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1. Taking the message to the rural patient: evidence-based PTSD care

Author

Bernardy, Nancy C., Montano, Macgregor, Cuccurullo, Lisa-Ann, Breen, Kristen, and Cole, Bernard F.

Subjects
Diagnosis, Care and treatment, Risk factors, Methods, Dosage and administration, Benzodiazepines -- Dosage and administration, Evidence-based medicine -- Methods, Post-traumatic stress disorder -- Risk factors -- Diagnosis -- Care and treatment
Abstract

Author(s): Nancy C. Bernardy [sup.1] [sup.2] , Macgregor Montano [sup.1] [sup.3] , Lisa-Ann Cuccurullo [sup.1] , Kristen Breen [sup.1] , Bernard F. Cole [sup.4] Author Affiliations: (1) grid.413726.5, 0000 0004 [...], The Department of Veterans Affairs and Department of Defense (VA/DoD) Clinical Practice Guideline for PTSD recommends against the use of benzodiazepines. Despite the recommendation, clinicians continue potentially inappropriate benzodiazepine prescribing practices for veterans with PTSD. We designed an educational product aimed at decreasing benzodiazepine use in PTSD care. Using VA data, the booklet was mailed to over 1300 New England veterans. Veterans were advised to discuss the booklet's information with their medical provider on their next appointment. The intervention resulted in a significant decrease in benzodiazepine use in veterans with PTSD, with 66% of the sample showing a dose reduction from pre- to post-booklet time points. Longitudinal analyses noted that rural veterans were significantly more likely to reduce benzodiazepine use than those in urban settings. Direct to consumer education appears to be an effective strategy to empower rural veterans to improve benzodiazepine prescribing safety and quality.

Published
2021
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3. Subpopulation Treatment Effect Pattern Plot (STEPP) analysis for continuous, binary, and count outcomes

Author

Yip, Wai-Ki, Bonetti, Marco, Cole, Bernard F, Barcella, William, Wang, Xin Victoria, Lazar, Ann, and Gelber, Richard D

Subjects
Mathematical Sciences, Biomedical and Clinical Sciences, Statistics, Precision Medicine, Clinical Research, Networking and Information Technology R&D (NITRD), Good Health and Well Being, Adenoma, Aspirin, Biomarkers, Tumor, Colorectal Neoplasms, Data Interpretation, Statistical, Folic Acid, Humans, Models, Statistical, Randomized Controlled Trials as Topic, Risk, Survival Analysis, Treatment Outcome, Generalized linear model, randomized clinical trial, subgroup analysis, Subpopulation Treatment Effect Pattern Plot, Clinical Sciences, Statistics & Probability, Clinical sciences, Clinical and health psychology
Abstract

BackgroundFor the past few decades, randomized clinical trials have provided evidence for effective treatments by comparing several competing therapies. Their successes have led to numerous new therapies to combat many diseases. However, since their conclusions are based on the entire cohort in the trial, the treatment recommendation is for everyone, and may not be the best option for an individual. Medical research is now focusing more on providing personalized care for patients, which requires investigating how patient characteristics, including novel biomarkers, modify the effect of current treatment modalities. This is known as heterogeneity of treatment effects. A better understanding of the interaction between treatment and patient-specific prognostic factors will enable practitioners to expand the availability of tailored therapies, with the ultimate goal of improving patient outcomes. The Subpopulation Treatment Effect Pattern Plot (STEPP) approach was developed to allow researchers to investigate the heterogeneity of treatment effects on survival outcomes across values of a (continuously measured) covariate, such as a biomarker measurement.MethodsHere, we extend the Subpopulation Treatment Effect Pattern Plot approach to continuous, binary, and count outcomes, which can be easily modeled using generalized linear models. With this extension of Subpopulation Treatment Effect Pattern Plot, these additional types of treatment effects within subpopulations defined with respect to a covariate of interest can be estimated, and the statistical significance of any observed heterogeneity of treatment effect can be assessed using permutation tests. The desirable feature that commonly used models are applied to well-defined patient subgroups to estimate treatment effects is retained in this extension.ResultsWe describe a simulation study to confirm that the proper Type I error rate is maintained when there is no treatment heterogeneity, and a power study to show that the statistics have power to detect treatment heterogeneity under alternative scenarios. As an illustration, we apply the methods to data from the Aspirin/Folate Polyp Prevention Study, a clinical trial evaluating the effect of oral aspirin, folic acid, or both as a chemoprevention agent against colorectal adenomas. The pre-existing R software package stepp has been extended to handle continuous, binary, and count data using Gaussian, Bernoulli, and Poisson models, and it is available on the Comprehensive R Archive Network.ConclusionThe extension of the method and the availability of new software now permit STEPP to be applied to the full range of clinical trial end points.

Published
2016

4. Identifying treatment effect heterogeneity in clinical trials using subpopulations of events: STEPP

Author

Lazar, Ann A, Bonetti, Marco, Cole, Bernard F, Yip, Wai-ki, and Gelber, Richard D

Subjects
Mathematical Sciences, Biomedical and Clinical Sciences, Statistics, Oncology and Carcinogenesis, Cancer, Clinical Research, Women's Health, Aging, Breast Cancer, Clinical Trials and Supportive Activities, 6.1 Pharmaceuticals, Antineoplastic Agents, Antineoplastic Agents, Hormonal, Biomarkers, Tumor, Breast Neoplasms, Data Interpretation, Statistical, Double-Blind Method, Female, Humans, Letrozole, Nitriles, Outcome Assessment, Health Care, Research Design, Tamoxifen, Treatment Outcome, Triazoles, Biomarker, breast cancer, competing risk, interaction, permutation-based inference, personalized medicine, precision medicine, survival analysis, overview, Clinical Sciences, Statistics & Probability, Clinical sciences, Clinical and health psychology
Abstract

BackgroundInvestigators conducting randomized clinical trials often explore treatment effect heterogeneity to assess whether treatment efficacy varies according to patient characteristics. Identifying heterogeneity is central to making informed personalized healthcare decisions. Treatment effect heterogeneity can be investigated using subpopulation treatment effect pattern plot (STEPP), a non-parametric graphical approach that constructs overlapping patient subpopulations with varying values of a characteristic. Procedures for statistical testing using subpopulation treatment effect pattern plot when the endpoint of interest is survival remain an area of active investigation.MethodsA STEPP analysis was used to explore patterns of absolute and relative treatment effects for varying levels of a breast cancer biomarker, Ki-67, in the phase III Breast International Group 1-98 randomized clinical trial, comparing letrozole to tamoxifen as adjuvant therapy for postmenopausal women with hormone receptor-positive breast cancer. Absolute treatment effects were measured by differences in 4-year cumulative incidence of breast cancer recurrence, while relative effects were measured by the subdistribution hazard ratio in the presence of competing risks using O-E (observed-minus-expected) methodology, an intuitive non-parametric method. While estimation of hazard ratio values based on O-E methodology has been shown, a similar development for the subdistribution hazard ratio has not. Furthermore, we observed that the subpopulation treatment effect pattern plot analysis may not produce results, even with 100 patients within each subpopulation. After further investigation through simulation studies, we observed inflation of the type I error rate of the traditional test statistic and sometimes singular variance-covariance matrix estimates that may lead to results not being produced. This is due to the lack of sufficient number of events within the subpopulations, which we refer to as instability of the subpopulation treatment effect pattern plot analysis. We introduce methodology designed to improve stability of the subpopulation treatment effect pattern plot analysis and generalize O-E methodology to the competing risks setting. Simulation studies were designed to assess the type I error rate of the tests for a variety of treatment effect measures, including subdistribution hazard ratio based on O-E estimation. This subpopulation treatment effect pattern plot methodology and standard regression modeling were used to evaluate heterogeneity of Ki-67 in the Breast International Group 1-98 randomized clinical trial.ResultsWe introduce methodology that generalizes O-E methodology to the competing risks setting and that improves stability of the STEPP analysis by pre-specifying the number of events across subpopulations while controlling the type I error rate. The subpopulation treatment effect pattern plot analysis of the Breast International Group 1-98 randomized clinical trial showed that patients with high Ki-67 percentages may benefit most from letrozole, while heterogeneity was not detected using standard regression modeling.ConclusionThe STEPP methodology can be used to study complex patterns of treatment effect heterogeneity, as illustrated in the Breast International Group 1-98 randomized clinical trial. For the subpopulation treatment effect pattern plot analysis, we recommend a minimum of 20 events within each subpopulation.

Published
2016

6. Axillary dissection versus no axillary dissection in patients with breast cancer and sentinel-node micrometastases (IBCSG 23-01): 10-year follow-up of a randomised, controlled phase 3 trial

Author

Boyle, Fran, Jerusalem, Guy, Stahel, Rolf, Aebi, Stefan, Green, Michael, Karlsson, Per, Kössler, Ingrid, Láng, Istvan, Hiltbrunner, Anita, Bernhard, Jürg, Fournarakou, Stamatina, Kammler, Roswitha, Maibach, Rudolf, Rabaglio, Manuela, Ribi, Karin, Roschitzki, Heidi, Roux, Susanne, Ruepp, Barbara, Mahoney, Caitlin, Price, Karen, Blacher, Lynette, Scolese, Tara, Scott, Karolyn, Lippert, Sandra, Zielinski, Theresa, Mastropasqua, Mauro, Andrighetto, Stefania, Dell'Orto, Patrizia, Renne, Giuseppe, Pruneri, Giancarlo, Dellapasqua, Silvia, Iorfida, Monica, Cancello, Giuseppe, Montagna, Emilia, Cardillo, Anna, Peruzzotti, Giulia, Ghisini, Raffaella, Luini, Alberto, Veronesi, Umberto, Intra, Mattia, Gentilini, Oreste, Zurrida, Stefano, Curigliano, Giuseppe, Nole, Franco, Orecchia, Roberto, Leonardi, Marisa Cristina, Baratella, Paola, Chifu, Camelia, Sargenti, Manuela, Crivellari, Diana, Morassut, Sandro, Mileto, Mario, Piccoli, Erica, Veronesi, Andreas, Magri, Marisa Donatella, Buonadonna, Angelo, Candiani, Ezio, Carbone, Antonino, Perin, Tiziana, Volpe, Rachele, Roncadin, Mario, Arcicasa, Mauro, Coran, Francesco, Lagrassa, Manuela, Recalcati, Angelo, Limonta, Maria Emanuela, Tricomi, Paolo, Fenaroli, Privato, Candiago, Elisabetta, Cattaneo, Laura, Gianatti, Alberto, Santini, Donatella, Maweja, Sylvie, Delvenne, Philippe, Rorive, Andrée, Collignon, Joëlle, Garbay, Jean-Remi, Mathieu, Marie-Christine, Galatius, Hanne, Hoffmann, Jack, Schousen, Peer, Lanng, Charlotte, Hoerby, John, Bruun Rasmussen, Birgitte, Holtveg, Helle, Moeller Talman, Maj-Lis, Abugattas, Julio Elías, Cotrina, Jose Manuel, Dyer, Richard, Lindtner, Jurij, Majdic, Elga, Frkovic-Grazio, Snjezana, Oehlschlegel, Christian, Ries, Gerhard, Töpfer, Michael, Lorenz, Ute, Schiltknecht, Otto, Späti, Bruno, Ehrsam, Andreas, Bamert, Monika, Egli-Tupaj, Martina, Rageth, Christoph, Saurenmann, Elisabeth, Tausch, Christoph, Caduff, Rosmarie, Moch, Holger, Varga, Zsuzsanna, Sarlos, Dimitri, Kralidis, Elena, Grobholz, Rainer, Pagani, Olivia, Bronz, Lucia, Ghielmini, Michele, Mazzucchelli, Luca, Rusca, Tiziana, Gyr, Thomas, Leidi, Linda, Caccia, Giorgio, Wyss, Daniel, Fey, Martin F., Müller, Michael, Günthert, Andreas, Berclaz, Gilles, Fleischmann, Achim, Delaloye, Jean Francois, Treboux, Assia, Lehr, Hans-Anton, Fiche, Maryse, Perey, Lucien, Zaman, Lucien, Jeanneret Sozzi, Wendy, Forbes, John, Lindsay, D.F., Preece, D.F., Hill, Jane, Jeal, P., Smart, P., Collins, John, Mann, Gregory Bruce, Millar, Robert, Murphy, Craig, Buchanan, Malcolm, Murugasu, Anand, French, James, Elder, Elisabeth, Mann, Lynette, Moon, David, Bilous, A. Michael, Pathmanathan, Nirmala, Howard, Virginia, Gill, Petere G., Kollias, James, Bochner, Melissa, Madigan, Linda, Rippy, Elisabeth, Whitfield, Robert, Farshidi, Fereshte, Moore, Katrina, Sywak, Mark, Tan, L., Ross, William, Briscoe, Karen, Jones, Allison, Shah, Aashit, Lim, Elgene, Macindoe, Robert, Spillane, Andrew, Bonar, S. Fiona, Carmalt, Hugh, West, Richard, Mak, Cindy, McKenzie, Paul, Harman, Richard, Gerred, Susanne, Juhasz, Eva, Allpress, Stephen, Craik, Julie, Campbell, Ian, Chin, Paul, Hayes, Lori, Mayall, Frederick, Thorburn, M., Galimberti, Viviana, Cole, Bernard F, Viale, Giuseppe, Veronesi, Paolo, Vicini, Elisa, Mazzarol, Giovanni, Massarut, Samuele, Zgajnar, Janez, Taffurelli, Mario, Littlejohn, David, Knauer, Michael, Tondini, Carlo, Di Leo, Angelo, Colleoni, Marco, Regan, Meredith M, Coates, Alan S, Gelber, Richard D, and Goldhirsch, Aron

Published
2018
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13. Weekly vs Every-3-Week Carboplatin with Weekly Paclitaxel in Neoadjuvant Chemotherapy for Triple-Negative Breast Cancer: A Retrospective Analysis

Author

Landry,Kara K, Lyon,Jessica L, Victoria,Kitty E, Changizzadeh,P Nick, Cole,Bernard F, Pulluri,Bhargavi, Sikov,William M, Wood,Marie E, Landry,Kara K, Lyon,Jessica L, Victoria,Kitty E, Changizzadeh,P Nick, Cole,Bernard F, Pulluri,Bhargavi, Sikov,William M, and Wood,Marie E

Abstract

Kara K Landry,1 Jessica L Lyon,2 Kitty E Victoria,1 P Nick Changizzadeh,3 Bernard F Cole,4 Bhargavi Pulluri,5 William M Sikov,6 Marie E Wood1 1Division of Hematology and Oncology, Department of Medicine, University of Vermont Medical Center, Burlington, VT, USA; 2Larner College of Medicine at the University of Vermont, Burlington, VA, USA; 3Hematology and Oncology, Eastern Connecticut Hematology and Oncology, Norwich, CT, USA; 4College of Engineering and Mathematical Sciences, University of Vermont, Burlington, VA, USA; 5Division of Hematology and Oncology, Saint Agnes Hospital, Baltimore, MD, USA; 6Women and Infants Hospital of Rhode Island, Program in Women’s Oncology, and Warren Alpert Medical School of Brown University, Providence, RI, USACorrespondence: Marie E Wood, Department of Medicine, Division of Hematology and Oncology, University of Vermont Medical Center, 111 Colchester Avenue, Burlington, VA, 05401, USA, Tel +1 802-847-8400, Email marie.wood@uvmhealth.orgBackground: Adding carboplatin to weekly paclitaxel as part of neoadjuvant chemotherapy (NACT) for stage II–III triple negative breast cancer (TNBC) has been shown to significantly increase the pathologic complete response (pCR) rate. Hematologic toxicities associated with every 3-week dosing of carboplatin have led some oncologists to explore weekly dosing as an alternative, but there are little published data comparing the two dosing schedules.Methods: We performed a retrospective analysis of patients who received paclitaxel and carboplatin, usually followed by AC, as initial NACT for TNBC at two academic cancer centers between 2008 and 2018 for whom pathologic results and post-operative follow-up were available. We recorded pCR, defined as ypT0/isN0, treatment delivery and disease-free survival, censored as of the patient’s last follow-up visit.Results: A total of 76 patients were identified (median age 49 years). A total of 47 received weekly carboplatin, of whom 83% received at least 11 of

Published
2022

16. Six-year absolute invasive disease-free survival benefit of adding adjuvant pertuzumab to trastuzumab and chemotherapy for patients with early HER2-positive breast cancer: A Subpopulation Treatment Effect Pattern Plot (STEPP) analysis of the APHINITY (BIG 4-11) trial

Author

Gelber, Richard D., primary, Wang, Xin V., additional, Cole, Bernard F., additional, Cameron, David, additional, Cardoso, Fatima, additional, Tjan-Heijnen, Vivianne, additional, Krop, Ian, additional, Loi, Sherene, additional, Salgado, Roberto, additional, Kiermaier, Astrid, additional, Frank, Elizabeth, additional, Fumagalli, Debora, additional, Caballero, Carmela, additional, de Azambuja, Evandro, additional, Procter, Marion, additional, Clark, Emma, additional, Restuccia, Eleonora, additional, Heeson, Sarah, additional, Bines, Jose, additional, Loibl, Sibylle, additional, and Piccart-Gebhart, Martine, additional

Published
2022
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17. Subpopulation Treatment Effect Pattern Plot (STEPP) Methods with R and Stata

Author

Venturini, Sergio, Bonetti, Marco, Lazar, Ann A., Cole, Bernard F., Wang, Xin&nbsp, Victoria, Gelber, Richard D., and Yip, Wai-Ki

Subjects
Settore SECS-S/01 - STATISTICA, General Earth and Planetary Sciences, interaction, clinical trial, treatment-covariate interaction, subgroup analysis, subpopulation, General Environmental Science, clinical trial, interaction, subgroup analysis, subpopulation, treatment-covariate interaction
Abstract

We introduce the stepp packages for R and Stata that implement the subpopulation treatment effect pattern plot (STEPP) method. STEPP is a nonparametric graphical tool aimed at examining possible heterogeneous treatment effects in subpopulations defined on a continuous covariate or composite score. More pecifically, STEPP considers overlapping subpopulations defined with respect to a continuous covariate (or risk index) and it estimates a treatment effect for each subpopulation. It also produces confidence regions and tests for treatment effect heterogeneity among the subpopulations. The original method has been extended in different directions such as different survival contexts, outcome types, or more efficient procedures for identifying the overlapping subpopulations. In this paper, we also introduce a novel method to determine the number of subjects within the subpopulations by minimizing the variability of the sizes of the subpopulations generated by a specific parameter combination. We illustrate the packages using both synthetic data and publicly available data sets. The most intensive computations in R are implemented in Fortran, while the Stata version exploits the powerful Mata language.

Published
2022

24. A Trial of Calcium and Vitamin D for the Prevention of Colorectal Adenomas

Author

Baron, John A., Barry, Elizabeth L., Mott, Leila A., Rees, Judy R., Sandler, Robert S., Snover, Dale C., Bostick, Roberd M., Ivanova, Anastasia, Cole, Bernard F., Ahnen, Dennis J., Beck, Gerald J., Bresalier, Robert S., Burke, Carol A., Church, Timothy R., Cruz-Correa, Marcia, Figueiredo, Jane C., Goodman, Michael, Kim, Adam S., Robertson, Douglas J., Rothstein, Richard, Shaukat, Aasma, Seabrook, March E., and Summers, Robert W.

Published
2015
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27. Subpopulation Treatment Effect Pattern Plot (STEPP) Methods with R and Stata.

Author

VENTURINI, SERGIO, BONETTI, MARCO, LAZAR, ANN A., COLE, BERNARD F., WANG, XIN VICTORIA, GELBER, RICHARD D., WAI-KI, and YIP

Subjects
TREATMENT effectiveness, CONFIDENCE regions (Mathematics), CONFIDENCE intervals, FORTRAN
Abstract

We introduce the stepp packages for R and Stata that implement the subpopulation treatment effect pattern plot (STEPP) method. STEPP is a nonparametric graphical tool aimed at examining possible heterogeneous treatment effects in subpopulations defined on a continuous covariate or composite score. More pecifically, STEPP considers overlapping subpopulations defined with respect to a continuous covariate (or risk index) and it estimates a treatment effect for each subpopulation. It also produces confidence regions and tests for treatment effect heterogeneity among the subpopulations. The original method has been extended in different directions such as different survival contexts, outcome types, or more efficient procedures for identifying the overlapping subpopulations. In this paper, we also introduce a novel method to determine the number of subjects within the subpopulations by minimizing the variability of the sizes of the subpopulations generated by a specific parameter combination. We illustrate the packages using both synthetic data and publicly available data sets. The most intensive computations in R are implemented in Fortran, while the Stata version exploits the powerful Mata language. [ABSTRACT FROM AUTHOR]

Published
2023
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31. Preoperative systemic therapy in locoregional management of early breast cancer: highlights from the Kyoto Breast Cancer Consensus Conference

Author

Toi, Masakazu, Benson, John R., Winer, Eric P., Forbes, John F., von Minckwitz, Gunter, Golshan, Mehra, Robertson, John F. R., Sasano, Hironobu, Cole, Bernard F., Chow, Louis W. C., Pegram, Mark D., Han, Wonshik, Huang, Chiun-Sheng, Ikeda, Tadashi, Kanao, Shotaro, Lee, Eun-Sook, Noguchi, Shinzaburo, Ohno, Shinji, Partridge, Ann H., Rouzier, Roman, Tozaki, Mitsuhiro, Sugie, Tomoharu, Yamauchi, Akira, and Inamoto, Takashi

Published
2012
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37. A simple assessment of lung nodule location for reduction in unnecessary invasive procedures

Author

Kinsey, C. Matthew, primary, Billatos, Ehab, additional, Mori, Vitor, additional, Tonelli, Ben, additional, Cole, Bernard F., additional, Duan, Fenghai, additional, Marques, Helga, additional, de la Bruere, Isaac, additional, Onieva, Jorge, additional, San José Estépar, Rubén, additional, Cleveland, Alyx, additional, Idelkope, Dan, additional, Stevenson, Chris, additional, Bates, Jason H. T., additional, Aberle, Denise, additional, Spira, Avi, additional, Washko, George, additional, and San José Estépar, Raúl, additional

Published
2021
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38. Anemia during adjuvant non-taxane chemotherapy for early breast cancer: Incidence and risk factors from two trials of the International Breast Cancer Study Group

Author

Gianni, Lorenzo, Cole, Bernard F., Panzini, Ilaria, Snyder, Raymond, Holmberg, Stig B., Byrne, Michael, Crivellari, Diana, Colleoni, Marco, Aebi, Stefan, Simoncini, Edda, Pagani, Olivia, Castiglione-Gertsch, Monica, Price, Karen N., Goldhirsch, Aron, Coates, Alan S., and Ravaioli, Alberto

Published
2008
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39. Clinical behavior of recurrent hormone receptor–positive breast cancer by adjuvant endocrine therapy within the Breast International Group 1-98 clinical trial

Author

Leone, Jose P., Cole, Bernard F., Regan, Meredith M., Thürlimann, Beat, Coates, Alan S., Rabaglio, Manuela, Giobbie-Hurder, Anita, Gelber, Richard D., Ejlertsen, Bent, Harvey, Vernon J., Neven, Patrick, Láng, Istvan, Bonnefoi, Herve, Wardley, Andrew, Goldhirsch, Aron, Di Leo, Angelo, Colleoni, Marco, Vaz-Luis, Ines, Lin, Nancy U., Leone, Jose P., Cole, Bernard F., Regan, Meredith M., Thürlimann, Beat, Coates, Alan S., Rabaglio, Manuela, Giobbie-Hurder, Anita, Gelber, Richard D., Ejlertsen, Bent, Harvey, Vernon J., Neven, Patrick, Láng, Istvan, Bonnefoi, Herve, Wardley, Andrew, Goldhirsch, Aron, Di Leo, Angelo, Colleoni, Marco, Vaz-Luis, Ines, and Lin, Nancy U.

Abstract

Background: Endocrine therapy resistance is a major cause of distant recurrence (DR) in hormone receptor–positive breast cancer. This study evaluated differences in survival after DR in patients treated with different adjuvant endocrine therapy regimens in the Breast International Group (BIG) 1-98 trial. Methods: BIG 1-98 compared 5 years of adjuvant treatment among 4 arms: tamoxifen (T), letrozole (L), tamoxifen followed by letrozole (TL), and letrozole followed by tamoxifen (LT). After a median follow-up of 8.1 years, 911 of 8010 patients (T, 302; L, 285; TL, 170; and LT, 154) had DR as the site of first recurrence. Univariate and multivariate Cox analyses were performed to determine features associated with post-DR survival. Results: The median follow-up time after DR was 59 months (interquartile range, 29-88 months). Among all patients with DR, 38.1% were 65 years old or older at enrollment, 61.9% had tumors larger than 2 cm, and 69.7% were node positive. Neoadjuvant or adjuvant chemotherapy was administered to 35.6% of the patients. There was no difference in post-DR survival by treatment arm (median survival, 20.8 months for T, 17.9 months for L, 17.3 months for TL, and 20.8 months for LT; P =.21). In multivariate analysis, older patients (hazard ratio [HR], 1.35; 95% confidence interval [CI], 1.15-1.59) and patients with tumors larger than 2 cm (HR, 1.19; 95% CI, 1.00-1.41), 4 or more positive nodes (HR, 1.31; 95% CI, 1.05-1.64), progesterone receptor (PR)–negative tumors (HR, 1.25; 95% CI, 1.02-1.52), or shorter disease-free survival (DFS) had significantly worse post-DR survival. Conclusions: Treatment with adjuvant T, L, or their sequences was not associated with differences in survival after DR. Significant differences in survival were observed by age, primary tumor size, nodal and PR status, and DFS, and this suggests that traditional baseline high-risk features remain prognostic in the metastatic setting.

Published
2021

41. Folic acid for the prevention of colorectal adenomas

Author

Cole, Bernard F., Baron, John A., Sandler, Robert S., Haile, Robert W., Ahnen, Dennis J., Bresalier, Robert S., McKeown-Eyssen, Gail, Summers, Robert W., Rothstein, Richard I., Burke, Carol A., Snover, Dale C., Church, Timothy R., Allen, John I., Robertson, Douglas J., Beck, John H., Byers, Tim, Mandel, Jack S., Mott, Leila A., Pearson, Loretta H., Barry, Elizabeth L., Rees, Judy R., Marcon, Norman, Saibil, Fred, Ueland, Per Magne, and Greenberg, E.Robert

Subjects
Folic acid -- Health aspects, Colorectal cancer -- Prevention, Colorectal cancer -- Risk factors
Abstract

A clinical trial carried out to observe the safety and efficiency of folic acid supplements to prevent colorectal adenomas is presented. Its result states that it does not reduce the risk but increase the risk of having colorectal adenomas.

Published
2007

42. Docetaxel/Gemcitabine Followed by Gemcitabine and External Beam Radiotherapy in Patients With Pancreatic Adenocarcinoma

Author

Pipas, J. Marc, Barth, Jr., Richard J., Zaki, Bassem, Tsapakos, Michael J., Suriawinata, Arief A., Bettmann, Michael A., Cates, Justin M., Ripple, Gregory H., Sutton, John E., Gordon, Stuart R., McDonnell, Carol E., Perez, Raymond P., Redfield, Nancy, Meyer, Louise P., Marshall, John F., Cole, Bernard F., and Colacchio, Thomas A.

Published
2005
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44. High rates of clinical and subclinical tuberculosis among HIV-infected ambulatory subjects in Tanzania

Author

Mtei, Lillian, Matee, Mecky, Herfort, Oliver, Bakari, Muhammad, Horsburgh, C. Robert, Waddell, Richard, Cole, Bernard F., Vuola, Jenni M., Tvaroha, Susan, Kreiswirth, Barry, Pallangyo, Kisali, and von Reyn, C. Fordham

Subjects
Tuberculosis -- Risk factors, Tuberculosis -- Diagnosis, HIV infection -- Risk factors, HIV infection -- Diagnosis, HIV patients -- Health aspects, Health, Health care industry
Published
2005

46. A randomized trial of aspirin to prevent colorectal adenomas

Author

Baron, John A., Cole, Bernard F., Sandler, Robert S., Haile, Robert W., Ahnen, Dennis, Bresalier, Robert, McKeown-Eyssen, Gail, Summers, Robert W., Rothstein, Richard, Burke, Carol A., Snover, Dale C., Church, Timothy R., Allen, John I., Beach, Michael, Beck, Gerald J., Bond, John H., Byers, Tim, Greenberg, E. Robert, Mandel, Jack S., Marcon, Norman, Mott, Leila A., Pearson, Loretta, Saibil, Fred, and Stolk, Rosalind U. van

Subjects
Colorectal cancer -- Prevention, Aspirin -- Evaluation
Abstract

Low-doses of aspirin may prevent colorectal cancer from getting worse, according to a study of 1,121 patients who had recently been diagnosed with colorectal tumors. The progression of the cancer was slower in patients who took 81 milligrams of aspirin, compared to the patients who took 325 milligrams of aspirin or a placebo.

Published
2003

47. Boost radiotherapy in young women with ductal carcinoma in situ: a multicentre, retrospective study of the Rare Cancer Network

Author

Omlin, Aurelius, Amichetti, Maurizio, Azria, David, Cole, Bernard F, Fourneret, Philippe, Poortmans, Philip, Naehrig, Diana, Miller, Robert C, Krengli, Marco, Gutierrez Miguelez, Cristina, Morgan, David, Goldberg, Hadassah, Scandolaro, Luciano, Gastelblum, Pauline, Ozsahin, Mahmut, Dohr, Dagmar, Christie, David, Oppitz, Ulrich, Abacioglu, Ufuk, and Gruber, Guenther

Published
2006
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49. Abstract PS10-01: 6-year absolute invasive disease-free survival (IDFS) benefit of adding adjuvant pertuzumab to trastuzumab and chemotherapy for patients with early HER2-positive breast cancer: A STEPP analysis of the APHINITY (BIG 4-11) trial

Author

Gelber, Richard D., primary, Wang, Xin Victoria, additional, Cole, Bernard F., additional, Cameron, David, additional, Cardoso, Fatima, additional, Tjan-Heijnen, Vivianne, additional, Krop, Ian, additional, Loi, Sherene, additional, Salgado, Roberto, additional, Kiermaier, Astrid, additional, Frank, Elizabeth, additional, Fumagalli, Debora, additional, Caballero, Carmela, additional, de Azambuja, Evandro, additional, Procter, Marion, additional, Clark, Emma, additional, Restuccia, Eleonora, additional, Heeson, Sarah, additional, Bines, Jose, additional, Loibl, Sibylle, additional, and Piccart-Gebhardt, Martine, additional

Published
2021
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