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Book: Statistical human genetics

Elston, Robert C. / Satagopan, Jaya M. / Sun, Shuying

methods and protocols

(Methods in molecular biology ; 850 ; Springer protocols)

2012

Author's details	ed. by Robert C. Elston ; Jaya M. Satagopan ; Shuying Sun
Series title	Methods in molecular biology ; 850 Springer protocols
Collection
Language	English
Size	XI, 564 S. : Ill., graph. Darst.
Publisher	Humana Press
Publishing place	New York u.a.
Publishing country	United States
Document type	Book
HBZ-ID	HT017146469
ISBN	978-1-61779-554-1 ; 9781617795558 ; 1-61779-554-2 ; 1617795550
Database	Catalogue ZB MED Medicine, Health

In stock of ZB MED Cologne/Königswinter

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2012 A 873	order for loan	Magazin

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Article ; Online: A model for an undergraduate research experience program in quantitative sciences.

Tan, Kay See / Elkin, Elena B / Satagopan, Jaya M

Journal of statistics and data science education : an official journal of the of the American Statistical Association

2022 Volume 30, Issue 1, Page(s) 65–74

Abstract: We developed a summer research experience program within a freestanding comprehensive cancer center to cultivate undergraduate students with an interest in and an aptitude for quantitative sciences focused on oncology. This unconventional location for an ...

Abstract	We developed a summer research experience program within a freestanding comprehensive cancer center to cultivate undergraduate students with an interest in and an aptitude for quantitative sciences focused on oncology. This unconventional location for an undergraduate program is an ideal setting for interdisciplinary training in the intersection of oncology, statistics, and epidemiology. This paper describes the development and implementation of a hands-on research experience program in this unique environment. Core components of the program include faculty-mentored projects, instructional programs to improve research skills and domain knowledge, and professional development activities. We discuss key considerations such as effective partnership between research and administrative units, recruiting students, and identifying faculty mentors with quantitative projects. We describe evaluation approaches and discuss post-program outcomes and lessons learned. In its initial two years, the program successfully improved students' perception of competence gained in research skills and statistical knowledge across several knowledge domains. The majority of students also went on to pursue graduate degrees in a quantitative field or work in oncology-centric academic research roles. Our research-based training model can be adapted by a variety of organizations motivated to develop a summer research experience program in quantitative sciences for undergraduate students.
Language	English
Publishing date	2022-02-22
Publishing country	United States
Document type	Journal Article
ISSN	2693-9169
ISSN (online)	2693-9169
DOI	10.1080/26939169.2021.2016036
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Factors Associated with Surgery Among South Asian American and Non-Hispanic White Women with Breast Cancer.

Lo, Lydia / Satagopan, Jaya M

American journal of undergraduate research

2020 Volume 18, Issue 3, Page(s) 15–23

Abstract: South Asian American (SA) women are diagnosed with more aggressive breast cancer than non-Hispanic White (NHW) women. Understanding the factors associated with the types of surgery received by these women sheds light on disease management in these ... ...

Abstract	South Asian American (SA) women are diagnosed with more aggressive breast cancer than non-Hispanic White (NHW) women. Understanding the factors associated with the types of surgery received by these women sheds light on disease management in these culturally distinct populations. We used data on age at diagnosis, stage, grade, estrogen and progesterone receptors, and surgery from 4,590 SA and 429,030 NHW breast cancer cases in the Surveillance, Epidemiology and End Results (SEER) program. We used logistic regression with surgery as the binary outcome (subcutaneous, total, or radical mastectomy (STRM) versus partial mastectomy, no, unknown or other (PNUM)) and included additive effects of all the variables and interactions of age, stage, grade, and estrogen and progesterone receptors with race/ethnicity. Type I error of 5% was used to assess statistical significance of the effects. SA were significantly more likely than NHW cases to receive STRM relative to PNUM surgery among women diagnosed at or after age 50 years and having localized stage disease (Odds Ratio (OR) = 1.27, 95% Confidence Interval (CI) = 1.06 - 1.52). Further, SA were significantly less likely than NHW cases to receive STRM relative to PNUM surgery among those diagnosed before age 50 years and having regional or distant stage disease (OR = 0.75, 95% CI = 0.59 - 0.95 for age at diagnosis < 40 years; OR = 0.77, 95% CI = 0.62 - 0.95 for age at diagnosis 40-49 years). The type of surgery received by SA and NHW women differ according to age at diagnosis and disease stage.
Language	English
Publishing date	2020-06-22
Publishing country	United States
Document type	Journal Article
ISSN	1536-4585
ISSN	1536-4585
DOI	10.33697/ajur.2021.048
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Article: Sociodemographic disparities in targeted therapy in ovarian cancer in a national sample.

Amin, Saber A / Collin, Lindsay J / Kavecansky, Juraj / Setoguchi, Soko / Satagopan, Jaya M / Bandera, Elisa V

Frontiers in oncology

2023 Volume 13, Page(s) 1104630

Abstract: Background: The treatment landscape for ovarian cancer has changed in recent years with the introduction of targeted therapies to treat patients with advanced disease. We investigated patient demographic and clinical factors associated with use of ... ...

Abstract	Background: The treatment landscape for ovarian cancer has changed in recent years with the introduction of targeted therapies to treat patients with advanced disease. We investigated patient demographic and clinical factors associated with use of targeted therapies as a part of the first-line treatment for ovarian cancer. Methods: This study included patients diagnosed with stage I-IV ovarian cancer between 2012 and 2019 from the National Cancer Database. Information on demographic and clinical characteristics were collected and described using frequency and percent across receipt of targeted therapy. Logistic regression was used to compute the odds ratios (ORs) and 95% confidence intervals (CI) associating patient demographic and clinical factors with receipt of targeted therapy. Results: Among 99,286 ovarian cancer patients (mean age 62 years), 4.1% received targeted therapy. The rate of targeted therapy receipt across racial and ethnic groups over the study period was fairly similar; however, non-Hispanic Black women were less likely to receive targeted therapy than their non-Hispanic White counterparts (OR=0.87, 95% CI: 0.76-1.00). Patients who received neoadjuvant chemotherapy were more likely to receive targeted therapy than those who received adjuvant chemotherapy (OR=1.26; 95% CI: 1.15-1.38). Moreover, among patients who received targeted therapy, 28% received neoadjuvant targeted therapy, with non-Hispanic Black women being most likely to receive neoadjuvant targeted therapy (34%) compared with other racial and ethnic groups. Conclusions: We observed differences in receipt of targeted therapy by factors such as age at diagnosis, stage, and comorbidities present at diagnosis, as well as factors related to healthcare access-including neighborhood education level and health insurance status. Approximately 28% of patients received targeted therapy in the neoadjuvant setting, which could negatively impact treatment outcomes and survival due to the increased risk of complications associated with targeted therapies that may delay or prevent surgery. These results warrant further evaluation in a cohort of patients with more comprehensive treatment information.
Language	English
Publishing date	2023-05-12
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2649216-7
ISSN	2234-943X
ISSN	2234-943X
DOI	10.3389/fonc.2023.1104630
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Article ; Online: Experiences and lessons learned from community-engaged recruitment for the South Asian breast cancer study in New Jersey during the COVID-19 pandemic.

Satagopan, Jaya M / Dharamdasani, Tina / Mathur, Shailja / Kohler, Racquel E / Bandera, Elisa V / Kinney, Anita Y

PloS one

2023 Volume 18, Issue 11, Page(s) e0294170

Abstract: Background: South Asians are a rapidly growing population in the United States. Breast cancer is a major concern among South Asian American women, who are an understudied population. We established the South Asian Breast Cancer (SABCa) study in New ... ...

Abstract	Background: South Asians are a rapidly growing population in the United States. Breast cancer is a major concern among South Asian American women, who are an understudied population. We established the South Asian Breast Cancer (SABCa) study in New Jersey during early 2020 to gain insights into their breast cancer-related health attitudes. Shortly after we started planning for the study, the COVID-19 disease spread throughout the world. In this paper, we describe our experiences and lessons learned from recruiting study participants by partnering with New Jersey's community organizations during the COVID-19 pandemic. Methods: We used a cross-sectional design. We contacted 12 community organizations and 7 (58%) disseminated our study information. However, these organizations became considerably busy with pandemic-related needs. Therefore, we had to pivot to alternative recruitment strategies through community radio, Rutgers Cancer Institute of New Jersey's Community Outreach and Engagement Program, and Rutgers Cooperative Extension's community health programs. We recruited participants through these alternative strategies, obtained written informed consent, and collected demographic information using a structured survey. Results: Twenty five women expressed interest in the study, of which 22 (88%) participated. Nine (41%) participants learned about the study through the radio, 5 (23%) through these participants, 1 (4.5%) through a non-radio community organization, and 7 (32%) through community health programs. Two (9%) participants heard about the study from their spouse. All participants were born outside the US, their average age was 52.4 years (range: 39-72 years), and they have lived in the US for an average of 26 years (range: 5-51 years). Conclusion: Pivoting to alternative strategies were crucial for successful recruitment. Findings suggest the significant potential of broadcast media for community-based recruitment. Family dynamics and the community's trust in our partners also encouraged participation. Such strategies must be considered when working with understudied populations.
MeSH term(s)	Humans ; United States ; Female ; Middle Aged ; Breast Neoplasms/epidemiology ; New Jersey/epidemiology ; COVID-19/epidemiology ; Pandemics ; Cross-Sectional Studies
Language	English
Publishing date	2023-11-13
Publishing country	United States
Document type	Journal Article
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0294170
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Article ; Online: Inverse association between total bilirubin and type 2 diabetes in U.S. South Asian males but not females.

Visaria, Aayush / Kanaya, Alka / Setoguchi, Soko / Gadgil, Meghana / Satagopan, Jaya

PloS one

2024 Volume 19, Issue 2, Page(s) e0297685

Abstract: Aims: United States South Asians constitute a fast-growing ethnic group with high prevalence of type 2 diabetes (T2D) despite lower mean BMI and other traditional risk factors compared to other races/ethnicities. Bilirubin has gained attention as a ... ...

Abstract	Aims: United States South Asians constitute a fast-growing ethnic group with high prevalence of type 2 diabetes (T2D) despite lower mean BMI and other traditional risk factors compared to other races/ethnicities. Bilirubin has gained attention as a potential antioxidant, cardio-protective marker. Hence we sought to determine whether total bilirubin was associated with prevalent and incident T2D in U.S. South Asians. Methods: We conducted a cross-sectional and prospective analysis of the Mediators of Atherosclerosis in South Asians Living in America (MASALA) study. Total bilirubin was categorized into gender-specific quartiles (Men: <0.6, 0.6, 0.7-0.8, >0.8; Women: <0.5, 0.5, 0.6, >0.6 mg/dl). We estimated odds of type 2 diabetes as well as other cardiovascular (CV) risk factors using multivariable logistic regression. Results: Among a total 1,149 participants (48% female, mean [SD] age of 57 [9] years), 38% had metabolic syndrome and 24% had T2D. Men and women in the lowest bilirubin quartile had 0.55% and 0.17% higher HbA1c than the highest quartile. Men, but not women, in the lowest bilirubin quartile had higher odds of T2D compared to the highest quartile (aOR [95% CI]; Men: 3.00 [1.72,5.23], Women: 1.15 [0.57,2.31]). There was no association between bilirubin and other CV risk factors. Conclusion: Total bilirubin was inversely associated with T2D in SA men but not women. Longitudinal studies are needed to understand temporality of association.
MeSH term(s)	Female ; Humans ; Male ; Bilirubin ; Cross-Sectional Studies ; Diabetes Mellitus, Type 2/epidemiology ; Risk Factors ; United States/epidemiology ; Asian
Chemical Substances	Bilirubin (RFM9X3LJ49)
Language	English
Publishing date	2024-02-07
Publishing country	United States
Document type	Journal Article
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0297685
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Article ; Online: Estimating Additive Interaction Effect in Stratified Two-Phase Case-Control Design.

Ni, Ai / Satagopan, Jaya M

Human heredity

2019 Volume 84, Issue 2, Page(s) 90–108

Abstract: Background and aims: There is considerable interest in epidemiology to estimate an additive interaction effect between two risk factors in case-control studies. An additive interaction is defined as the differential reduction in absolute risk associated ...

Abstract	Background and aims: There is considerable interest in epidemiology to estimate an additive interaction effect between two risk factors in case-control studies. An additive interaction is defined as the differential reduction in absolute risk associated with one factor between different levels of the other factor. A stratified two-phase case-control design is commonly used in epidemiology to reduce the cost of assembling covariates. It is crucial to obtain valid estimates of the model parameters by accounting for the underlying stratification scheme to obtain accurate and precise estimates of additive interaction effects. The aim of this paper is to examine the properties of different methods for estimating model parameters and additive interaction effects under a stratified two-phase case-control design. Methods: Using simulations, we investigate the properties of three existing methods, namely stratum-specific offset, inverse-probability weighting, and multiple imputation for estimating model parameters and additive interaction effects. We also illustrate these properties using data from two published epidemiology studies. Results: Simulation studies show that the multiple imputation method performs well when both the true and analysis models are additive (i.e., does not include multiplicative interaction terms) but does not provide a discernible advantage over the offset method when the analysis models are non-additive (i.e., includes multiplicative interaction terms). The offset method exhibits the best overall properties when the analysis model contains multiplicative interaction effects. Conclusion: When estimating additive interaction between risk factors in stratified two-phase case-control studies, we recommend estimating model parameters using multiple imputation when the analysis model is additive, and we recommend the offset method when the analysis model is non-additive.
MeSH term(s)	Case-Control Studies ; Computer Simulation ; Endometrial Neoplasms/genetics ; Female ; Humans ; Male ; Models, Statistical ; Regression Analysis ; Risk Factors
Language	English
Publishing date	2019-10-21
Publishing country	Switzerland
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2424-7
ISSN	1423-0062 ; 0001-5652
ISSN (online)	1423-0062
ISSN	0001-5652
DOI	10.1159/000502738
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: A Model for an Undergraduate Research Experience Program in Quantitative Sciences

Kay See Tan / Elena B. Elkin / Jaya M. Satagopan

Journal of Statistics and Data Science Education, Vol 0, Iss 0, Pp 1-

2022 Volume 10

Abstract	We developed a summer research experience program within a freestanding comprehensive cancer center to cultivate undergraduate students with an interest in and an aptitude for quantitative sciences focused on oncology. This unconventional location for an undergraduate program is an ideal setting for interdisciplinary training in the intersection of oncology, statistics, and epidemiology. This article describes the development and implementation of a hands-on research experience program in this unique environment. Core components of the program include faculty-mentored projects, instructional programs to improve research skills and domain knowledge, and professional development activities. We discuss key considerations such as fostering effective partnership between research and administrative units, recruiting students, and identifying faculty mentors with quantitative projects. We describe evaluation approaches and discuss post-program outcomes and lessons learned. In its initial two years, the program successfully improved the students’ perception of competence gained in research skills and statistical knowledge across several knowledge domains. The majority of students also went on to pursue graduate degrees in a quantitative field or work in oncology-centric academic research roles. Our research-based training model can be adapted by a variety of organizations motivated to develop a summer research experience program in quantitative sciences for undergraduate students. Supplemental files for this article are available online.
Keywords	analysis of biomedical data ; applied statistics internship ; computational biology ; experiential learning ; mentoring ; statistical training ; Probabilities. Mathematical statistics ; QA273-280 ; Special aspects of education ; LC8-6691
Subject code	370
Language	English
Publishing date	2022-02-01T00:00:00Z
Publisher	Taylor & Francis Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Statistical Interactions from a Growth Curve Perspective.

Devlin, Sean M / Satagopan, Jaya M

Human heredity

2017 Volume 82, Issue 1-2, Page(s) 21–36

Abstract: Logistic regression is widely used to evaluate the association between risk factors and a binary outcome. The logistic curve is symmetric around its point of inflection. Alternative families of curves, such as the additive Gompertz or Guerrero-Johnson ... ...

Abstract	Logistic regression is widely used to evaluate the association between risk factors and a binary outcome. The logistic curve is symmetric around its point of inflection. Alternative families of curves, such as the additive Gompertz or Guerrero-Johnson models, have been proposed in various scenarios due to their asymmetry: disease risk may initially increase rapidly and be followed by a longer period where the rate of growth slowly decreases. When modeling binary outcomes in relation to risk factors, an additive logistic model may not provide a good fit to the data. Suppose the outcome and an additive function of the risk factors are indeed related through an asymmetric function, but we model the relationship using a logistic function. We illustrate - both from a mathematical framework and through a simulation-based evaluation - that higher-order terms, such as pairwise interactions and quadratic terms, may be required in a logistic regression model to obtain a good fit to the data. Importantly, as significant higher-order terms may be a manifestation of model misspecification, these terms should be cautiously interpreted; a more pragmatic approach is to develop contrasts of disease risk coming from a good fitting model. We illustrate these concepts in 2 cohort studies examining early death for late-stage colorectal and pancreatic cancer cases, and 2 case-control studies investigating NAT2 acetylation, smoking, and advanced colorectal adenoma and bladder cancer.
Language	English
Publishing date	2017-07-26
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2424-7
ISSN	1423-0062 ; 0001-5652
ISSN (online)	1423-0062
ISSN	0001-5652
DOI	10.1159/000477125
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Article ; Online: Measuring differential treatment benefit across marker specific subgroups: The choice of outcome scale.

Satagopan, Jaya M / Iasonos, Alexia

Contemporary clinical trials

2017 Volume 63, Page(s) 40–50

Abstract: Clinical and epidemiological studies of anticancer therapies increasingly seek to identify predictive biomarkers to obtain insights into variation in treatment benefit. For time to event endpoints, a predictive biomarker is typically assessed using the ... ...

Abstract	Clinical and epidemiological studies of anticancer therapies increasingly seek to identify predictive biomarkers to obtain insights into variation in treatment benefit. For time to event endpoints, a predictive biomarker is typically assessed using the interaction between the biomarker and treatment in a proportional hazards model. Interactions are contrasts of summaries of outcomes and depend upon the choice of the outcome scale. In this paper, we investigate interaction contrasts under three scales - the natural logarithm of hazard ratio, the natural logarithm of survival probability, and survival probability at a pre-specified time. We illustrate that we can have a non-zero interaction on survival or logarithm of survival probability scales even when there is no interaction on the logarithm of hazard ratio scale. Since survival probabilities have clinically useful interpretation and are easier to convey to patients than hazard ratios, we recommend evaluating a predictive biomarker using survival probabilities. We provide empirical illustration of the three scales of interaction for evaluating a predictive biomarker using reconstructed data from a published melanoma study.
MeSH term(s)	Antineoplastic Agents/therapeutic use ; Biomarkers ; Drugs, Investigational/therapeutic use ; Humans ; Neoplasms/drug therapy ; Neoplasms/mortality ; Neoplasms/pathology ; Probability ; Proportional Hazards Models ; Randomized Controlled Trials as Topic/methods ; Research Design ; Survival Analysis
Chemical Substances	Antineoplastic Agents ; Biomarkers ; Drugs, Investigational
Language	English
Publishing date	2017-02-22
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	2182176-8
ISSN	1559-2030 ; 1551-7144
ISSN (online)	1559-2030
ISSN	1551-7144
DOI	10.1016/j.cct.2017.02.007
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