survival Analysis
Longitudinal Data Analysis
Clustered Data Analysis
ROC Curve Analysis
Design and Analysis of Microarray Studies

Positions:

Professor of Biostatistics and Bioinformatics

Biostatistics & Bioinformatics
School of Medicine

Member of the Duke Cancer Institute

Duke Cancer Institute
School of Medicine

Education:

Ph.D. 1992

University of Wisconsin - Madison

Grants:

Role of the tumor NLRP3 inflammasome in the generation of anti-PD-1 antibody immunotherapy-associated toxicities

Administered By
Medicine, Medical Oncology
Awarded By
National Institutes of Health
Role
Biostatistician
Start Date
End Date

Alliance NCORP Research Base - Clinical Trials - CALGB 70807

Administered By
Duke Cancer Institute
Awarded By
Mayo Clinic
Role
Principal Investigator
Start Date
End Date

ETIOLOGY OF COPD AMONG CONSTRUCTION WORKERS

Administered By
Family Medicine & Community Health,Occupational & Environmental Medicine
Awarded By
National Institute for Occupational Safety and Health
Role
Biostatistician
Start Date
End Date

Publications:

Phase II trial of galiximab (anti-CD80 monoclonal antibody) plus rituximab (CALGB 50402): Follicular Lymphoma International Prognostic Index (FLIPI) score is predictive of upfront immunotherapy responsiveness.

Authors
Czuczman, MS; Leonard, JP; Jung, S; Johnson, JL; Hsi, ED; Byrd, JC; Cheson, BD
URI
https://scholars.duke.edu/individual/pub1373444
PMID
29390097
Source
pubmed
Published In
Ann Oncol
Volume
29
Published Date
Start Page
2271
DOI
10.1093/annonc/mdx812

Blocking the double-lumen orifice versus apneic oxygenation during 1-lung ventilation.

Authors
Jung, DM; Ahn, HJ; Jung, S-H; Yang, M; Kim, JA; Shin, SM; Jeon, S
MLA Citation
Jung, Dae Myung, et al. “Blocking the double-lumen orifice versus apneic oxygenation during 1-lung ventilation.J Thorac Cardiovasc Surg, vol. 154, no. 6, Dec. 2017, pp. 2122–23. Pubmed, doi:10.1016/j.jtcvs.2017.07.072.
URI
https://scholars.duke.edu/individual/pub1488847
PMID
29132897
Source
pubmed
Published In
The Journal of Thoracic and Cardiovascular Surgery
Volume
154
Published Date
Start Page
2122
End Page
2123
DOI
10.1016/j.jtcvs.2017.07.072

A prediction model for advanced colorectal neoplasia in an asymptomatic screening population.

BACKGROUND: An electronic medical record (EMR) database of a large unselected population who received screening colonoscopies may minimize sampling error and represent real-world estimates of risk for screening target lesions of advanced colorectal neoplasia (CRN). Our aim was to develop and validate a prediction model for assessing the probability of advanced CRN using a clinical data warehouse. METHODS: A total of 49,450 screenees underwent their first colonoscopy as part of a health check-up from 2002 to 2012 at Samsung Medical Center, and the dataset was constructed by means of natural language processing from the computerized EMR system. The screenees were randomized into training and validation sets. The prediction model was developed using logistic regression. The model performance was validated and compared with existing models using area under receiver operating curve (AUC) analysis. RESULTS: In the training set, age, gender, smoking duration, drinking frequency, and aspirin use were identified as independent predictors for advanced CRN (adjusted P < .01). The developed model had good discrimination (AUC = 0.726) and was internally validated (AUC = 0.713). The high-risk group had a 3.7-fold increased risk of advanced CRN compared to the low-risk group (1.1% vs. 4.0%, P < .001). The discrimination performance of the present model for high-risk patients with advanced CRN was better than that of the Asia-Pacific Colorectal Screening score (AUC = 0.678, P < .001) and Schroy's CAN index (AUC = 0.672, P < .001). CONCLUSION: The present 5-item risk model can be calculated readily using a simple questionnaire and can identify the low- and high-risk groups of advanced CRN at the first screening colonoscopy. This model may increase colorectal cancer risk awareness and assist healthcare providers in encouraging the high-risk group to undergo a colonoscopy.
Authors
Hong, SN; Son, HJ; Choi, SK; Chang, DK; Kim, Y-H; Jung, S-H; Rhee, P-L
MLA Citation
Hong, Sung Noh, et al. “A prediction model for advanced colorectal neoplasia in an asymptomatic screening population.Plos One, vol. 12, no. 8, 2017, p. e0181040. Pubmed, doi:10.1371/journal.pone.0181040.
URI
https://scholars.duke.edu/individual/pub1276430
PMID
28841657
Source
pubmed
Published In
Plos One
Volume
12
Published Date
Start Page
e0181040
DOI
10.1371/journal.pone.0181040

Longitudinal monitoring of EGFR mutations in plasma predicts outcomes of NSCLC patients treated with EGFR TKIs: Korean Lung Cancer Consortium (KLCC-12-02).

We hypothesized that plasma-based EGFR mutation analysis for NSCLC may be feasible for monitoring treatment response to EGFR TKIs and also predict drug resistance.Clinically relevant mutations including exon 19 deletion (ex19del), L858R and T790M were analyzed using droplet digital PCR (ddPCR) in longitudinally collected plasma samples (n = 367) from 81 NSCLC patients treated with EGFR TKI. Of a total 58 baseline cell-free DNA (cfDNA) samples available for ddPCR analysis, 43 (74.1%) had the same mutation in the matched tumors (clinical sensitivity: 70.8% [17/24] for L858R and 76.5% [26/34] for ex19del). The concordance rates of plasma with tissue-based results of EGFR mutations were 87.9% for L858R and 86.2% for ex19del. All 40 patients who were detected EGFR mutations at baseline showed a dramatic decrease of mutant copies (>50%) in plasma during the first two months after treatment. Median progression-free survival (PFS) was 10.1 months for patients with undetectable EGFR v 6.3 months for detectable EGFR mutations in blood after two-month treatment (HR 3.88, 95% CI 1.48-10.19, P = 0.006). We observed emerging resistance with early detection of T790M as a secondary mutation in 14 (28.6%) of 49 patients. Plasma-based EGFR mutation analysis using ddPCR can monitor treatment response to EGFR TKIs and can lead to early detection of EGFR TKIs resistance. Further studies confirming clinical implications of EGFR mutation in plasma are warranted to guide optimal therapeutic strategies upon knowledge of treatment response and resistance.
Authors
Lee, JY; Qing, X; Xiumin, W; Yali, B; Chi, S; Bak, SH; Lee, HY; Sun, J-M; Lee, S-H; Ahn, JS; Cho, EK; Kim, D-W; Kim, HR; Min, YJ; Jung, S-H; Park, K; Mao, M; Ahn, M-J
MLA Citation
Lee, Ji Yun, et al. “Longitudinal monitoring of EGFR mutations in plasma predicts outcomes of NSCLC patients treated with EGFR TKIs: Korean Lung Cancer Consortium (KLCC-12-02).Oncotarget, vol. 7, no. 6, Feb. 2016, pp. 6984–93. Pubmed, doi:10.18632/oncotarget.6874.
URI
https://scholars.duke.edu/individual/pub1165804
PMID
26755650
Source
pubmed
Published In
Oncotarget
Volume
7
Published Date
Start Page
6984
End Page
6993
DOI
10.18632/oncotarget.6874

Development and external validation of nomograms predictive of response to radiation therapy and overall survival in nasopharyngeal cancer patients.

INTRODUCTION: Large variability in the clinical outcomes has been observed among the nasopharyngeal cancer (NPC) patients with the same stage receiving similar treatment. This suggests that the current Tumour-Node-Metastasis staging systems need to be refined. The nomogram is a useful predictive tool that integrates individual variables into a statistical model to predict outcome of interest. This study was to design predictive nomograms based on the clinical and pathological features of patients with NPC. MATERIALS AND METHODS: Clinical data of 270 NPC patients who underwent definitive radiation therapy (RT) alone or concurrent with chemotherapy were collected. Factors predictive of response to RT and overall survival (OS) were determined by univariate and multivariate analyses, and predictive nomograms were created. Nomograms were validated externally by assessing discrimination and calibration using an independent data set (N=122). RESULTS: Three variables predictive of response to RT (age, histology classification and N classification) and four predictive of OS (age, performance status, smoking status and N classification), in addition to T classification, were extracted to generate the nomograms. The nomograms were validated externally, which showed perfect correlation with each other. CONCLUSION: The designed nomograms proved highly predictive of response to RT and OS in individual patients, and could facilitate individualised and personalised patients' counselling and care.
Authors
Cho, J-K; Lee, G-J; Yi, K-I; Cho, K-S; Choi, N; Kim, JS; Kim, H; Oh, D; Choi, S-K; Jung, S-H; Jeong, H-S; Ahn, YC
MLA Citation
Cho, Jae-Keun, et al. “Development and external validation of nomograms predictive of response to radiation therapy and overall survival in nasopharyngeal cancer patients.Eur J Cancer, vol. 51, no. 10, July 2015, pp. 1303–11. Pubmed, doi:10.1016/j.ejca.2015.04.003.
URI
https://scholars.duke.edu/individual/pub1102855
PMID
25934438
Source
pubmed
Published In
Eur J Cancer
Volume
51
Published Date
Start Page
1303
End Page
1311
DOI
10.1016/j.ejca.2015.04.003