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Article ; Online: Predictive values, uncertainty, and interpretation of serology tests for the novel coronavirus.

Brownstein, Naomi C / Chen, Yian Ann

2021 Volume 11, Issue 1, Page(s) 5491

Abstract: Antibodies testing in the coronavirus era is frequently promoted, but the underlying statistics behind their validation has come under more scrutiny in recent weeks. We provide calculations, interpretations, and plots of positive and negative predictive ... ...

Abstract	Antibodies testing in the coronavirus era is frequently promoted, but the underlying statistics behind their validation has come under more scrutiny in recent weeks. We provide calculations, interpretations, and plots of positive and negative predictive values under a variety of scenarios. Prevalence, sensitivity, and specificity are estimated within ranges of values from researchers and antibodies manufacturers. Illustrative examples are highlighted, and interactive plots are provided in the Supplementary Information. Implications are discussed for society overall and across diverse locations with different levels of disease burden. Specifically, the proportion of positive serology tests that are false can differ drastically from up to 3%-88% for people from different places with different proportions of infected people in the populations while the false negative rate is typically under 10%.
MeSH term(s)	Antibodies, Viral/blood ; COVID-19/diagnosis ; COVID-19/virology ; Coronavirus Infections/diagnosis ; Coronavirus Infections/virology ; Humans ; Predictive Value of Tests ; Reagent Kits, Diagnostic ; SARS-CoV-2/isolation & purification ; Serologic Tests/methods ; Uncertainty
Chemical Substances	Antibodies, Viral ; Reagent Kits, Diagnostic
Language	English
Publishing date	2021-03-09
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-021-84173-1
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Predictive values, uncertainty, and interpretation of serology tests for the novel coronavirus.

Brownstein, Naomi C / Chen, Yian A

medRxiv : the preprint server for health sciences

2020

Abstract	Antibodies testing in the coronavirus era is frequently promoted, but the underlying statistics behind their validation has come under more scrutiny in recent weeks. We provide calculations, interpretations, and plots of positive and negative predictive values under a variety of scenarios. Prevalence, sensitivity, and specificity are estimated within ranges of values from researchers and antibodies manufacturers. Illustrative examples are highlighted, and interactive plots are provided in the Supplementary Material. Implications are discussed for society overall and across diverse locations with different levels of disease burden. Specifically, the proportion of positive serology tests that are false can differ drastically from up to 3% to 88% for people from different places with different proportions of infected people in the populations while the false negative rate is typically under 10%.
Keywords	covid19
Language	English
Publishing date	2020-12-15
Publishing country	United States
Document type	Preprint
DOI	10.1101/2020.06.04.20122358
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Article ; Online: Sparse clusterability: testing for cluster structure in high dimensions.

Laborde, Jose / Stewart, Paul A / Chen, Zhihua / Chen, Yian A / Brownstein, Naomi C

BMC bioinformatics

2023 Volume 24, Issue 1, Page(s) 125

Abstract: Background: Cluster analysis is utilized frequently in scientific theory and applications to separate data into groups. A key assumption in many clustering algorithms is that the data was generated from a population consisting of multiple distinct ... ...

Abstract	Background: Cluster analysis is utilized frequently in scientific theory and applications to separate data into groups. A key assumption in many clustering algorithms is that the data was generated from a population consisting of multiple distinct clusters. Clusterability testing allows users to question the inherent assumption of latent cluster structure, a theoretical requirement for meaningful results in cluster analysis. Results: This paper proposes methods for clusterability testing designed for high-dimensional data by utilizing sparse principal component analysis. Type I error and power of the clusterability tests are evaluated using simulated data with different types of cluster structure in high dimensions. Empirical performance of the new methods is evaluated and compared with prior methods on gene expression, microarray, and shotgun proteomics data. Our methods had reasonably low Type I error and maintained power for many datasets with a variety of structures and dimensions. Cluster structure was not detectable in other datasets with spatially close clusters. Conclusion: This is the first analysis of clusterability testing on both simulated and real-world high-dimensional data.
MeSH term(s)	Algorithms ; Cluster Analysis
Language	English
Publishing date	2023-03-31
Publishing country	England
Document type	Journal Article
ZDB-ID	2041484-5
ISSN	1471-2105 ; 1471-2105
ISSN (online)	1471-2105
ISSN	1471-2105
DOI	10.1186/s12859-023-05210-6
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Article ; Online: Factors Associated With Guideline-concordant and Excessive Cervical Cancer Screening: A Mixed Methods Study.

Perkins, Rebecca B / Fuzzell, Lindsay / Lake, Paige / Brownstein, Naomi C / Fontenot, Holly B / Michel, Alexandra / Whitmer, Ashley / Vadaparampil, Susan T

Women's health issues : official publication of the Jacobs Institute of Women's Health

2024

Abstract: Introduction: National guidelines recommend cervical cancer screening with Papanicolaou (Pap) testing at 3-year intervals or with human papillomavirus (HPV) testing alone or HPV/Pap cotesting at 5-year intervals for average-risk individuals aged 30-65 ... ...

Abstract	Introduction: National guidelines recommend cervical cancer screening with Papanicolaou (Pap) testing at 3-year intervals or with human papillomavirus (HPV) testing alone or HPV/Pap cotesting at 5-year intervals for average-risk individuals aged 30-65 years. Methods: We explored factors associated with clinician-reported guideline-concordant screening, as well as facilitators and barriers to appropriate cervical cancer screening. Results: A national sample of clinicians (N = 1,251) completed surveys; a subset (n = 55) completed interviews. Most (94%) screened average-risk patients aged 30-65 years with cotesting. Nearly all clinicians who were categorized as nonadherent to national guidelines were overscreening (98%). Guideline concordant screening was reported by 47% and 82% of those using cotesting and HPV testing, respectively (5-year intervals), and by 62% of those using Pap testing only (3-year intervals). Concordant screening was reported more often by clinicians who were aged <40 years, non-Hispanic, and practicing in the West or Midwest, and less often by obstetrician-gynecologists and private practice physicians. Concordant screening was facilitated by beliefs that updated guidelines were evidence-based and reduced harms, health care system dissemination of guidelines, and electronic medical record prompts. Barriers to concordant screening included using outdated guidelines, relying on personal judgment, concern about missing cancers, inappropriate patient risk assessment, and lack of support for guideline adoption through health care systems or electronic medical records. Conclusions: Most clinicians screened with Pap/HPV cotesting and approximately one-half endorsed a 5-year screening interval. Clinician knowledge gaps include understanding the evidence underlying 5-year intervals and appropriate risk assessment to determine which patients should be screened more frequently. Education and tracking systems can promote guideline-concordant screening.
Language	English
Publishing date	2024-02-20
Publishing country	United States
Document type	Journal Article
ZDB-ID	1085396-0
ISSN	1878-4321 ; 1049-3867
ISSN (online)	1878-4321
ISSN	1049-3867
DOI	10.1016/j.whi.2024.01.001
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Article ; Online: Attitudes toward the American Cancer Society's 2020 cervical cancer screening guidelines: A qualitative study of a national sample of US clinicians.

Michel, Alexandra D / Fontenot, Holly B / Fuzzell, Lindsay / Brownstein, Naomi C / Lake, Paige / Vadaparampil, Susan T / Perkins, Rebecca B

Cancer

2024

Abstract: Background: The 2020 American Cancer Society (ACS) guidelines are the most recent national guidelines for cervical cancer screening. These guidelines propose two major changes from current practice: initiating screening at age 25 years and using primary ...

Abstract	Background: The 2020 American Cancer Society (ACS) guidelines are the most recent national guidelines for cervical cancer screening. These guidelines propose two major changes from current practice: initiating screening at age 25 years and using primary human papillomavirus (HPV) testing. Adoption of guidelines often occurs slowly, and therefore understanding clinician attitudes is important to facilitate practice change. Methods: Interviews with a national sample of clinicians who perform cervical cancer screening in a variety of settings explored attitudes toward the two major changes from the 2020 ACS cervical cancer screening guidelines. Clinicians participated in 30- to 60-min interviews exploring their attitudes toward various aspects of cervical cancer screening. Qualitative analysis was performed. Results: Seventy clinicians participated from across the United States. Few respondents were initiating screening at age 25 years, and none were using primary HPV testing. However, over half would be willing to adopt these practices if supported by scientific evidence and recommended by professional medical organizations. Barriers to adoption included the lack of endorsement by professional societies, lack of laboratory availability and insurance coverage, limited autonomy within large health care systems, and concerns related to missed disease. Conclusions: Few clinicians have adopted screening initiation or primary HPV testing, as recommended by the 2020 ACS guidelines, but over half were open to adopting these changes. Implementation may be facilitated via professional organization endorsement, clinician education, and laboratory, health care system, and insurance support. Plain language summary: In 2020, the American Cancer Society (ACS) released updated guidelines for cervical cancer screening. The main changes to current practices were to initiate screening at age 25 years instead of age 21 years and to screen using primary human papillomavirus (HPV) testing rather than cytology alone or in combination with HPV testing. We performed in-depth interviews with 70 obstetrics and gynecology, family medicine, and internal medicine physicians and advanced practice providers about their attitudes toward these guidelines. Few clinicians are following the 2020 ACS guidelines, but over half were open to changing practice if the changes were supported by evidence and recommended by professional medical organizations. Barriers to adoption included the lack of endorsement by professional medical organizations, logistical issues, and concerns about missed disease.
Language	English
Publishing date	2024-03-04
Publishing country	United States
Document type	Journal Article
ZDB-ID	1429-1
ISSN	1097-0142 ; 0008-543X ; 1934-662X
ISSN (online)	1097-0142
ISSN	0008-543X ; 1934-662X
DOI	10.1002/cncr.35269
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Article ; Online: Tests of trend between disease outcomes and ordinal covariates discretized from underlying continuous variables: simulation studies and applications to NHANES 2007-2008.

Brownstein, Naomi C / Cai, Jianwen

BMC medical research methodology

2019 Volume 19, Issue 1, Page(s) 2

Abstract: Background: Many epidemiological studies test trends when investigating the association between a risk factor and a disease outcome. Continuous exposures are commonly discretized when the outcome is nonlinearly related to exposure as well as to ... ...

Abstract	Background: Many epidemiological studies test trends when investigating the association between a risk factor and a disease outcome. Continuous exposures are commonly discretized when the outcome is nonlinearly related to exposure as well as to facilitate interpretation and reduce measurement error. Guidance is needed regarding statistically valid trend tests for epidemiological data of this nature. Methods: The association between a discretized variable and a disease is modeled through logistic regression or survival analysis. Linear regression is then conducted by regressing the odds ratio or relative risk on the midpoint of the exposure interval. The trend test is based on the slope of the regression line. In order to investigate the performance of this approach, we conducted simulation studies, considering ten different approaches for the linear regression based on the inclusion or exclusion of an intercept in the model and the form of the weights. The proposed methods are applied to the National Health and Nutrition Examination Survey (NHANES) 2007-2008 for illustration. Results: The simulation studies show that eight of these methods are valid, and the relative efficiency depends on the underlying relationship between the covariate and the outcome. Conclusions: The significance of the study is its potential to help practitioners select an appropriate method to test for trend in their future studies that utilize ordinal covariates.
MeSH term(s)	Computer Simulation/statistics & numerical data ; Humans ; Linear Models ; Logistic Models ; Models, Statistical ; Nutrition Surveys/statistics & numerical data ; Risk Factors ; Treatment Outcome
Language	English
Publishing date	2019-01-05
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, Non-P.H.S.
ISSN	1471-2288
ISSN (online)	1471-2288
DOI	10.1186/s12874-018-0630-7
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Article ; Online: Shift From Smoking Cigarettes to Vaping Nicotine in Young Adults.

Sanford, Brandon T / Brownstein, Naomi C / Baker, Nathaniel L / Palmer, Amanda M / Smith, Tracy T / Rojewski, Alana M / Toll, Benjamin A

JAMA internal medicine

2023 Volume 184, Issue 1, Page(s) 106–108

MeSH term(s)	Humans ; Young Adult ; Nicotine/adverse effects ; Vaping/adverse effects ; Smoking ; Smoking Cessation ; Tobacco Products ; Electronic Nicotine Delivery Systems
Chemical Substances	Nicotine (6M3C89ZY6R)
Language	English
Publishing date	2023-11-11
Publishing country	United States
Document type	Journal Article
ZDB-ID	2699338-7
ISSN	2168-6114 ; 2168-6106
ISSN (online)	2168-6114
ISSN	2168-6106
DOI	10.1001/jamainternmed.2023.5239
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Article ; Online: Sparse clusterability

Jose Laborde / Paul A. Stewart / Zhihua Chen / Yian A. Chen / Naomi C. Brownstein

BMC Bioinformatics, Vol 24, Iss 1, Pp 1-

testing for cluster structure in high dimensions

2023 Volume 27

Abstract: Abstract Background Cluster analysis is utilized frequently in scientific theory and applications to separate data into groups. A key assumption in many clustering algorithms is that the data was generated from a population consisting of multiple ... ...

Abstract	Abstract Background Cluster analysis is utilized frequently in scientific theory and applications to separate data into groups. A key assumption in many clustering algorithms is that the data was generated from a population consisting of multiple distinct clusters. Clusterability testing allows users to question the inherent assumption of latent cluster structure, a theoretical requirement for meaningful results in cluster analysis. Results This paper proposes methods for clusterability testing designed for high-dimensional data by utilizing sparse principal component analysis. Type I error and power of the clusterability tests are evaluated using simulated data with different types of cluster structure in high dimensions. Empirical performance of the new methods is evaluated and compared with prior methods on gene expression, microarray, and shotgun proteomics data. Our methods had reasonably low Type I error and maintained power for many datasets with a variety of structures and dimensions. Cluster structure was not detectable in other datasets with spatially close clusters. Conclusion This is the first analysis of clusterability testing on both simulated and real-world high-dimensional data.
Keywords	Cluster analysis ; Cluster tendency ; Clustering ; Big data ; Dimension reduction ; Principal component analysis ; Computer applications to medicine. Medical informatics ; R858-859.7 ; Biology (General) ; QH301-705.5
Subject code	004
Language	English
Publishing date	2023-03-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Predictive values, uncertainty, and interpretation of serology tests for the novel coronavirus

Naomi C. Brownstein / Yian Ann Chen

Scientific Reports, Vol 11, Iss 1, Pp 1-

2021 Volume 12

Abstract: Abstract Antibodies testing in the coronavirus era is frequently promoted, but the underlying statistics behind their validation has come under more scrutiny in recent weeks. We provide calculations, interpretations, and plots of positive and negative ... ...

Abstract	Abstract Antibodies testing in the coronavirus era is frequently promoted, but the underlying statistics behind their validation has come under more scrutiny in recent weeks. We provide calculations, interpretations, and plots of positive and negative predictive values under a variety of scenarios. Prevalence, sensitivity, and specificity are estimated within ranges of values from researchers and antibodies manufacturers. Illustrative examples are highlighted, and interactive plots are provided in the Supplementary Information. Implications are discussed for society overall and across diverse locations with different levels of disease burden. Specifically, the proportion of positive serology tests that are false can differ drastically from up to 3%–88% for people from different places with different proportions of infected people in the populations while the false negative rate is typically under 10%.
Keywords	Medicine ; R ; Science ; Q
Language	English
Publishing date	2021-03-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Characteristics associated with healthcare disruptions during the COVID-19 pandemic for women in the United States at high risk for breast cancer.

Conley, Claire C / Rodriguez, Jennifer D / Brownstein, Naomi C / O'Neill, Suzanne C / Vadaparampil, Susan T

Preventive medicine reports

2022 Volume 30, Page(s) 101975

Abstract: Delays in healthcare, including breast cancer screening, were documented during the coronavirus disease 2019 (COVID-19) pandemic. However, no studies have examined the impact of COVID-19 on healthcare among women at high (≥20 % lifetime) risk for breast ... ...

Abstract	Delays in healthcare, including breast cancer screening, were documented during the coronavirus disease 2019 (COVID-19) pandemic. However, no studies have examined the impact of COVID-19 on healthcare among women at high (≥20 % lifetime) risk for breast cancer. This study fills that gap. Between August 2020 and January 2021, high-risk women (N = 225) living in the United States (US) completed an online survey assessing COVID-related healthcare disruptions. Descriptive statistics characterized the frequency of breast cancer screening (mammogram and breast magnetic resonance imaging [MRI]) since the beginning of the COVID-19 pandemic. Multivariable linear regression analysis with backward selection examined demographic characteristics associated with COVID-related healthcare disruptions. Since March 2020, 40 % of participants had received a mammogram and 12 % had received a screening breast MRI. On average, participants reported low levels of COVID-related healthcare disruptions (
Language	English
Publishing date	2022-09-06
Publishing country	United States
Document type	Journal Article
ZDB-ID	2785569-7
ISSN	2211-3355
ISSN	2211-3355
DOI	10.1016/j.pmedr.2022.101975
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