Susan Halabi

Overview:

Design and analysis of clinical trials, statistical analysis of biomarker and high dimensional data, development and validation of prognostic and predictive models.

Positions:

Professor of Biostatistics and Bioinformatics

Biostatistics & Bioinformatics
School of Medicine

Chief, Division of Biostatistics

Biostatistics & Bioinformatics
School of Medicine

Member of the Duke Cancer Institute

Duke Cancer Institute
School of Medicine

Education:

Ph.D. 1994

University of Texas Health Sciences Center, Houston

Grants:

PCRP Clinical Consortium: Duke University Clinical Research Site

Administered By
Medicine, Medical Oncology
Awarded By
Department of Defense
Role
Co Investigator
Start Date
End Date

Developing and Validating Prognostic Models of Clinical Outcomes In Men With Castration Resistant Prostate Cancer

Administered By
Biostatistics & Bioinformatics
Awarded By
National Institutes of Health
Role
Principal Investigator
Start Date
End Date

Surrogate Endpoints of Overall Survival in Men with Metastatic Hormone Sensitive Prostate Cancer

Administered By
Biostatistics & Bioinformatics
Awarded By
Prostate Cancer Foundation
Role
Principal Investigator
Start Date
End Date

Precision Medicine in Platinum-treated Lethal Bladder Cancer

Administered By
Biostatistics & Bioinformatics
Awarded By
Memorial Sloan Kettering Cancer Center
Role
Principal Investigator
Start Date
End Date

Serum Androgens and Survival in CRPC

Administered By
Duke Cancer Institute
Awarded By
University of California - San Francisco
Role
Principal Investigator
Start Date
End Date

Publications:

Palbociclib (P) in patients (Pts) with pancreatic cancer (PC) and gallbladder or bile duct cancer (GBC) with CDKN2A alterations: Results from the Targeted Agent and Profiling Utilization Registry (TAPUR) study.

Authors
Al Baghdadi, T; Halabi, S; Garrett-Mayer, E; Mangat, PK; Ahn, ER; Sahai, V; Alvarez, RH; Kim, ES; Yost, KJ; Guo, K; Rygiel, AL; Antonelli, KR; Butler, NL; Bruinooge, SS; Schilsky, RL
MLA Citation
Al Baghdadi, Tareq, et al. “Palbociclib (P) in patients (Pts) with pancreatic cancer (PC) and gallbladder or bile duct cancer (GBC) with CDKN2A alterations: Results from the Targeted Agent and Profiling Utilization Registry (TAPUR) study.Journal of Clinical Oncology, vol. 36, no. 15_suppl, American Society of Clinical Oncology (ASCO), 2018, pp. 2532–2532. Crossref, doi:10.1200/jco.2018.36.15_suppl.2532.
URI
https://scholars.duke.edu/individual/pub1437060
Source
crossref
Published In
Journal of Clinical Oncology : Official Journal of the American Society of Clinical Oncology
Volume
36
Published Date
Start Page
2532
End Page
2532
DOI
10.1200/jco.2018.36.15_suppl.2532

Comparative Survival of Asian and White Metastatic Castration-Resistant Prostate Cancer Men Treated With Docetaxel.

There are few data regarding disparities in overall survival (OS) between Asian and white men with metastatic castration-resistant prostate cancer (mCRPC). We compared OS of Asian and white mCRPC men treated in phase III clinical trials with docetaxel and prednisone (DP) or a DP-containing regimen. Individual participant data from 8820 men with mCRPC randomly assigned on nine phase III trials to receive DP or a DP-containing regimen were combined. Men enrolled in these trials had a diagnosis of prostate adenocarcinoma. The median overall survival was 18.8 months (95% confidence interval [CI] = 17.4 to 22.1 months) and 21.2 months (95% CI = 20.8 to 21.7 months) for Asian and white men, respectively. The pooled hazard ratio for death for Asian men compared with white men, adjusted for baseline prognostic factors, was 0.95 (95% CI = 0.84 to 1.09), indicating that Asian men were not at increased risk of death. This large analysis showed that Asian men did not have shorter OS duration than white men treated with docetaxel.
Authors
Halabi, S; Dutta, S; Tangen, CM; Rosenthal, M; Petrylak, DP; Thompson, IM; Chi, KN; De Bono, JS; Araujo, JC; Logothetis, C; Eisenberger, MA; Quinn, DI; Fizazi, K; Morris, MJ; Higano, CS; Tannock, IF; Small, EJ; Kelly, WK
MLA Citation
Halabi, Susan, et al. “Comparative Survival of Asian and White Metastatic Castration-Resistant Prostate Cancer Men Treated With Docetaxel.Jnci Cancer Spectr, vol. 4, no. 2, Apr. 2020, p. pkaa003. Pubmed, doi:10.1093/jncics/pkaa003.
URI
https://scholars.duke.edu/individual/pub1439883
PMID
32368717
Source
pubmed
Published In
Jnci Cancer Spectrum
Volume
4
Published Date
Start Page
pkaa003
DOI
10.1093/jncics/pkaa003

a systematic review and recommendation for reporting of surrogate endpoint evaluation using meta-analyses

© The Author(s) 2019. Published by Oxford University Press. Background: Meta-analysis of randomized controlled trials (RCTs) has been widely conducted for the evaluation of surrogate endpoints in oncology, but little attention has been given to the adequacy of reporting and interpretation. This review evaluated the reporting quality of published meta-analyses on surrogacy evaluation and developed recommendations for future reporting. Methods: We searched PubMed through August 2017 to identify studies that evaluated surrogate endpoints using the meta-analyses of RCTs in oncology. Both individual patient data (IPD) and aggregate data (AD) meta-analyses were included for the review. Results: Eighty meta-analyses were identified: 22 used IPD and 58 used AD from multiple RCTs. We observed variability and reporting deficiencies in both IPD and AD meta-analyses, especially on reporting of trial selection, endpoint definition, study and patient characteristics for included RCTs, and important statistical methods and results. Based on these findings, we proposed a checklist and recommendations to improve completeness, consistency, and transparency of reports of meta-analytic surrogacy evaluation. We highlighted key aspects of the design and analysis of surrogate endpoints and presented explanations and rationale why these items should be clearly reported in surrogacy evaluation. Conclusions: Our reporting of surrogate endpoint evaluation using meta-analyses (ReSEEM) guidelines and recommendations will improve the quality in reporting and facilitate the interpretation and reproducibility of meta-analytic surrogacy evaluation. Also, they should help promote greater methodological consistency and could also serve as an evaluation tool in the peer review process for assessing surrogacy research.
Authors
Xie, W; Halabi, S; Tierney, JF; Sydes, MR; Collette, L; Dignam, JJ; Buyse, M; Sweeney, CJ; Regan, MM
MLA Citation
Xie, W., et al. “a systematic review and recommendation for reporting of surrogate endpoint evaluation using meta-analyses.” Jnci Cancer Spectrum, vol. 3, no. 1, Mar. 2019. Scopus, doi:10.1093/jncics/pkz002.
URI
https://scholars.duke.edu/individual/pub1451280
Source
scopus
Published In
Jnci Cancer Spectrum
Volume
3
Published Date
DOI
10.1093/jncics/pkz002

Use of pain at baseline and pain progression to predict overall survival (OS) in patients (pts) with docetaxel pretreated metastatic castration-refractory prostate cancer (CRPC): Results from the SPARC trial

Authors
Sartor, AO; Petrylak, D; Sternberg, C; Witjes, F; Halabi, S; Berry, W; Petrone, M; McKearn, T; Noursalehi, M; George, M
URI
https://scholars.duke.edu/individual/pub1450916
Source
wos-lite
Published In
Journal of Clinical Oncology : Official Journal of the American Society of Clinical Oncology
Volume
27
Published Date

Score and deviance residuals based on the full likelihood approach in survival analysis.

Assuming the proportional hazards model and non-informative censoring, the full likelihood approach is used to obtain two new residuals. The first residual is based on the ideas used in obtaining score-type residuals similar to the partial likelihood approach. The second type of residual is based on the concept of deviance residuals. Extensive simulations are conducted to compare the performance of the residuals from the full likelihood-based approach with those of the partial likelihood method. We demonstrate through simulation studies that the full likelihood-based residuals are more efficient than their partial likelihood counterpart in identifying potential outliers when the censoring proportion is high. The graphical techniques are used to illustrate the applications of these residuals using some examples.
Authors
Halabi, S; Dutta, S; Wu, Y; Liu, A
MLA Citation
Halabi, Susan, et al. “Score and deviance residuals based on the full likelihood approach in survival analysis.Pharm Stat, Aug. 2020. Pubmed, doi:10.1002/pst.2047.
URI
https://scholars.duke.edu/individual/pub1453808
PMID
32776412
Source
pubmed
Published In
Pharm Stat
Published Date
DOI
10.1002/pst.2047

Research Areas:

Adenocarcinoma
Adenocarcinoma, Clear Cell
African Americans
Age Factors
Aged, 80 and over
Alkaline Phosphatase
Alleles
Arab countries
Area Under Curve
Biological Markers
Biomarkers, Pharmacological
Breast Neoplasms
Cancer Vaccines
Carcinoma
Carcinoma, Renal Cell
Case-Control Studies
Chemoprevention
Chemotherapy
Chi-Square Distribution
Clinical Trials, Phase II as Topic
Clinical trials
Cohort Studies
Computer Simulation
Confidence Intervals
Construction Materials
Contraceptives, Oral
DNA Damage
DNA Primers
DNA Repair
DNA, Neoplasm
Data Interpretation, Statistical
Decision Making
Decision Support Techniques
Diagnostic Imaging
Disease Progression
Disease-Free Survival
Drug Design
Dust
Efficiency, Organizational
Endpoint Determination
Equipment Design
Factor Analysis, Statistical
Family relationships
Gels
Gene Expression
Genes, Immunoglobulin
Genetic Predisposition to Disease
Genetics, Medical
Genotype
Germany
Graft vs Host Disease
HIV Infections
Hispanic Americans
Individualized Medicine
Kaplan-Meier Estimate
Ketoconazole
Lasso
Logistic Models
Lymphokines
Mining
Models, Biological
Models, Statistical
Models, Theoretical
Molecular Sequence Data
Multiprotein Complexes
Multivariate Analysis
Mutation
Neoplasms, Hormone-Dependent
Nomograms
Odds Ratio
Outcome Assessment (Health Care)
Ovarian Neoplasms
Personalized medicine
Population
Population Surveillance
Precision Medicine
Predictive Value of Tests
Pregnancy
Probability
Prognosis
Proportional Hazards Models
Prospective Studies
ROC Curve
Randomized Controlled Trials as Topic
Receptors, Progesterone
Registries
Reproducibility of Results
Research Design
Residence Characteristics
Retrospective Studies
Ribosomal Protein S6 Kinases
Risk
Risk Assessment
Risk Factors
Sample Size
Selective Estrogen Receptor Modulators
Sensitivity and Specificity
Statistics as Topic
Survival
Survival Analysis
Survival Rate
Tamoxifen
Translocation, Genetic
Treatment Failure
Treatment Outcome
Tumor Markers, Biological
United States
Urologic Neoplasms
Validation Studies as Topic
Vascular Endothelial Growth Factors