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Showing 1 to 12 of 16 entries
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Targeted sequencing of established and candidate colorectal cancer genes in the Colon Cancer Family Registry Cohort.

Oncotarget

Raskin L, Guo Y, Du L, Clendenning M, Rosty C, Lindor NM, Gruber SB, Buchanan DD.
PMID: 29212164
Oncotarget. 2017 Jun 21;8(55):93450-93463. doi: 10.18632/oncotarget.18596. eCollection 2017 Nov 07.

The underlying genetic cause of colorectal cancer (CRC) can be identified for 5-10% of all cases, while at least 20% of CRC cases are thought to be due to inherited genetic factors. Screening for highly penetrant mutations in genes...

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Raskin L, Guo Y, Du L, et al. Targeted sequencing of established and candidate colorectal cancer genes in the Colon Cancer Family Registry Cohort. Oncotarget. 2017;8(55):93450-93463doi: 10.18632/oncotarget.18596.
Raskin, L., Guo, Y., Du, L., Clendenning, M., Rosty, C., Lindor, N. M., Gruber, S. B., & Buchanan, D. D. (2017). Targeted sequencing of established and candidate colorectal cancer genes in the Colon Cancer Family Registry Cohort. Oncotarget, 8(55), 93450-93463. https://doi.org/10.18632/oncotarget.18596
Raskin, Leon, et al. "Targeted sequencing of established and candidate colorectal cancer genes in the Colon Cancer Family Registry Cohort." Oncotarget vol. 8,55 (2017): 93450-93463. doi: https://doi.org/10.18632/oncotarget.18596
Raskin L, Guo Y, Du L, Clendenning M, Rosty C, Lindor NM, Gruber SB, Buchanan DD. Targeted sequencing of established and candidate colorectal cancer genes in the Colon Cancer Family Registry Cohort. Oncotarget. 2017 Jun 21;8(55):93450-93463. doi: 10.18632/oncotarget.18596. eCollection 2017 Nov 07. PMID: 29212164; PMCID: PMC5706810.
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Exploratory Genome-Wide Interaction Analysis of Nonsteroidal Anti-inflammatory Drugs and Predicted Gene Expression on Colorectal Cancer Risk.

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology

Wang X, Su YR, Petersen PS, Bien S, Schmit SL, Drew DA, Albanes D, Berndt SI, Brenner H, Campbell PT, Casey G, Chang-Claude J, Gallinger SJ, Gruber SB, Haile RW, Harrison TA, Hoffmeister M, Jacobs EJ, Jenkins MA, Joshi AD, Li L, Lin Y, Lindor NM, Marchand LL, Martin V, Milne R, Maclnnis R, Moreno V, Nan H, Newcomb PA, Potter JD, Rennert G, Rennert H, Slattery ML, Thibodeau SN, Weinstein SJ, Woods MO, Chan AT, White E, Hsu L, Peters U.
PMID: 32651213
Cancer Epidemiol Biomarkers Prev. 2020 Sep;29(9):1800-1808. doi: 10.1158/1055-9965.EPI-19-1018. Epub 2020 Jul 10.

BACKGROUND: Regular use of nonsteroidal anti-inflammatory drugs (NSAID) is associated with lower risk of colorectal cancer. Genome-wide interaction analysis on single variants (G × E) has identified several SNPs that may interact with NSAIDs to confer colorectal cancer risk,...

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Wang X, Su YR, Petersen PS, et al. Exploratory Genome-Wide Interaction Analysis of Nonsteroidal Anti-inflammatory Drugs and Predicted Gene Expression on Colorectal Cancer Risk. Cancer Epidemiol Biomarkers Prev. 2020;29(9):1800-1808doi: 10.1158/1055-9965.EPI-19-1018.
Wang, X., Su, Y. R., Petersen, P. S., Bien, S., Schmit, S. L., Drew, D. A., Albanes, D., Berndt, S. I., Brenner, H., Campbell, P. T., Casey, G., Chang-Claude, J., Gallinger, S. J., Gruber, S. B., Haile, R. W., Harrison, T. A., Hoffmeister, M., Jacobs, E. J., Jenkins, M. A., Joshi, A. D., Li, L., Lin, Y., Lindor, N. M., Marchand, L. L., Martin, V., Milne, R., Maclnnis, R., Moreno, V., Nan, H., Newcomb, P. A., Potter, J. D., Rennert, G., Rennert, H., Slattery, M. L., Thibodeau, S. N., Weinstein, S. J., Woods, M. O., Chan, A. T., White, E., Hsu, L., & Peters, U. (2020). Exploratory Genome-Wide Interaction Analysis of Nonsteroidal Anti-inflammatory Drugs and Predicted Gene Expression on Colorectal Cancer Risk. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 29(9), 1800-1808. https://doi.org/10.1158/1055-9965.EPI-19-1018
Wang, Xiaoliang, et al. "Exploratory Genome-Wide Interaction Analysis of Nonsteroidal Anti-inflammatory Drugs and Predicted Gene Expression on Colorectal Cancer Risk." Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology vol. 29,9 (2020): 1800-1808. doi: https://doi.org/10.1158/1055-9965.EPI-19-1018
Wang X, Su YR, Petersen PS, Bien S, Schmit SL, Drew DA, Albanes D, Berndt SI, Brenner H, Campbell PT, Casey G, Chang-Claude J, Gallinger SJ, Gruber SB, Haile RW, Harrison TA, Hoffmeister M, Jacobs EJ, Jenkins MA, Joshi AD, Li L, Lin Y, Lindor NM, Marchand LL, Martin V, Milne R, Maclnnis R, Moreno V, Nan H, Newcomb PA, Potter JD, Rennert G, Rennert H, Slattery ML, Thibodeau SN, Weinstein SJ, Woods MO, Chan AT, White E, Hsu L, Peters U. Exploratory Genome-Wide Interaction Analysis of Nonsteroidal Anti-inflammatory Drugs and Predicted Gene Expression on Colorectal Cancer Risk. Cancer Epidemiol Biomarkers Prev. 2020 Sep;29(9):1800-1808. doi: 10.1158/1055-9965.EPI-19-1018. Epub 2020 Jul 10. PMID: 32651213; PMCID: PMC7556991.
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Predicted Cure and Survival Among Transplant Recipients With a Previous Cancer Diagnosis.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology

Engels EA, Haber G, Hart A, Lynch CF, Li J, Pawlish KS, Qiao B, Yu KJ, Pfeiffer RM.
PMID: 34678077
J Clin Oncol. 2021 Dec 20;39(36):4039-4048. doi: 10.1200/JCO.21.01195. Epub 2021 Oct 22.

PURPOSE: A previous cancer diagnosis is a negative consideration in evaluating patients for possible solid organ transplantation. Statistical models may improve selection of patients with cancer evaluated for transplantation.METHODS: We fitted statistical cure models for patients with cancer in...

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Engels EA, Haber G, Hart A, et al. Predicted Cure and Survival Among Transplant Recipients With a Previous Cancer Diagnosis. J Clin Oncol. 2021;39(36):4039-4048doi: 10.1200/JCO.21.01195.
Engels, E. A., Haber, G., Hart, A., Lynch, C. F., Li, J., Pawlish, K. S., Qiao, B., Yu, K. J., & Pfeiffer, R. M. (2021). Predicted Cure and Survival Among Transplant Recipients With a Previous Cancer Diagnosis. Journal of clinical oncology : official journal of the American Society of Clinical Oncology, 39(36), 4039-4048. https://doi.org/10.1200/JCO.21.01195
Engels, Eric A, et al. "Predicted Cure and Survival Among Transplant Recipients With a Previous Cancer Diagnosis." Journal of clinical oncology : official journal of the American Society of Clinical Oncology vol. 39,36 (2021): 4039-4048. doi: https://doi.org/10.1200/JCO.21.01195
Engels EA, Haber G, Hart A, Lynch CF, Li J, Pawlish KS, Qiao B, Yu KJ, Pfeiffer RM. Predicted Cure and Survival Among Transplant Recipients With a Previous Cancer Diagnosis. J Clin Oncol. 2021 Dec 20;39(36):4039-4048. doi: 10.1200/JCO.21.01195. Epub 2021 Oct 22. PMID: 34678077; PMCID: PMC8677988.
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Predicted Cure and Survival Among Transplant Recipients With a Previous Cancer Diagnosis.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology

Engels EA, Haber G, Hart A, Lynch CF, Li J, Pawlish KS, Qiao B, Yu KJ, Pfeiffer RM.
PMID: 34678077
J Clin Oncol. 2021 Dec 20;39(36):4039-4048. doi: 10.1200/JCO.21.01195. Epub 2021 Oct 22.

PURPOSE: A previous cancer diagnosis is a negative consideration in evaluating patients for possible solid organ transplantation. Statistical models may improve selection of patients with cancer evaluated for transplantation.METHODS: We fitted statistical cure models for patients with cancer in...

Cite
Engels EA, Haber G, Hart A, et al. Predicted Cure and Survival Among Transplant Recipients With a Previous Cancer Diagnosis. J Clin Oncol. 2021;39(36):4039-4048doi: 10.1200/JCO.21.01195.
Engels, E. A., Haber, G., Hart, A., Lynch, C. F., Li, J., Pawlish, K. S., Qiao, B., Yu, K. J., & Pfeiffer, R. M. (2021). Predicted Cure and Survival Among Transplant Recipients With a Previous Cancer Diagnosis. Journal of clinical oncology : official journal of the American Society of Clinical Oncology, 39(36), 4039-4048. https://doi.org/10.1200/JCO.21.01195
Engels, Eric A, et al. "Predicted Cure and Survival Among Transplant Recipients With a Previous Cancer Diagnosis." Journal of clinical oncology : official journal of the American Society of Clinical Oncology vol. 39,36 (2021): 4039-4048. doi: https://doi.org/10.1200/JCO.21.01195
Engels EA, Haber G, Hart A, Lynch CF, Li J, Pawlish KS, Qiao B, Yu KJ, Pfeiffer RM. Predicted Cure and Survival Among Transplant Recipients With a Previous Cancer Diagnosis. J Clin Oncol. 2021 Dec 20;39(36):4039-4048. doi: 10.1200/JCO.21.01195. Epub 2021 Oct 22. PMID: 34678077; PMCID: PMC8677988.
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Predicted Cure and Survival Among Transplant Recipients With a Previous Cancer Diagnosis.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology

Engels EA, Haber G, Hart A, Lynch CF, Li J, Pawlish KS, Qiao B, Yu KJ, Pfeiffer RM.
PMID: 34678077
J Clin Oncol. 2021 Dec 20;39(36):4039-4048. doi: 10.1200/JCO.21.01195. Epub 2021 Oct 22.

PURPOSE: A previous cancer diagnosis is a negative consideration in evaluating patients for possible solid organ transplantation. Statistical models may improve selection of patients with cancer evaluated for transplantation.METHODS: We fitted statistical cure models for patients with cancer in...

Cite
Engels EA, Haber G, Hart A, et al. Predicted Cure and Survival Among Transplant Recipients With a Previous Cancer Diagnosis. J Clin Oncol. 2021;39(36):4039-4048doi: 10.1200/JCO.21.01195.
Engels, E. A., Haber, G., Hart, A., Lynch, C. F., Li, J., Pawlish, K. S., Qiao, B., Yu, K. J., & Pfeiffer, R. M. (2021). Predicted Cure and Survival Among Transplant Recipients With a Previous Cancer Diagnosis. Journal of clinical oncology : official journal of the American Society of Clinical Oncology, 39(36), 4039-4048. https://doi.org/10.1200/JCO.21.01195
Engels, Eric A, et al. "Predicted Cure and Survival Among Transplant Recipients With a Previous Cancer Diagnosis." Journal of clinical oncology : official journal of the American Society of Clinical Oncology vol. 39,36 (2021): 4039-4048. doi: https://doi.org/10.1200/JCO.21.01195
Engels EA, Haber G, Hart A, Lynch CF, Li J, Pawlish KS, Qiao B, Yu KJ, Pfeiffer RM. Predicted Cure and Survival Among Transplant Recipients With a Previous Cancer Diagnosis. J Clin Oncol. 2021 Dec 20;39(36):4039-4048. doi: 10.1200/JCO.21.01195. Epub 2021 Oct 22. PMID: 34678077; PMCID: PMC8677988.
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Accounting for misclassification in electronic health records-derived exposures using generalized linear finite mixture models.

Health services & outcomes research methodology

Hubbard RA, Johnson E, Chubak J, Wernli KJ, Kamineni A, Bogart A, Rutter CM.
PMID: 28943779
Health Serv Outcomes Res Methodol. 2017 Jun;17(2):101-112. doi: 10.1007/s10742-016-0149-5. Epub 2016 Jun 03.

Exposures derived from electronic health records (EHR) may be misclassified, leading to biased estimates of their association with outcomes of interest. An example of this problem arises in the context of cancer screening where test indication, the purpose for...

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Hubbard RA, Johnson E, Chubak J, et al. Accounting for misclassification in electronic health records-derived exposures using generalized linear finite mixture models. Health Serv Outcomes Res Methodol. 2016;17(2):101-112doi: 10.1007/s10742-016-0149-5.
Hubbard, R. A., Johnson, E., Chubak, J., Wernli, K. J., Kamineni, A., Bogart, A., & Rutter, C. M. (2017). Accounting for misclassification in electronic health records-derived exposures using generalized linear finite mixture models. Health services & outcomes research methodology, 17(2), 101-112. https://doi.org/10.1007/s10742-016-0149-5
Hubbard, Rebecca A, et al. "Accounting for misclassification in electronic health records-derived exposures using generalized linear finite mixture models." Health services & outcomes research methodology vol. 17,2 (2017): 101-112. doi: https://doi.org/10.1007/s10742-016-0149-5
Hubbard RA, Johnson E, Chubak J, Wernli KJ, Kamineni A, Bogart A, Rutter CM. Accounting for misclassification in electronic health records-derived exposures using generalized linear finite mixture models. Health Serv Outcomes Res Methodol. 2017 Jun;17(2):101-112. doi: 10.1007/s10742-016-0149-5. Epub 2016 Jun 03. PMID: 28943779; PMCID: PMC5608281.
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Risk Models for Breast Cancer and Their Validation.

Statistical science : a review journal of the Institute of Mathematical Statistics

Brentnall AR, Cuzick J.
PMID: 32226220
Stat Sci. 2020 Mar 03;35(1):14-30. doi: 10.1214/19-STS729.

Strategies to prevent cancer and diagnose it early when it is most treatable are needed to reduce the public health burden from rising disease incidence. Risk assessment is playing an increasingly important role in targeting individuals in need of...

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Brentnall AR, Cuzick J. Risk Models for Breast Cancer and Their Validation. Stat Sci. 2020;35(1):14-30doi: 10.1214/19-STS729.
Brentnall, A. R., & Cuzick, J. (2020). Risk Models for Breast Cancer and Their Validation. Statistical science : a review journal of the Institute of Mathematical Statistics, 35(1), 14-30. https://doi.org/10.1214/19-STS729
Brentnall, Adam R, and Cuzick, Jack. "Risk Models for Breast Cancer and Their Validation." Statistical science : a review journal of the Institute of Mathematical Statistics vol. 35,1 (2020): 14-30. doi: https://doi.org/10.1214/19-STS729
Brentnall AR, Cuzick J. Risk Models for Breast Cancer and Their Validation. Stat Sci. 2020 Mar 03;35(1):14-30. doi: 10.1214/19-STS729. PMID: 32226220; PMCID: PMC7100774.
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Genetically Inferred Telomere Length and Testicular Germ Cell Tumor Risk.

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology

Brown DW, Lan Q, Rothman N, Pluta J, Almstrup K, Dalgaard MD, Greene MH, Grotmol T, Loveday C, Schwartz SM, Turnbull C, Wiklund F, Kanetsky PA, Nathanson KL, McGlynn KA, Machiela MJ.
PMID: 33737296
Cancer Epidemiol Biomarkers Prev. 2021 Jun;30(6):1275-1278. doi: 10.1158/1055-9965.EPI-20-1775. Epub 2021 Mar 18.

BACKGROUND: Studies evaluating the association between peripheral blood leukocyte telomere length (LTL) and testicular germ cell tumor (TGCT) risk have produced conflicting results.METHODS: Using available genotype data from the Testicular Cancer Consortium (TECAC), polygenic risk score and Mendelian randomization...

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Brown DW, Lan Q, Rothman N, et al. Genetically Inferred Telomere Length and Testicular Germ Cell Tumor Risk. Cancer Epidemiol Biomarkers Prev. 2021;30(6):1275-1278doi: 10.1158/1055-9965.EPI-20-1775.
Brown, D. W., Lan, Q., Rothman, N., Pluta, J., Almstrup, K., Dalgaard, M. D., Greene, M. H., Grotmol, T., Loveday, C., Schwartz, S. M., Turnbull, C., Wiklund, F., Kanetsky, P. A., Nathanson, K. L., McGlynn, K. A., Machiela, M. J. (2021). Genetically Inferred Telomere Length and Testicular Germ Cell Tumor Risk. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 30(6), 1275-1278. https://doi.org/10.1158/1055-9965.EPI-20-1775
Brown, Derek W, et al. "Genetically Inferred Telomere Length and Testicular Germ Cell Tumor Risk." Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology vol. 30,6 (2021): 1275-1278. doi: https://doi.org/10.1158/1055-9965.EPI-20-1775
Brown DW, Lan Q, Rothman N, Pluta J, Almstrup K, Dalgaard MD, Greene MH, Grotmol T, Loveday C, Schwartz SM, Turnbull C, Wiklund F, Kanetsky PA, Nathanson KL, McGlynn KA, Machiela MJ. Genetically Inferred Telomere Length and Testicular Germ Cell Tumor Risk. Cancer Epidemiol Biomarkers Prev. 2021 Jun;30(6):1275-1278. doi: 10.1158/1055-9965.EPI-20-1775. Epub 2021 Mar 18. PMID: 33737296; PMCID: PMC8172526.
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Genetically Inferred Telomere Length and Testicular Germ Cell Tumor Risk.

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology

Brown DW, Lan Q, Rothman N, Pluta J, Almstrup K, Dalgaard MD, Greene MH, Grotmol T, Loveday C, Schwartz SM, Turnbull C, Wiklund F, Kanetsky PA, Nathanson KL, McGlynn KA, Machiela MJ.
PMID: 33737296
Cancer Epidemiol Biomarkers Prev. 2021 Jun;30(6):1275-1278. doi: 10.1158/1055-9965.EPI-20-1775. Epub 2021 Mar 18.

BACKGROUND: Studies evaluating the association between peripheral blood leukocyte telomere length (LTL) and testicular germ cell tumor (TGCT) risk have produced conflicting results.METHODS: Using available genotype data from the Testicular Cancer Consortium (TECAC), polygenic risk score and Mendelian randomization...

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Brown DW, Lan Q, Rothman N, et al. Genetically Inferred Telomere Length and Testicular Germ Cell Tumor Risk. Cancer Epidemiol Biomarkers Prev. 2021;30(6):1275-1278doi: 10.1158/1055-9965.EPI-20-1775.
Brown, D. W., Lan, Q., Rothman, N., Pluta, J., Almstrup, K., Dalgaard, M. D., Greene, M. H., Grotmol, T., Loveday, C., Schwartz, S. M., Turnbull, C., Wiklund, F., Kanetsky, P. A., Nathanson, K. L., McGlynn, K. A., Machiela, M. J. (2021). Genetically Inferred Telomere Length and Testicular Germ Cell Tumor Risk. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 30(6), 1275-1278. https://doi.org/10.1158/1055-9965.EPI-20-1775
Brown, Derek W, et al. "Genetically Inferred Telomere Length and Testicular Germ Cell Tumor Risk." Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology vol. 30,6 (2021): 1275-1278. doi: https://doi.org/10.1158/1055-9965.EPI-20-1775
Brown DW, Lan Q, Rothman N, Pluta J, Almstrup K, Dalgaard MD, Greene MH, Grotmol T, Loveday C, Schwartz SM, Turnbull C, Wiklund F, Kanetsky PA, Nathanson KL, McGlynn KA, Machiela MJ. Genetically Inferred Telomere Length and Testicular Germ Cell Tumor Risk. Cancer Epidemiol Biomarkers Prev. 2021 Jun;30(6):1275-1278. doi: 10.1158/1055-9965.EPI-20-1775. Epub 2021 Mar 18. PMID: 33737296; PMCID: PMC8172526.
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Solid Organ Transplantation and Survival among Individuals with a History of Cancer.

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology

Engels EA, Haber G, Hart A, Lynch CF, Li J, Pawlish KS, Qiao B, Yu KJ, Pfeiffer RM.
PMID: 33926864
Cancer Epidemiol Biomarkers Prev. 2021 Jul;30(7):1312-1319. doi: 10.1158/1055-9965.EPI-21-0044. Epub 2021 Apr 29.

BACKGROUND: The success of immunotherapy highlights a possible role for immunity in controlling cancer during remission for patients with cancer in the general population. A prior cancer diagnosis is common among solid organ transplant candidates, and immunosuppressive medications administered...

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Engels EA, Haber G, Hart A, et al. Solid Organ Transplantation and Survival among Individuals with a History of Cancer. Cancer Epidemiol Biomarkers Prev. 2021;30(7):1312-1319doi: 10.1158/1055-9965.EPI-21-0044.
Engels, E. A., Haber, G., Hart, A., Lynch, C. F., Li, J., Pawlish, K. S., Qiao, B., Yu, K. J., & Pfeiffer, R. M. (2021). Solid Organ Transplantation and Survival among Individuals with a History of Cancer. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 30(7), 1312-1319. https://doi.org/10.1158/1055-9965.EPI-21-0044
Engels, Eric A, et al. "Solid Organ Transplantation and Survival among Individuals with a History of Cancer." Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology vol. 30,7 (2021): 1312-1319. doi: https://doi.org/10.1158/1055-9965.EPI-21-0044
Engels EA, Haber G, Hart A, Lynch CF, Li J, Pawlish KS, Qiao B, Yu KJ, Pfeiffer RM. Solid Organ Transplantation and Survival among Individuals with a History of Cancer. Cancer Epidemiol Biomarkers Prev. 2021 Jul;30(7):1312-1319. doi: 10.1158/1055-9965.EPI-21-0044. Epub 2021 Apr 29. PMID: 33926864; PMCID: PMC8254777.
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Association of Preexisting Symptoms with Treatment Decisions among Newly Diagnosed Prostate Cancer Patients.

The patient

Zeliadt SB, Ramsey SD, Potosky AL, Arora NK, Blough DK, Oakley-Girvan I, Hamilton AS, Van Den Eeden SK, Penson DF.
PMID: 20119493
Patient. 2008 Jul 01;1(3):189. doi: 10.2165/1312067-200801030-00006.

BACKGROUND: The choice between surgical versus non-surgical treatment options is a fundamental decision for men with local stage prostate cancer because of differences in risks of genitourinary side effects among available treatments. OBJECTIVES: We assessed whether preexisting genitourinary symptoms...

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Zeliadt SB, Ramsey SD, Potosky AL, et al. Association of Preexisting Symptoms with Treatment Decisions among Newly Diagnosed Prostate Cancer Patients. Patient. 2008;1(3):189doi: 10.2165/1312067-200801030-00006.
Zeliadt, S. B., Ramsey, S. D., Potosky, A. L., Arora, N. K., Blough, D. K., Oakley-Girvan, I., Hamilton, A. S., Van Den Eeden, S. K., & Penson, D. F. (2008). Association of Preexisting Symptoms with Treatment Decisions among Newly Diagnosed Prostate Cancer Patients. The patient, 1(3), 189. https://doi.org/10.2165/1312067-200801030-00006
Zeliadt, Steven B, et al. "Association of Preexisting Symptoms with Treatment Decisions among Newly Diagnosed Prostate Cancer Patients." The patient vol. 1,3 (2008): 189. doi: https://doi.org/10.2165/1312067-200801030-00006
Zeliadt SB, Ramsey SD, Potosky AL, Arora NK, Blough DK, Oakley-Girvan I, Hamilton AS, Van Den Eeden SK, Penson DF. Association of Preexisting Symptoms with Treatment Decisions among Newly Diagnosed Prostate Cancer Patients. Patient. 2008 Jul 01;1(3):189. doi: 10.2165/1312067-200801030-00006. PMID: 20119493; PMCID: PMC2812903.
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Predictors of preoperative MRI for breast cancer: differences by data source.

Journal of comparative effectiveness research

Loggers ET, Gao H, Gold LS, Kessler L, Etzioni R, Buist DS.
PMID: 25960128
J Comp Eff Res. 2015 May;4(3):215-226. doi: 10.2217/cer.15.1. Epub 2015 May 11.

AIM: Investigate how the results of predictive models of preoperative MRI for breast cancer change based on available data.MATERIALS & METHODS: A total of 1919 insured women aged ≥18 with stage 0-III breast cancer diagnosed 2002-2009. Four models were...

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Loggers ET, Gao H, Gold LS, et al. Predictors of preoperative MRI for breast cancer: differences by data source. J Comp Eff Res. 2015;4(3):215-226doi: 10.2217/cer.15.1.
Loggers, E. T., Gao, H., Gold, L. S., Kessler, L., Etzioni, R., Buist, D. S. (2015). Predictors of preoperative MRI for breast cancer: differences by data source. Journal of comparative effectiveness research, 4(3), 215-226. https://doi.org/10.2217/cer.15.1
Loggers, Elizabeth T, et al. "Predictors of preoperative MRI for breast cancer: differences by data source." Journal of comparative effectiveness research vol. 4,3 (2015): 215-226. doi: https://doi.org/10.2217/cer.15.1
Loggers ET, Gao H, Gold LS, Kessler L, Etzioni R, Buist DS. Predictors of preoperative MRI for breast cancer: differences by data source. J Comp Eff Res. 2015 May;4(3):215-226. doi: 10.2217/cer.15.1. Epub 2015 May 11. PMID: 25960128; PMCID: PMC4641841.
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Showing 1 to 12 of 16 entries