Biometrics

Phyllis A Gimotty, Associate Professor Of Biostatistics
Wistar Institute 3601 Spruce Street Philadelphia, Pa 191044265

Grant 5P50CA093372-069002 from National Cancer Institute, IRG: ZCA1

Abstract: The goal of the Biometrics Core is to provide SPORE investigators access biostatisticians who have experience with biostatistical methodology and their application to research studies in cancer of the skin. The Biometrics Core staff will provide expertise in research methodologies necessary to design and implement rigorous research studies in Specific Aim 1. Through Specific Aim 2 they will provide expertise in informatics necessary to support efficient database development and database linkage, as well as expertise in statistical programming necessary to implement sample designs and both descriptive and inferential statistical analyses for SPORE studies. By way of Specific Aim 3 they will provide expertise in statistical methodology critical in the evahtation of research hypotheses and in the development of statistical models specified by the research objectives of the SPORE studies. Lastly, through Specific Aim 4, they will provide oversight, maintenance and quality assurance for data stored in the SPORE Database Library, facilitating access to it for SPORE-related inquiries and uses. Through these specific aims the Biometrics Core will insure that SPORE-related studies will have high quality study designs and statistical analysis plans that will provide a solid foundation for statistical inferences.

Keywords: biomedical facility, skin neoplasm, statistics /biometry, cancer information system, mathematical model

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CORE--BIOMETRICS

Phyllis A Gimotty, Associate Professor Of Biostatistics
Wistar Institute 3601 Spruce Street Philadelphia, Pa 191044265

Grant 5P50CA093372-029002 from National Cancer Institute, IRG: ZCA1

Abstract: The goal of the Biometrics Core is to provide SPORE investigators access to a team of biostatisticians who have experience with biostatistical methodology and their application to research studies in cancer of the skin. The Biometrics Core staff will provide expertise in research methodologies necessary to design and implement rigorous research studies in Specific Aim 1. In Specific Aim 2 they will provide expertise in informatics necessary, to support efficient database development and database linkage, as well as expertise in statistical programming necessary to implement sample designs and both descriptive and inferential statistical analyses for SPORE studies. In Specific Aim 3 they will provide expertise in statistical methodology critical in the evaluation of research hypotheses and in the development of statistical models specified by the research objectives of the SPORE studies. Lastly, in Specific Aim 4, they will provide oversight, maintenance and quality assurance for the SPORE Database Library, facilitating access to it for SPORE-related inquiries and uses. Through these specific aims the Biometrics Core will insure that SPORE-related studies will have high quality study designs and statistical analysis plans that will provide a solid foundation for statistical inferences.

Keywords: biomedical facility, statistics /biometry, animal data, human data

Project start date: 2002-09-28

Project end date: 2003-09-27

Biometrics

Phyllis A Gimotty, Associate Professor Of Biostatistics
Wistar Institute 3601 Spruce Street Philadelphia, Pa 191044265

Grant 5P50CA093372-059002 from National Cancer Institute, IRG: ZCA1

Abstract: The goal of the Biometrics Core is to provide SPORE investigators access biostatisticians who have experience with biostatistical methodology and their application to research studies in cancer of the skin. The Biometrics Core staff will provide expertise in research methodologies necessary to design and implement rigorous research studies in Specific Aim 1. Through Specific Aim 2 they will provide expertise in informatics necessary to support efficient database development and database linkage, as well as expertise in statistical programming necessary to implement sample designs and both descriptive and inferential statistical analyses for SPORE studies. By way of Specific Aim 3 they will provide expertise in statistical methodology critical in the evahtation of research hypotheses and in the development of statistical models specified by the research objectives of the SPORE studies. Lastly, through Specific Aim 4, they will provide oversight, maintenance and quality assurance for data stored in the SPORE Database Library, facilitating access to it for SPORE-related inquiries and uses. Through these specific aims the Biometrics Core will insure that SPORE-related studies will have high quality study designs and statistical analysis plans that will provide a solid foundation for statistical inferences.

Keywords: biomedical facility, skin neoplasm, statistics /biometry, cancer information system, mathematical model

Clinically Useful Pronostic Models In Primar

Phyllis A Gimotty, Associate Professor Of Biostatistics
Wistar Institute 3601 Spruce Street Philadelphia, Pa 191044265

Grant 5P50CA093372-060002 from National Cancer Institute, IRG: ZCA1

Abstract: Staging and therapy of cutaneous melanoma patients with sentinel lymph node biopsies and the use of systemic adjuvant therapy in those with high risk primary lesions and/or regional lymph node metastases lately have become commonplace, although neither intervention has been shown unequivocally to improve overall survival. These, together with the promulgation of the recent extensive revision of the AJCC staging system, make it particularly timely and important to develop further, validate and export prognostic models that will be used for designing efficient clinical trials and for clinical management of patients with melanoma. The overall objective of this project remains to impact positively on melanoma s management and mortality by developing and testing prognostic models using a well documented and carefully followed cohort of approximately 5,000 melanoma patients assembled since 1972 and an archive of tissue blocks of primary lesions for a representative sample these patients. In specific aim 1 we will establish both better modeling techniques and more robust prognostic factors by the application of innovative biostatistical methods to address the candidacy of clinical and new immunohistologic biomarkers. Specific aims 2 and 3 are designed to continue development of models whose use will I) protect patients with "minimal risk" melanomas from the morbidity and cost of excessive investigation and therapy, and 2) better calibrate investigation and management of patients with metastatic capacity by clinical trialists and clinicians by predicting the likelihood of a SLN biopsy revealing melanoma and of metastasis-free survival with and without regional surgical staging and therapy. To optimize surveillance and allow early intervention for additional primary melanomas in follow-up, in specific aim 4 we will develop prognostic models for predicting the occurrence of a second primary melanoma. These new models will ultimately incorporate information on patients  MC1R and CDKN2A genotypes. To promote the use of models by trialists and practitioners, in all models we will develop individualized patient probabilities for the occurrence of clinically relevant events and will accomplish external validation with intra- and extra-SPORE collaborators.

Keywords: mathematical model, melanoma, metastasis, model design /development, prognosis, biopsy, neoplasm /cancer classification /staging, neoplastic process, human data, human tissue

CLINICALLY USEFUL PROGNOSTIC MODELS IN PRIMARY MELANOMA

Phyllis A Gimotty, Associate Professor Of Biostatistics
Wistar Institute 3601 Spruce Street Philadelphia, Pa 191044265

Grant 5P50CA093372-020002 from National Cancer Institute, IRG: ZCA1

Abstract: Staging and therapy of cutaneous melanoma patients with sentinel lymph node (SLN) biopsies and the use of systemic adjuvant therapy in those with high risk primaries and/or regional lymph node metastases lately have become commonplace, although neither has been shown unequivocally to improve survival. It is both timely and important to develop prognostic models that have potential utility for the design of efficient clinical trials and for clinical management of patients with melanoma. The objective of this project is to develop prognostic models using a rigorously documented and carefully followed cohort of over 5,500 melanoma patients assembled since 1972 and an archive of tissue blocks containing a representative sample of their primary lesions. The application of novel biostatistical methods using clinical and new immunohistologic data will allow us to achieve our explicit goals. To protect patients with "minimal risk" melanomas from the morbidity and cost of excessive investigation and therapy, in the first specific aim we will test the hypothesis that invasive melanoma without metastatic capacity can be identified using currently available, easily employed, and readily interpreted clinical, histologic and immunohistologic prognostic variables. To better calibrate investigation and management of patients with metastatic capacity by clinical trialists and clinicians, in the second specific aim we will develop multivariable prognostic models for predicting the likelihood of a SLN biopsy revealing melanoma and of metastasis-free survival after regional surgical staging and therapy. To optimize surveillance for additional primary melanomas in follow-up, in the third specific aim we will develop multivariable prognostic models for predicting the occurrence or a second primary. To promote the use of these models by clinical trialists and clinicians, we will develop individualized patient probabilities of the occurrence of clinically relevant events that can be used in trial design and clinical decision making.

Keywords: mathematical model, melanoma, metastasis, model design /development, prognosis, tumor progression, human data, human tissue

Project start date: 2002-09-28

Project end date: 2003-09-27

Biometrics

Phyllis A Gimotty, Associate Professor Of Biostatistics
Wistar Institute 3601 Spruce Street Philadelphia, Pa 191044265

Grant 2P50CA093372-039002 from National Cancer Institute, IRG: ZCA1

Abstract: The goal of the Biometrics Core is to provide SPORE investigators access biostatisticians who have experience with biostatistical methodology and their application to research studies in cancer of the skin. The Biometrics Core staff will provide expertise in research methodologies necessary to design and implement rigorous research studies in Specific Aim 1. Through Specific Aim 2 they will provide expertise in informatics necessary to support efficient database development and database linkage, as well as expertise in statistical programming necessary to implement sample designs and both descriptive and inferential statistical analyses for SPORE studies. By way of Specific Aim 3 they will provide expertise in statistical methodology critical in the evahtation of research hypotheses and in the development of statistical models specified by the research objectives of the SPORE studies. Lastly, through Specific Aim 4, they will provide oversight, maintenance and quality assurance for data stored in the SPORE Database Library, facilitating access to it for SPORE-related inquiries and uses. Through these specific aims the Biometrics Core will insure that SPORE-related studies will have high quality study designs and statistical analysis plans that will provide a solid foundation for statistical inferences.

Keywords: biomedical facility, skin neoplasm, statistics /biometry, cancer information system, mathematical model

Project start date: 2004-07-27

Project end date: 2009-06-30

CORE--Biostatistics Core D: U. Of PA Consortium

Phyllis A Gimotty, Professor Of Biostatistics
University Of Pennsylvania
3451 Walnut Street
philadelphia, Pa 19104

Grant 5P01CA025874-289006 from National Cancer Institute, IRG: NCI

Abstract: The goal of the Biometrics Core is to provide investigators in this program project access biostatisticians who have experience with biostatistical methodology and their application to research in melanoma etiology and progression. The Biometrics Core staff will provide expertise in research methodologies necessary to design and implement rigorous experimental studies in Specific Aim 1. Through Specific Aim 2 they will provide expertise in informatics necessary to support efficient database development and database linkage, as well as expertise in statistical programming necessary for both descriptive and inferential statistical analyses. By way of Specific Aim 3 they will provide expertise in statistical methodology critical in the evaluation of research hypotheses and in the development of statistical models specified by the research objectives of each of the research projects. Through these specific aims the Biometrics Core will insure that this program project will have high quality study designs and statistical analysis plans that will provide a solid foundation for statistical inference

Keywords: biomedical facility, disease /disorder etiology, melanoma, statistics /biometry

Cancer Biostatistics Training Grant

Phyllis A Gimotty, Professor Of Biostatistics
Biostatistics And Epidemiologyuniversity Of Pennsylvania

Grant 2T32CA093283-06A1 from National Cancer Institute, IRG: NCI

Abstract: The Center for Clinical Epidemiology and Biostatistics (CCEB) of the University of Pennsylvania (Penn) School of Medicine (SOM) resubmits this proposal to continue an innovative and successful pre-doctoral training program in cancer biostatistics. The objective of this program is to train individuals to be rigorous and independent academic investigators able to use the range of approaches in biostatistics to address questions in cancer research. The program is specifically built upon existing collaborative relationships among biostatistics, statistics, and cancer research faculty in the CCEB and Department of Biostatistics and Epidemiology (DBE), the Abramson Cancer Center (ACC), and Wharton´s Department of Statistics (STAT) at Penn. This pre-doctoral training program for PhD students in Statistics and Biostatistics who have advanced to the dissertation stage of their training, provides didactic training in fundamental skills, methodologies, and principles of biostatistics, with emphasis on the areas of most importance to cancer research. Trainees are required to obtain a strong background in substantive areas related to cancer through participation in research seminars and a series of interdisciplinary courses in cancer research and cancer biology that examine methodologic issues, scientific approaches, technologies, concepts, and applications of statistical approaches in cancer research. Specifically, the training program is designed to 1) provide in-depth knowledge of the biostatistical techniques appropriate to cancer research; 2) provide research experiences with mentors in both biostatistics and cancer research; and 3) provide an inter-disciplinary infrastructure, bringing together faculty and students in the CCEB, DBE, ACC, and STAT, designed to support graduate education in cancer biostatistics. The strengths of the program are its training program in biostatistics, including comprehensive course offerings available to students; the wide-ranging experience of the biostatistics faculty in multiple areas of biostatistics methods and cancer research; the commitment of the faculty to collaborative research and training; the established teaching program in Statistics offered by the Wharton School; the long history of successful clinical research training programs offered by the CCEB; and the existing collaborative links among CCEB and DBE faculty in biostatistics and epidemiology, the ACC, and STAT. The resources available to students include a broad array of ongoing research projects, including clinical trials, observational studies, translational research, and experimental studies. Penn´s commitment to collaborative research and training and the broad range of expertise and experiences of faculty participating in this training program provide an ideal environment for this training program

Project start date: 2001-09-01

Project end date: 2013-07-31

5T32CA093283-05 (2007): $181359

5T32CA093283-04 (2006): $181357

5T32CA093283-03 (2005): $174445

5T32CA093283-02 (2004): $136018

Clinically Useful Pronostic Models In Primar

Phyllis A Gimotty, Associate Professor Of Biostatistics
Wistar Institute 3601 Spruce Street Philadelphia, Pa 191044265

Grant 2P50CA093372-030002 from National Cancer Institute, IRG: ZCA1

Abstract: Staging and therapy of cutaneous melanoma patients with sentinel lymph node biopsies and the use of systemic adjuvant therapy in those with high risk primary lesions and/or regional lymph node metastases lately have become commonplace, although neither intervention has been shown unequivocally to improve overall survival. These, together with the promulgation of the recent extensive revision of the AJCC staging system, make it particularly timely and important to develop further, validate and export prognostic models that will be used for designing efficient clinical trials and for clinical management of patients with melanoma. The overall objective of this project remains to impact positively on melanoma s management and mortality by developing and testing prognostic models using a well documented and carefully followed cohort of approximately 5,000 melanoma patients assembled since 1972 and an archive of tissue blocks of primary lesions for a representative sample these patients. In specific aim 1 we will establish both better modeling techniques and more robust prognostic factors by the application of innovative biostatistical methods to address the candidacy of clinical and new immunohistologic biomarkers. Specific aims 2 and 3 are designed to continue development of models whose use will I) protect patients with "minimal risk" melanomas from the morbidity and cost of excessive investigation and therapy, and 2) better calibrate investigation and management of patients with metastatic capacity by clinical trialists and clinicians by predicting the likelihood of a SLN biopsy revealing melanoma and of metastasis-free survival with and without regional surgical staging and therapy. To optimize surveillance and allow early intervention for additional primary melanomas in follow-up, in specific aim 4 we will develop prognostic models for predicting the occurrence of a second primary melanoma. These new models will ultimately incorporate information on patients  MC1R and CDKN2A genotypes. To promote the use of models by trialists and practitioners, in all models we will develop individualized patient probabilities for the occurrence of clinically relevant events and will accomplish external validation with intra- and extra-SPORE collaborators.

Keywords: mathematical model, melanoma, metastasis, model design /development, prognosis, biopsy, neoplasm /cancer classification /staging, tumor progression, human data, human tissue

Project start date: 2004-07-27

Project end date: 2009-06-30