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@article{Reganetal2016,
	abstract = { PurposeRisk of recurrence is the primary consideration in breast cancer adjuvant therapy recommendations. The TEXT (Tamoxifen and Exemestane Trial) and SOFT (Suppression of Ovarian Function Trial) trials investigated adjuvant endocrine therapies for premenopausal women with hormone receptor--positive breast cancer, testing exemestane plus ovarian function suppression (OFS), tamoxifen plus OFS, and tamoxifen alone. We examined absolute treatment effect across a continuum of recurrence risk to individualize endocrine therapy decision making for premenopausal women with human epidermal growth factor receptor 2 (HER2) --negative disease.Patients and MethodsThe TEXT and SOFT hormone receptor--positive, HER2-negative analysis population included 4,891 women. The end point was breast cancer--free interval (BCFI), defined as time from random assignment to first occurrence of invasive locoregional, distant, or contralateral breast cancer. A continuous, composite measure of recurrence risk for each patient was determined from a Cox model incorporating age, nodal status, tumor size and grade, and estrogen receptor, progesterone receptor, and Ki-67 expression levels. Subpopulation treatment effect pattern plot methodology revealed differential treatment effects on 5-year BCFI according to composite risk.ResultsSOFT patients who remained premenopausal after chemotherapy experienced absolute improvement of 5\% or more in 5-year BCFI with exemestane plus OFS versus tamoxifen plus OFS or tamoxifen alone, reaching 10\% to 15\% at intermediate to high composite risk; the benefit of tamoxifen plus OFS versus tamoxifen alone was apparent at the highest composite risk. The SOFT no-chemotherapy cohort---for whom composite risk was lowest on average---did well with all endocrine therapies. For TEXT patients, the benefit of exemestane plus OFS versus tamoxifen plus OFS in 5-year BCFI ranged from 5\% to 15\%; patients not receiving chemotherapy and with lowest composite risk did well with both treatments.ConclusionPremenopausal women with hormone receptor--positive, HER2-negative disease and high recurrence risk, as defined by clinicopathologic characteristics, may experience improvement of 10\% to 15\% in 5-year BCFI with exemestane plus OFS versus tamoxifen alone. An improvement of at least 5\% may be achieved for women at intermediate risk, and improvement is minimal for those at lowest risk. },
	author = {Regan, Meredith M. and Francis, Prudence A. and Pagani, Olivia and Fleming, Gini F. and Walley, Barbara A. and Viale, Giuseppe and Colleoni, Marco and L\'{a}ng, Istv\'{a}n and G\'{o}mez, Henry L. and Tondini, Carlo and Pinotti, Graziella and Price, Karen N. and Coates, Alan S. and Goldhirsch, Aron and Gelber, Richard D.},
	date-added = {2022-06-16 09:54:53 +0200},
	date-modified = {2022-06-16 09:54:53 +0200},
	doi = {10.1200/JCO.2015.64.3171},
	eprint = {https://doi.org/10.1200/JCO.2015.64.3171},
	journal = {Journal of Clinical Oncology},
	note = {PMID: 27044936},
	number = {19},
	pages = {2221-2231},
	title = {Absolute Benefit of Adjuvant Endocrine Therapies for Premenopausal Women With Hormone Receptor--Positive, Human Epidermal Growth Factor Receptor 2--Negative Early Breast Cancer: TEXT and SOFT Trials},
	url = {https://doi.org/10.1200/JCO.2015.64.3171},
	volume = {34},
	year = {2016},
	bdsk-url-1 = {https://doi.org/10.1200/JCO.2015.64.3171}}

@article{Vialeetal2011,
	abstract = {Background
On average, aromatase inhibitors are better than tamoxifen when used as initial or sequential therapy for postmenopausal women with endocrine-responsive early breast cancer. Because there may be contraindications to their use based on side-effects or cost, we investigated subgroups in which aromatase inhibitors may be more or less important.
Patients and methods
Breast International Group 1-98 trial randomized 6182 women among four groups comparing letrozole and tamoxifen with sequences of each agent; 5177 (84%) had centrally confirmed estrogen receptor (ER) positivity. We assessed whether centrally determined ER, progesterone receptor (PgR), human epidermal growth factor receptor 2, and Ki-67 labeling index, alone or in combination with other prognostic features, predicted the magnitude of letrozole effectiveness compared with either sequence or tamoxifen monotherapy.
Results
Individually, none of the markers significantly predicted differential treatment effects. Subpopulation treatment effect pattern plot analysis of a composite measure of prognostic risk revealed three patterns. Estimated 5-year disease-free survival for letrozole monotherapy, letrozole→tamoxifen, tamoxifen→letrozole, and tamoxifen monotherapy were 96%, 94%, 93%, and 94%, respectively, for patients at lowest risk; 90%, 91%, 93%, and 86%, respectively, for patients at intermediate risk; and 80%, 76%, 74%, and 69%, respectively, for patients at highest risk.
Conclusion
A composite measure of risk informs treatment selection better than individual biomarkers and supports the choice of 5 years of letrozole for patients at highest risk for recurrence.},
	author = {G. Viale and M.M. Regan and P. Dell'Orto and M.G. Mastropasqua and E. Maiorano and B.B. Rasmussen and G. MacGrogan and J.F. Forbes and R.J. Paridaens and M. Colleoni and I. L{\'a}ng and B. Th{\"u}rlimann and H. Mouridsen and L. Mauriac and R.D. Gelber and K.N. Price and A. Goldhirsch and B.A. Gusterson and A.S. Coates},
	date-added = {2022-06-16 09:53:12 +0200},
	date-modified = {2022-06-16 09:53:12 +0200},
	doi = {https://doi.org/10.1093/annonc/mdq738},
	issn = {0923-7534},
	journal = {Annals of Oncology},
	keywords = {aromatase inhibitor, breast cancer, prognostic factor, tamoxifen},
	number = {10},
	pages = {2201-2207},
	title = {Which patients benefit most from adjuvant aromatase inhibitors? Results using a composite measure of prognostic risk in the BIG 1-98 randomized trial},
	url = {https://www.sciencedirect.com/science/article/pii/S0923753419377427},
	volume = {22},
	year = {2011},
	bdsk-url-1 = {https://www.sciencedirect.com/science/article/pii/S0923753419377427},
	bdsk-url-2 = {https://doi.org/10.1093/annonc/mdq738}}

@article{Gelberetal2022,
	abstract = {Aim
The APHINITY trial showed that adding adjuvant pertuzumab (P) to trastuzumab and chemotherapy, compared with adding placebo (Pla), significantly improved invasive disease-free survival (IDFS) for patients with HER2+ early breast cancer both overall and for the node-positive (N+) cohort. We explored whether adding P could benefit some N− subpopulations and whether to consider de-escalation for some N+ subpopulations.
Methods
Subpopulation Treatment Effect Pattern Plot (STEPP) is an exploratory, graphical method that plots estimates of treatment effect for overlapping patient subpopulations defined by a covariate of interest. We used STEPP to estimate Kaplan--Meier differences in 6-year IDFS percentages (P minus Pla: Δ $\pm$ standard error [SE]), both overall and by nodal status, for overlapping subpopulations defined by (1) a clinical composite risk score, (2) tumour infiltrating lymphocytes (TILs) percentage, and (3) human epidermal growth factor receptor 2 (HER2) FISH copy number. Because of multiplicity, a Δ of at least three SE is required to warrant attention.
Results
The average absolute gains in 6-year IDFS percentages were 2.8 $\pm$ 0.9 overall; 4.5 $\pm$ 1.2 for N+ and 0.1 $\pm$ 1.1 for N−. Largest gains were for patients with intermediate clinical composite risk (5.3 $\pm$ 1.9 overall; 6.9 $\pm$ 2.3 N+; 4.0 $\pm$ 3.0 N−), highest TILs percentage (6.3 $\pm$ 1.7 overall; 7.4 $\pm$ 2.4 N+; 3.2 $\pm$ 1.7 N−), and intermediate HER2 copy number (2.8 $\pm$ 1.9 overall; 7.4 $\pm$ 2.5 N+; −1.3 $\pm$ 1.9 N−), but clear evidence indicating a pattern of differential subpopulation treatment effects was lacking.
Conclusions
STEPP plots for N− did not identify subpopulations clearly benefiting from adding P, and those for N+ did not identify subpopulations warranting de-escalation. TILs percentage appeared to be more predictive of P treatment effect than clinical composite risk score.
Trial registration
clinicaltrials.gov Identifier NCT01358877.},
	author = {Richard D. Gelber and Xin V. Wang and Bernard F. Cole and David Cameron and Fatima Cardoso and Vivianne Tjan-Heijnen and Ian Krop and Sherene Loi and Roberto Salgado and Astrid Kiermaier and Elizabeth Frank and Debora Fumagalli and Carmela Caballero and Evandro {de Azambuja} and Marion Procter and Emma Clark and Eleonora Restuccia and Sarah Heeson and Jose Bines and Sibylle Loibl and Martine Piccart-Gebhart},
	date-added = {2022-06-16 09:17:13 +0200},
	date-modified = {2022-06-16 09:17:46 +0200},
	doi = {https://doi.org/10.1016/j.ejca.2022.01.031},
	issn = {0959-8049},
	journal = {European Journal of Cancer},
	keywords = {STEPP (Subpopulation Treatment Effect Pattern Plot), HER2-positive early breast cancer, Adjuvant therapy, Pertuzumab, Trastuzumab, TILs (tumour infiltrating lymphocytes)},
	pages = {219--228},
	title = {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},
	url = {https://www.sciencedirect.com/science/article/pii/S0959804922000648},
	volume = {166},
	year = {2022},
	bdsk-url-1 = {https://www.sciencedirect.com/science/article/pii/S0959804922000648},
	bdsk-url-2 = {https://doi.org/10.1016/j.ejca.2022.01.031}}

@article{Paganietal2020,
	abstract = { PURPOSE The Tamoxifen and Exemestane Trial (TEXT)/Suppression of Ovarian Function Trial (SOFT) showed superior outcomes for premenopausal women with hormone receptor (HR)--positive breast cancer treated with adjuvant exemestane plus ovarian function suppression (OFS) or tamoxifen plus OFS versus tamoxifen alone. We previously reported the magnitude of absolute improvements in freedom from any recurrence across a continuous, composite measure of recurrence risk to tailor decision making. With longer follow-up, we now focus on distant recurrence. METHODS The TEXT/SOFT HR-positive/human epidermal growth factor receptor 2 (HER2)--negative analysis population included 4,891 women stratified by predetermined chemotherapy use. Kaplan-Meier estimates of 8-year freedom from distant recurrence were analyzed using subpopulation treatment effect pattern plot (STEPP) methodology across subpopulations defined by the continuous composite measure of recurrence risk. For each patient, the composite risk value was obtained from a Cox model that incorporated age; nodal status; tumor size; grade; and estrogen receptor, progesterone receptor, and Ki-67 labeling index expression levels. RESULTS The overall rate of 8-year freedom from distant recurrence was 91.1\% and ranged from approximately 100\% to 63\% across lowest to highest composite risks. TEXT patients who received chemotherapy had an average absolute improvement with exemestane plus OFS versus tamoxifen plus OFS of 5.1\%, and STEPP analysis showed improvements from less than 1\% to more than 15\% from lowest to highest composite risks. SOFT patients who remained premenopausal after chemotherapy had an average 5.2\% absolute improvement with exemestane plus OFS versus tamoxifen and reached 10\% across composite risks; for tamoxifen plus OFS versus tamoxifen, the maximum improvement was approximately 3.5\%. Women who did not receive chemotherapy had a more than 97\% rate of 8-year freedom from distant recurrence, and improvements with exemestane plus OFS ranged from 1\% to 4\%. CONCLUSION Premenopausal women with HR-positive/HER2-negative breast cancer and high recurrence risk, as defined by clinicopathologic characteristics, may experience a 10\% to 15\% absolute improvement in 8-year freedom from distant recurrence with exemestane plus OFS versus tamoxifen plus OFS or tamoxifen alone. The potential benefit of escalating endocrine therapy versus tamoxifen alone is minimal for those at low recurrence risk. },
	author = {Pagani, Olivia and Francis, Prudence A. and Fleming, Gini F. and Walley, Barbara A. and Viale, Giuseppe and Colleoni, Marco and L\'{a}ng, Istv\'{a}n and G\'{o}mez, Henry L. and Tondini, Carlo and Pinotti, Graziella and Di Leo, Angelo and Coates, Alan S. and Goldhirsch, Aron and Gelber, Richard D. and Regan, Meredith M. and},
	date-added = {2022-06-16 09:13:06 +0200},
	date-modified = {2022-06-16 09:18:18 +0200},
	doi = {10.1200/JCO.18.01967},
	eprint = {https://doi.org/10.1200/JCO.18.01967},
	journal = {Journal of Clinical Oncology},
	note = {PMID: 31618131},
	number = {12},
	pages = {1293--1303},
	title = {Absolute Improvements in Freedom From Distant Recurrence to Tailor Adjuvant Endocrine Therapies for Premenopausal Women: Results From TEXT and SOFT},
	url = {https://doi.org/10.1200/JCO.18.01967},
	volume = {38},
	year = {2020},
	bdsk-url-1 = {https://doi.org/10.1200/JCO.18.01967}}

@article{Hyndmanetal1996,
	author = {Hyndman, R. J. and Bashtannyk, D. M. and Grunwald, G. K.},
	date-added = {2022-06-07 10:53:26 +0200},
	date-modified = {2022-06-07 10:58:43 +0200},
	journal = {Journal of Computational and Graphical Statistics},
	pages = {315--336},
	title = {{Estimating and Cvisualizing Conditional Densities}},
	volume = {5},
	year = {1996}}

@manual{R_Hyndmanetal2022,
	author = {Rob J Hyndman and Jochen Einbeck and Matthew P Wand},
	date-added = {2022-06-07 10:51:14 +0200},
	date-modified = {2022-06-07 10:51:34 +0200},
	note = {R package version 3.4},
	title = {{hdrcde}: Highest Density Regions and Conditional Density Estimation},
	url = {https://pkg.robjhyndman.com/hdrcde/},
	year = {2022},
	bdsk-url-1 = {https://pkg.robjhyndman.com/hdrcde/}}

@article{RoystonAmbler1998,
	author = {Royston, P. and Ambler, G.},
	date-added = {2021-03-17 15:16:23 +0100},
	date-modified = {2021-03-17 15:18:43 +0100},
	journal = {Stata Technical Bulletin},
	pages = {24--32},
	title = {{sg81: Multivariable Fractional Polynomials}},
	volume = {43},
	year = {1998}}

@article{Fosteretal2011,
	author = {Foster, J. C. and Taylor, J. M. G. and Rubert, S. J.},
	date-added = {2021-03-17 08:58:51 +0100},
	date-modified = {2021-03-17 08:59:45 +0100},
	journal = {{Statistics in Medicine}},
	pages = {2867--2880},
	title = {{Subgroup Identification From Randomized Clinical Trial Data}},
	volume = {30},
	year = {2011}}

@article{RoystonSauerbrei2007,
	author = {Royston, P. and Sauerbrei, W.},
	date-added = {2021-03-17 08:55:56 +0100},
	date-modified = {2021-03-17 08:57:06 +0100},
	journal = {Stata Journal},
	number = {1},
	pages = {45--70},
	title = {{Multivariable Modeling with Cubic Regression Splines: A Principled Approach}},
	volume = {7},
	year = {2007}}

@article{Lietal2015,
	author = {Li, J. and Zhao, L. and Tian, L. and Cai, T. and Claggett, B. and Callegaro, A. and Dizier, B. and Spiessens, B. and Ulloa-Montoya, F. and Wei, L. J.},
	date-added = {2021-03-17 08:50:05 +0100},
	date-modified = {2021-03-17 08:54:51 +0100},
	journal = {Biometrics},
	pages = {877--887},
	title = {{A Predictive Enrichment Procedure to Identify Potential Responders to a New Therapy for Randomized, Comparative, Controlled Clinical Studies}},
	volume = {72},
	year = {2015}}

@article{Zhaoetal2013,
	author = {Zhao, L. and Tian, L. and Cai, T. and Claggett, B. and Wei, L. J.},
	date-added = {2021-03-17 08:48:07 +0100},
	date-modified = {2021-03-17 08:49:11 +0100},
	journal = {Journal of the American Statistical Association},
	number = {502},
	pages = {527--539},
	title = {{Effectively Selecting a Target Population for a Future Comparative Study}},
	volume = {108},
	year = {2013}}

@article{Simon2002,
	author = {Simon, R.},
	date-added = {2021-03-17 08:44:33 +0100},
	date-modified = {2021-03-17 08:45:23 +0100},
	journal = {{Statistics in Medicine}},
	number = {2909--2916},
	title = {{Bayesian Subset Analysis: Application to Studying Treatment-by-Gender Interactions}},
	volume = {21},
	year = {2002}}

@book{Simonetal1995,
	author = {Simon, R. and Dixon, D. O. and Freidlin, B. A.},
	date-added = {2021-03-17 08:43:02 +0100},
	date-modified = {2021-03-17 08:44:31 +0100},
	publisher = {Kluwer Academic Publications},
	title = {{A Bayesian Model for Evaluating Specificity of Treatment Effects in Clinical Trials.}},
	year = {1995}}

@article{RoystonAltman1994,
	author = {Royston, P. and Altman, D. G.},
	date-added = {2021-03-16 16:08:13 +0100},
	date-modified = {2021-03-16 16:12:11 +0100},
	journal = {Applied Statistics},
	pages = {429--467},
	title = {{Regression Using Fractional Polynomials of Continuous Covariates: Parsimonious Parametric Modelling}},
	volume = {43},
	year = {1994}}

@article{RoystonSauerbrei2004,
	author = {Royston, P. and Sauerbrei, W.},
	date-added = {2021-03-16 15:55:51 +0100},
	date-modified = {2021-03-16 15:57:20 +0100},
	journal = {{Statistics in Medicine}},
	pages = {2509--2525},
	title = {{A New Approach to Modelling Interactions Between Treatment and Continuous Covariates in Clinical Trials by Using Fractional Polynomials}},
	volume = {23},
	year = {2004}}

@book{RoystonSauerbrei2008,
	author = {Royston, Patrick and Sauerbrei, Willi},
	date-added = {2021-03-16 15:11:37 +0100},
	date-modified = {2021-03-16 15:14:26 +0100},
	publisher = {John Wiley \& Sons},
	title = {{Multivariable Model-Building}},
	year = {2008}}

@book{Hayes2017,
	author = {Hayes, A. F.},
	date-added = {2021-03-16 14:42:43 +0100},
	date-modified = {2021-03-16 14:52:52 +0100},
	edition = {2nd},
	publisher = {Guilford Press},
	title = {{Introduction to Mediation, Moderation, and Conditional Process Analysis}},
	year = {2017}}

@book{HernanRobins2021,
	author = {Hern\'an, M. A. and Robins, J. M.},
	date-added = {2021-03-16 14:35:17 +0100},
	date-modified = {2021-03-16 14:40:59 +0100},
	publisher = {CRC Press},
	title = {{Causal Inference: What If}},
	year = {2021}}

@book{Imai2017,
	author = {Imai, K.},
	date-added = {2021-03-16 14:33:43 +0100},
	date-modified = {2021-03-16 14:35:16 +0100},
	publisher = {Princeton University Press},
	title = {{Quantitative Social Science. An Introduction}},
	year = {2017}}

@book{vanderWeele2015,
	author = {van der Weele, T. J.},
	date-added = {2021-03-16 14:32:26 +0100},
	date-modified = {2021-03-16 14:33:33 +0100},
	publisher = {Oxford University Press},
	title = {{Explanation in Causal Inference}},
	year = {2015}}

@article{Baronetal2003,
	author = {Baron, John A. and Cole, Bernard F. and Sandler, Robert S. and Haile, Robert W. and Ahnen, Dennis and Bresalier, Robert and McKeown-Eyssen, Gail and Summers, Robert W. and Rothstein, Richard and Burke, Carol A. and Snover, Dale C. and Church, Timothy R. and Allen, John I. and Beach, Michael and Beck, Gerald J. and Bond, John H. and Byers, Tim and Greenberg, E. Robert and Mandel, Jack S. and Marcon, Norman and Mott, Leila A. and Pearson, Loretta and Saibil, Fred and van Stolk, Rosalind U.},
	date-added = {2021-03-08 13:57:44 +0100},
	date-modified = {2021-03-08 13:58:48 +0100},
	journal = {{The New England Journal of Medicine}},
	number = {10},
	pages = {891--899},
	title = {{A Randomized Trial of Aspirin to Prevent Colorectal Adenomas}},
	volume = {348},
	year = {2003},
	bdsk-url-1 = {https://doi.org/10.1056/NEJMoa021735}}

@article{Vialeetal2008_etal,
	abstract = {Purpose To evaluate the prognostic and predictive value of Ki-67 labeling index (LI) in a trial comparing letrozole (Let) with tamoxifen (Tam) as adjuvant therapy in postmenopausal women with early breast cancer. Patients and Methods Breast International Group (BIG) trial 1-98 randomly assigned 8,010 patients to four treatment arms comparing Let and Tam with sequences of each agent. Of 4,922 patients randomly assigned to receive 5 years of monotherapy with either agent, 2,685 had primary tumor material available for central pathology assessment of Ki-67 LI by immunohistochemistry and had tumors confirmed to express estrogen receptors after central review. The prognostic and predictive value of centrally measured Ki-67 LI on disease-free survival (DFS) were assessed among these patients using proportional hazards modeling, with Ki-67 LI values dichotomized at the median value of 11\%. Results Higher values of Ki-67 LI were associated with adverse prognostic factors and with worse DFS (hazard ratio [HR; high:low] = 1.8; 95\% CI, 1.4 to 2.3). The magnitude of the treatment benefit for Let versus Tam was greater among patients with high tumor Ki-67 LI (HR [Let:Tam] = 0.53; 95\% CI, 0.39 to 0.72) than among patients with low tumor Ki-67 LI (HR [Let:Tam] = 0.81; 95\% CI, 0.57 to 1.15; interaction P = .09). Conclusion Ki-67 LI is confirmed as a prognostic factor in this study. High Ki-67 LI levels may identify a patient group that particularly benefits from initial Let adjuvant therapy. },
	author = {Viale, Giuseppe and Giobbie-Hurder, Anita and {et al.}},
	date-added = {2021-03-03 09:02:10 +0100},
	date-modified = {2021-03-03 09:03:55 +0100},
	journal = {{Journal of Clinical Oncology}},
	number = {34},
	pages = {5569--5575},
	title = {{Prognostic and Predictive Value of Centrally Reviewed Ki-67 Labeling Index in Postmenopausal Women With Endocrine-Responsive Breast Cancer: Results From Breast International Group Trial 1-98 Comparing Adjuvant Tamoxifen With Letrozole}},
	volume = {26},
	year = {2008},
	bdsk-url-1 = {https://doi.org/10.1200/JCO.2008.17.0829}}

@article{Gerdesetal1983_etal,
	abstract = {Abstract The production of a mouse monoclonal antibody, Ki-67, is described. The Ki-67 antibody recognized a nuclear antigen present in proliferating cells, but absent in resting cells. Immunostainings with Ki-67 revealed nuclear reactivity in cells of germinal centres of cortical follicles, cortical thymocytes, neck cells of gastrointestinal mucosa, un-differentiated spermatogonia and cells of a number of human cell lines. The Ki-67 antibody did not react with cells known to be in a resting stage, such as lymphocytes, monocytes, parietal cells and Paneth's cells of gastrointestinal mucosa, hepatocytes, renal cells, mature sperm cells, brain cells, etc. Expression of the antigen recognized by Ki-67 could be induced in peripheral blood lymphocytes after stimulation with phytohaemagglutinin, whereas it disappeared from HL-60 cells stimulated with phorbol esters to differentiate into mature macrophages in a resting stage. These findings suggest that Ki-67 is directed against a nuclear antigen associated with cell proliferation. A first series of immunostainings of tumour biopsies indicated that Ki-67 may be a potent tool for easy and quick evaluation of the proportion of proliferating cells in a tumour.},
	author = {Gerdes, Johannes and Schwab, Ulrich and {et al.}},
	date-added = {2021-03-03 09:01:55 +0100},
	date-modified = {2021-03-03 09:03:51 +0100},
	journal = {International Journal of Cancer},
	number = {1},
	pages = {13--20},
	title = {{Production of a Mouse Monoclonal Antibody Reactive With a Human Nuclear Antigen Associated With Cell Proliferation}},
	volume = {31},
	year = {1983},
	bdsk-url-1 = {https://onlinelibrary.wiley.com/doi/abs/10.1002/ijc.2910310104},
	bdsk-url-2 = {https://doi.org/10.1002/ijc.2910310104}}

@article{BIG98a_etal,
	author = {{Breast International Group (BIG) 1-98 Collaborative Group} and Th\"urlimann, B. and {et al.}},
	date-added = {2021-03-03 09:01:25 +0100},
	date-modified = {2021-03-03 09:03:40 +0100},
	journal = {{The New England Journal of Medicine}},
	number = {26},
	pages = {2747--2757},
	title = {{A Comparison of Letrozole and Tamoxifen in Postmenopausal Women With Early Breast Cancer}},
	volume = {353},
	year = {2005}}

@article{Coates2007_etal,
	author = {Coates, A. S. and Keshaviah, A. and {et al.}},
	date-added = {2021-03-03 09:01:02 +0100},
	date-modified = {2021-03-03 09:03:45 +0100},
	journal = {{Journal of Clinical Oncology}},
	number = {5},
	pages = {486--492},
	title = {{Five Years of Letrozole Compared With Tamoxifen as Initial Adjuvant Therapy for Postmenopausal Women With Endocrine-Responsive Early Breast Cancer: Update of Study BIG 1-98}},
	volume = {25},
	year = {2007}}

@book{Collett2015,
	author = {Collett, D.},
	date-added = {2021-03-02 15:47:07 +0100},
	date-modified = {2021-03-02 15:48:01 +0100},
	edition = {3rd},
	publisher = {CRC Press},
	title = {{Modelling Survival Data in Medical Research}},
	year = {2015}}

@article{Gerdesetal1983,
	abstract = {Abstract The production of a mouse monoclonal antibody, Ki-67, is described. The Ki-67 antibody recognized a nuclear antigen present in proliferating cells, but absent in resting cells. Immunostainings with Ki-67 revealed nuclear reactivity in cells of germinal centres of cortical follicles, cortical thymocytes, neck cells of gastrointestinal mucosa, un-differentiated spermatogonia and cells of a number of human cell lines. The Ki-67 antibody did not react with cells known to be in a resting stage, such as lymphocytes, monocytes, parietal cells and Paneth's cells of gastrointestinal mucosa, hepatocytes, renal cells, mature sperm cells, brain cells, etc. Expression of the antigen recognized by Ki-67 could be induced in peripheral blood lymphocytes after stimulation with phytohaemagglutinin, whereas it disappeared from HL-60 cells stimulated with phorbol esters to differentiate into mature macrophages in a resting stage. These findings suggest that Ki-67 is directed against a nuclear antigen associated with cell proliferation. A first series of immunostainings of tumour biopsies indicated that Ki-67 may be a potent tool for easy and quick evaluation of the proportion of proliferating cells in a tumour.},
	author = {Gerdes, Johannes and Schwab, Ulrich and Lemke, Hilmar and Stein, Harald},
	date-added = {2021-03-02 11:14:08 +0100},
	date-modified = {2021-03-02 11:14:53 +0100},
	journal = {International Journal of Cancer},
	number = {1},
	pages = {13--20},
	title = {{Production of a Mouse Monoclonal Antibody Reactive With a Human Nuclear Antigen Associated With Cell Proliferation}},
	volume = {31},
	year = {1983},
	bdsk-url-1 = {https://onlinelibrary.wiley.com/doi/abs/10.1002/ijc.2910310104},
	bdsk-url-2 = {https://doi.org/10.1002/ijc.2910310104}}

@article{Clahasenetal1999,
	abstract = {Introduction:Prognostic factors can be useful to identify node-negative patients at increased risk of relapse who should receive adjuvant treatment. In the past, oestrogen receptor status and mitotic index have been shown to be significant predictors of prognosis. Different techniques for the measurement of these prognostic factors are available.Methods:Paraffin-embedded tumour specimens from 441 pre-menopausal patients with node-negative breast cancer who were previously randomized onto a trial comparing peri-operative chemotherapy with no further therapy were studied. Oestrogen receptor status was determined by the classical biochemical assay and by immunohistochemistry (ER-IA). Mitotic index was assessed by counting the number of mitoses and by calculating the percentage of tumour cells positively staining for the antibody Ki-67.Results:There was a good correlation between ER-IA and the biochemical ER-assay (P<0.01), and the percentage of Ki-67 positive tumour cells and mitotic counts (P<0.01) respectively. However, ER-IA significantly predicted disease-free survival (RR=2.67, 95% CI: 1.60--4.44,P<0.01) whereas the biochemical assay was only borderline significant (RR=1.54, 95% CI: 1.00--2.36,P=0.05). Similarly, Ki-67 was a stronger indicator of prognosis (RR=2.84, 95% CI: 1.80--4.48,P<0.01) than mitotic counts (RR=1.56, 95% CI: 1.22--2.00,P<0.01).Conclusions:We conclude that ER-IA performs better in predicting prognosis than the classical biochemical oestrogen receptor assay. Ki-67 is a more accurate marker for tumour cell proliferation and predicts prognosis of patients with breast cancer better than do mitotic counts.},
	author = {P.C. Clahsen and C.J.H. {van de Velde} and C. Duval and C. Pallud and A.- M. Mandard and A. Delobelle-Deroide and L. {van den Broek} and M.J. {van de Vijver}},
	date-added = {2021-03-02 11:11:41 +0100},
	date-modified = {2021-03-02 11:12:52 +0100},
	journal = {European Journal of Surgical Oncology},
	number = {4},
	pages = {356--363},
	title = {{The Utility of Mitotic Index, Oestrogen Receptor and Ki-67 Measurements in the Creation of Novel Prognostic Indices Fornode-Negative Breast Cancer}},
	volume = {25},
	year = {1999},
	bdsk-url-1 = {https://www.sciencedirect.com/science/article/pii/S0748798399906571},
	bdsk-url-2 = {https://doi.org/10.1053/ejso.1999.0657}}

@article{Coates2007,
	author = {Coates, A. S. and Keshaviah, A. and Th\"urlimann, B. and Mouridsen, H. and Mauriac, L. and Forbes, J. F. and Paridaens, R. and Castiglione-Gertsch, M. and Gelber, R. D. and Colleoni, M. and L{\'a}ng, I. and Del Mastro, L. and Smith, I. and Chirgwin, J. and Nogaret, J. M. and Pienkowski, T. and Wardley, A. and Jakobsen, E. H. and Price, K. N. and Goldhirsch, A.},
	date-added = {2021-03-02 10:04:54 +0100},
	date-modified = {2021-03-03 09:00:28 +0100},
	journal = {{Journal of Clinical Oncology}},
	number = {5},
	pages = {486--492},
	title = {{Five Years of Letrozole Compared With Tamoxifen as Initial Adjuvant Therapy for Postmenopausal Women With Endocrine-Responsive Early Breast Cancer: Update of Study BIG 1-98}},
	volume = {25},
	year = {2007}}

@article{BIG98b,
	author = {{Breast International Group (BIG) 1-98 Collaborative Group}},
	date-added = {2021-03-02 09:58:39 +0100},
	date-modified = {2021-03-02 10:01:09 +0100},
	journal = {{The New England Journal of Medicine}},
	number = {8},
	pages = {766--776},
	title = {Letrozole Therapy Alone or in Sequence with Tamoxifen in Women with Breast Cancer},
	volume = {361},
	year = {2009},
	bdsk-url-1 = {https://doi.org/10.1056/NEJMoa0810818}}

@article{BIG98a,
	author = {{Breast International Group (BIG) 1-98 Collaborative Group} and Th\"urlimann, B. and Keshaviah, A. and Coates, A. S. and Mouridsen, H. and Mauriac, L. and Forbes, J. F. and Paridaens, R. and Castiglione-Gertsch, M. and Gelber, R. D. and Rabaglio, M. and Smith, I. and Wardley, A. and Price, K. N. and Goldhirsch, A.},
	date-added = {2021-03-02 09:54:09 +0100},
	date-modified = {2021-03-03 09:00:03 +0100},
	journal = {{The New England Journal of Medicine}},
	number = {26},
	pages = {2747--2757},
	title = {{A Comparison of Letrozole and Tamoxifen in Postmenopausal Women With Early Breast Cancer}},
	volume = {353},
	year = {2005}}

@book{Gould2018,
	author = {Gould, W. W.},
	date-added = {2021-02-25 09:23:53 +0100},
	date-modified = {2021-02-25 09:24:46 +0100},
	publisher = {{Stata Press}},
	title = {{The Mata Book: A Book for Serious Programmers and Those Who Want to Be}},
	year = {2018}}

@book{Pesarin2001,
	author = {Pesarin, F.},
	date-added = {2021-02-17 11:56:46 +0100},
	date-modified = {2021-02-17 11:57:22 +0100},
	publisher = {John Wiley \& Sons},
	title = {{Multivariate Permutation Tests}},
	year = {2001}}

@book{vanderVaart1998,
	author = {van der Vaart, A. W.},
	date-added = {2021-02-17 09:53:50 +0100},
	date-modified = {2021-02-17 09:54:47 +0100},
	publisher = {Cambridge University Press},
	title = {{Asymptotic Statistics}},
	year = {1998}}

@article{Petoetal1977,
	author = {Peto, R. and Pike, M C and Armitage, P. and Breslow, N E and Cox, D R and Howard, S V and Mantel, N. and McPherson, K. and Peto, J. and Smith, P G},
	date-added = {2021-02-10 11:53:25 +0100},
	date-modified = {2021-02-10 11:56:36 +0100},
	journal = {British Journal of Cancer},
	number = {1},
	pages = {1--39},
	title = {{Design and analysis of randomized clinical trials requiring prolonged observation of each patient. II. Analysis and examples}},
	volume = {35},
	year = {1977}}

@article{Lazaretal2016,
	author = {Lazar, Ann and Bonetti, Marco and Cole, Bernard F. and Yip, Wai-Ki and Gelber, Richard D.},
	date-added = {2021-01-18 10:44:36 +0100},
	date-modified = {2021-01-18 10:46:11 +0100},
	journal = {{Clinical Trials}},
	number = {2},
	pages = {169--179},
	title = {{Identifying Treatment Effect Heterogeneity in Clinical Trials Using Subpopulations of Events: STEPP}},
	volume = {13},
	year = {2016}}

@article{Yipetal2016,
	author = {Yip, Wai-Ki and Bonetti, Marco and Cole, Bernard F. and Barcella, William and Wang, Xin Victoria and Lazar, Ann and Gelber, Richard D.},
	date-added = {2021-01-18 10:36:38 +0100},
	date-modified = {2021-02-10 12:47:58 +0100},
	journal = {{Clinical Trials}},
	number = {4},
	pages = {382--390},
	title = {{Subpopulation Treatment Effect Pattern Plot (STEPP) Analysis for Continuous, Binary, and Count Outcomes}},
	volume = {13},
	year = {2016}}

@article{Pocock2008,
	author = {Pocock, S.},
	date-added = {2021-01-04 18:07:52 +0100},
	date-modified = {2021-01-04 18:08:04 +0100},
	journal = {{The New England Journal of Medicine}},
	pages = {2076--2077},
	title = {{More on Subgroup Analysis in Clinical Trials}},
	volume = {358},
	year = {2008}}

@article{Lagakos2006,
	author = {Lagakos, S.},
	date-added = {2021-01-04 18:07:03 +0100},
	date-modified = {2021-01-04 18:07:20 +0100},
	journal = {{The New England Journal of Medicine}},
	pages = {1667--1669},
	title = {{The Challenge of Subgroup Analysis - Reporting Without Distorting}},
	volume = {354},
	year = {2006}}

@article{RoystonSauerbrei2009,
	abstract = {There is increasing interest in the medical world in the possibility of tailoring treatment to the individual patient. Statistically, the relevant task is to identify interactions between covariates and treatments, such that the patient's value of a given covariate influences how strongly (or even whether) they are likely to respond to a treatment. The most valuable data are obtained in randomized controlled clinical trials of novel treatments in comparison with a control treat- ment. We describe two techniques to detect and model such interactions. The first technique, multivariable fractional polynomials interaction, is based on fractional polynomials methodology, and provides a method of testing for continuous-by- binary interactions and by modeling the treatment effect as a function of a continuous covariate. The second technique, subpopulation treatment-effect pattern plot, aims to do something similar but is focused on producing a nonparametric estimate of the treatment effect, expressed graphically. Stata programs for both of these techniques are described. Real data for brain and breast cancer are used as examples. Copyright 2009 by StataCorp LP.},
	author = {Royston, Patrick and Sauerbrei, Willi},
	date-added = {2021-01-04 18:04:06 +0100},
	date-modified = {2021-01-04 18:04:27 +0100},
	journal = {{Stata Journal}},
	month = {June},
	number = {2},
	pages = {230--251},
	title = {{Two Techniques for Investigating Interactions Between Treatment and Continuous Covariates in Clinical Trials}},
	url = {https://ideas.repec.org/a/tsj/stataj/v9y2009i2p230-251.html},
	volume = {9},
	year = 2009,
	bdsk-url-1 = {https://ideas.repec.org/a/tsj/stataj/v9y2009i2p230-251.html}}

@article{Wangetal2007,
	author = {Wang, Rui and Lagakos, Stephen W. and Ware, James H. and Hunter, David J. and Drazen, Jeffrey M.},
	date-added = {2021-01-04 18:00:38 +0100},
	date-modified = {2021-01-04 18:00:55 +0100},
	doi = {10.1056/NEJMsr077003},
	journal = {N Engl J Med},
	journal-full = {{The New England Journal of Medicine}},
	mesh = {{Clinical Trials as Topic; Data Interpretation, Statistical; Quality Control; Statistics as Topic}},
	month = {Nov},
	number = {21},
	pages = {2189--94},
	pmid = {18032770},
	pst = {ppublish},
	title = {{Statistics in Medicine--reporting of Subgroup Analyses in Clinical Trials}},
	volume = {357},
	year = {2007},
	bdsk-url-1 = {https://doi.org/10.1056/NEJMsr077003}}

@book{TherneauGrambsch2000,
	address = {New York},
	author = {Therneau, Terry M. and Grambsch, Patricia M.},
	date-added = {2021-01-04 17:59:02 +0100},
	date-modified = {2021-01-04 17:59:21 +0100},
	isbn = {0-387-98784-3},
	publisher = {Springer-Verlag},
	title = {{Modeling Survival Data: Extending the {C}ox Model}},
	year = {2000}}

@manual{R_survival,
	author = {Therneau, Terry M.},
	date-added = {2021-01-04 17:58:47 +0100},
	date-modified = {2021-01-04 17:58:52 +0100},
	note = {R package version 3.2-7},
	title = {{A Package for Survival Analysis in \texttt{R}}},
	url = {https://CRAN.R-project.org/package=survival},
	year = {2020},
	bdsk-url-1 = {https://CRAN.R-project.org/package=survival}}

@manual{R_cmprsk,
	author = {Gray, Robert J.},
	date-added = {2021-01-04 17:57:22 +0100},
	date-modified = {2021-04-30 14:53:44 +0200},
	note = {R package version 2.2-10},
	title = {{\texttt{cmprsk}: Subdistribution Analysis of Competing Risks}},
	url = {https://CRAN.R-project.org/package=cmprsk},
	year = {2020},
	bdsk-url-1 = {https://CRAN.R-project.org/package=cmprsk}}

@article{Lazaretal2010,
	abstract = { The discovery of biomarkers that predict treatment effectiveness has great potential for improving medical care, particularly in oncology. These biomarkers are increasingly reported on a continuous scale, allowing investigators to explore how treatment efficacy varies as the biomarker values continuously increase, as opposed to using arbitrary categories of expression levels resulting in a loss of information. In the age of biomarkers as continuous predictors (eg, expression level percentage rather than positive v negative), alternatives to such dichotomized analyses are needed. The purpose of this article is to provide an overview of an intuitive statistical approach--the subpopulation treatment effect pattern plot (STEPP)--for evaluating treatment-effect heterogeneity when a biomarker is measured on a continuous scale. STEPP graphically explores the patterns of treatment effect across overlapping intervals of the biomarker values. As an example, STEPP methodology is used to explore patterns of treatment effect for varying levels of the biomarker Ki-67 in the BIG (Breast International Group) 1-98 randomized clinical trial comparing letrozole with tamoxifen as adjuvant therapy for postmenopausal women with hormone receptor--positive breast cancer. STEPP analyses showed patients with higher Ki-67 values who were assigned to receive tamoxifen had the poorest prognosis and may benefit most from letrozole. },
	author = {Lazar, Ann and Cole, Bernard F. and Bonetti, Marco and Gelber, Richard D.},
	date-added = {2021-01-04 17:56:12 +0100},
	date-modified = {2021-01-18 10:44:34 +0100},
	doi = {10.1200/JCO.2009.27.9182},
	eprint = {https://doi.org/10.1200/JCO.2009.27.9182},
	journal = {{Journal of Clinical Oncology}},
	note = {PMID: 20837942},
	number = {29},
	pages = {4539--4544},
	title = {{Evaluation of Treatment-Effect Heterogeneity Using Biomarkers Measured on a Continuous Scale: Subpopulation Treatment Effect Pattern Plot}},
	url = {https://doi.org/10.1200/JCO.2009.27.9182},
	volume = {28},
	year = {2010},
	bdsk-url-1 = {https://doi.org/10.1200/JCO.2009.27.9182}}

@article{Gray1988,
	author = {Gray, Robert J.},
	date-added = {2021-01-04 17:37:31 +0100},
	date-modified = {2021-01-04 17:37:45 +0100},
	journal = {The Annals of Statistics},
	number = {3},
	pages = {1141--1154},
	publisher = {{The Institute of Mathematical Statistics}},
	title = {{A Class of $K$-Sample Tests for Comparing the Cumulative Incidence of a Competing Risk}},
	url = {https://doi.org/10.1214/aos/1176350951},
	volume = {16},
	year = {1988},
	bdsk-url-1 = {https://doi.org/10.1214/aos/1176350951}}

@article{FineGray1999,
	abstract = {With explanatory covariates, the standard analysis for competing risks data involves modeling the cause-specific hazard functions via a proportional hazards assumption. Unfortunately, the cause-specific hazard function does not have a direct interpretation in terms of survival probabilities for the particular failure type. In recent years many clinicians have begun using the cumulative incidence function, the marginal failure probabilities for a particular cause, which is intuitively appealing and more easily explained to the nonstatistician. The cumulative incidence is especially relevant in cost-effectiveness analyses in which the survival probabilities are needed to determine treatment utility. Previously, authors have considered methods for combining estimates of the cause-specific hazard functions under the proportional hazards formulation. However, these methods do not allow the analyst to directly assess the effect of a covariate on the marginal probability function. In this article we propose a novel semiparametric proportional hazards model for the subdistribution. Using the partial likelihood principle and weighting techniques, we derive estimation and inference procedures for the finite-dimensional regression parameter under a variety of censoring scenarios. We give a uniformly consistent estimator for the predicted cumulative incidence for an individual with certain covariates; confidence intervals and bands can be obtained analytically or with an easy-to-implement simulation technique. To contrast the two approaches, we analyze a dataset from a breast cancer clinical trial under both models.},
	author = {Fine, Jason P. and Gray, Robert J.},
	date-added = {2021-01-04 17:36:51 +0100},
	date-modified = {2021-01-04 17:36:51 +0100},
	issn = {01621459},
	journal = {Journal of the American Statistical Association},
	number = {446},
	pages = {496--509},
	publisher = {[American Statistical Association, Taylor & Francis, Ltd.]},
	title = {{A Proportional Hazards Model for the Subdistribution of a Competing Risk}},
	url = {http://www.jstor.org/stable/2670170},
	volume = {94},
	year = {1999},
	bdsk-url-1 = {http://www.jstor.org/stable/2670170}}

@article{Cox1972,
	abstract = {Summary The analysis of censored failure times is considered. It is assumed that on each individual are available values of one or more explanatory variables. The hazard function (age-specific failure rate) is taken to be a function of the explanatory variables and unknown regression coefficients multiplied by an arbitrary and unknown function of time. A conditional likelihood is obtained, leading to inferences about the unknown regression coefficients. Some generalizations are outlined.},
	author = {Cox, David R.},
	date-added = {2021-01-04 17:35:26 +0100},
	date-modified = {2021-01-04 17:35:47 +0100},
	journal = {{Journal of the Royal Statistical Society B}},
	number = {2},
	pages = {187--202},
	title = {{Regression Models and Life-Tables}},
	volume = {34},
	year = {1972}}

@article{Colleonietal2002,
	abstract = {Cyclophosphamide, methotrexate and fluorouracil adjuvant combination chemotherapy for breast cancer is currently used for the duration of six monthly courses. We performed a joint analysis of two studies on the duration of adjuvant cyclophosphamide, methotrexate and fluorouracil in patients with node-positive breast cancer to investigate whether three courses of cyclophosphamide, methotrexate and fluorouracil might suffice. The International Breast Cancer Study Group Trial VI randomly assigned 735 pre- and perimenopausal patients to receive 'classical' cyclophosphamide, methotrexate and fluorouracil for three consecutive cycles, or the same chemotherapy for six consecutive cycles. The German Breast Cancer Study Group randomised 289 patients to receive either three or six cycles of i.v. cyclophosphamide, methotrexate and fluorouracil day 1, 8. Treatment effects were estimated using Cox regression analysis stratified by clinical trial without further adjustment for covariates. The 5-year disease-free survival per cents (+/-s.e.) were 54+/-2% for three cycles and 55+/-2% for six cycles (n=1024; risk ratio (risk ratio: CMFx3/CMFx6), 1.00; 95% confidence interval, 0.85 to 1.18; P=0.99). Use of three rather than six cycles was demonstrated to be adequate in both studies for patients at least 40-years-old with oestrogen-receptor-positive tumours (n=594; risk ratio, 0.86; 95% confidence interval, 0.68 to 1.08; P=0.19). In fact, results slightly favoured three cycles over six for this subgroup, and the 95% confidence interval excluded an adverse effect of more than 2% with respect to absolute 5-year survival. In contrast, three cycles appeared to be possibly inferior to six cycles for women less than 40-years-old (n=190; risk ratio, 1.25; 95% confidence interval, 0.87 to 1.80; P=0.22) and for women with oestrogen-receptor-negative tumours (n=302; risk ratio, 1.15; 95% confidence interval, 0.85 to 1.57; P=0.37). Thus, three initial cycles of adjuvant cyclophosphamide, methotrexate and fluorouracil chemotherapy were as effective as six cycles for older patients (40-years-old) with oestrogen-receptor-positive tumours, while six cycles of adjuvant cyclophosphamide, methotrexate and fluorouracil might still be required for other cohorts. Because endocrine therapy with tamoxifen and GnRH analogues is now available for younger women with oestrogen-receptor-positive tumours, the need for six cycles of cyclophosphamide, methotrexate and fluorouracil is unclear and requires further investigation.},
	author = {Colleoni, M. and Litman, H. J. and Castiglione-Gertsch, M. and Sauerbrei, W. and Gelber, R. D. and Bonetti, M. and Coates, A. S. and Schumacher, M. and Bastert, G. and Rudenstam, C.-M. and Schmoor, C. and Lindtner, J. and Collins, J. and Th{\"u}rlimann, B. and Holmberg, S. B. and Crivellari, D. and Beyerle, C. and Neumann, R. L. A. and Goldhirsch, A. and {International Breast Cancer Study Group} and {German Breast Cancer Study Group}},
	date-added = {2021-01-04 17:32:31 +0100},
	date-modified = {2021-01-04 17:33:12 +0100},
	journal = {{British Journal of Cancer}},
	number = {11},
	pages = {1705--14},
	title = {{Duration of adjuvant chemotherapy for breast cancer: a joint analysis of two randomised trials investigating three versus six courses of CMF}},
	volume = {86},
	year = {2002}}

@article{Bonettietal2009,
	abstract = {Abstract A new, intuitive method has recently been proposed to explore treatment--covariate interactions in survival data arising from two treatment arms of a clinical trial. The method is based on constructing overlapping subpopulations of patients with respect to one (or more) covariates of interest and in observing the pattern of the treatment effects estimated across the subpopulations. A plot of these treatment effects is called a subpopulation treatment effect pattern plot. Here, we explore the small sample characteristics of the asymptotic results associated with the method and develop an alternative permutation distribution-based approach to inference that should be preferred for smaller sample sizes. We then describe an extension of the method to the case in which the pattern of estimated quantiles of survivor functions is of interest. Copyright {\copyright} 2009 John Wiley \& Sons, Ltd.},
	author = {Bonetti, Marco and Zahrieh, David and Cole, Bernard F. and Gelber, Richard D.},
	date-added = {2021-01-04 17:30:42 +0100},
	date-modified = {2021-01-04 17:31:07 +0100},
	journal = {{Statistics in Medicine}},
	number = {8},
	pages = {1255--1268},
	title = {{A Small Sample Study of The STEPP Approach to Assessing Treatment--covariate Interactions in Survival Data}},
	volume = {28},
	year = {2009},
	bdsk-url-1 = {https://www.onlinelibrary.wiley.com/doi/abs/10.1002/sim.3524},
	bdsk-url-2 = {https://doi.org/10.1002/sim.3524}}

@article{BonettiGelber2000,
	author = {Bonetti, Marco and Gelber, Richard D.},
	date-added = {2021-01-04 17:29:03 +0100},
	date-modified = {2021-01-04 17:29:17 +0100},
	journal = {{Statistics in Medicine}},
	number = {19},
	pages = {2595--2609},
	title = {{A Graphical Method to Assess Treatment--covariate Interactions Using the Cox Model on Subsets of the Data}},
	volume = {19},
	year = {2000}}

@article{BonettiGelber2004,
	abstract = {{ We discuss the practice of examining patterns of treatment effects across overlapping patient subpopulations. In particular, we focus on the case in which patient subgroups are defined to contain patients having increasingly larger (or smaller) values of one particular covariate of interest, with the intent of exploring the possible interaction between treatment effect and that covariate. We formalize these subgroup approaches (STEPP: subpopulation treatment effect pattern plots) and implement them when treatment effect is defined as the difference in survival at a fixed time point between two treatment arms. The joint asymptotic distribution of the treatment effect estimates is derived, and used to construct simultaneous confidence bands around the estimates and to test the null hypothesis of no interaction. These methods are illustrated using data from a clinical trial conducted by the International Breast Cancer Study Group, which demonstrates the critical role of estrogen receptor content of the primary breast cancer for selecting appropriate adjuvant therapy. The considerations are also relevant for general subset analysis, since information from the same patients is typically used in the estimation of treatment effects within two or more subgroups of patients defined with respect to different covariates. }},
	author = {Bonetti, Marco and Gelber, Richard D.},
	date-added = {2021-01-04 17:26:31 +0100},
	date-modified = {2021-01-04 17:26:53 +0100},
	journal = {Biostatistics},
	number = {3},
	pages = {465--481},
	title = {{Patterns of Treatment Effects in Subsets of Patients in Clinical Trials}},
	volume = {5},
	year = {2004}}

@article{Vialeetal2008,
	abstract = {Purpose To evaluate the prognostic and predictive value of Ki-67 labeling index (LI) in a trial comparing letrozole (Let) with tamoxifen (Tam) as adjuvant therapy in postmenopausal women with early breast cancer. Patients and Methods Breast International Group (BIG) trial 1-98 randomly assigned 8,010 patients to four treatment arms comparing Let and Tam with sequences of each agent. Of 4,922 patients randomly assigned to receive 5 years of monotherapy with either agent, 2,685 had primary tumor material available for central pathology assessment of Ki-67 LI by immunohistochemistry and had tumors confirmed to express estrogen receptors after central review. The prognostic and predictive value of centrally measured Ki-67 LI on disease-free survival (DFS) were assessed among these patients using proportional hazards modeling, with Ki-67 LI values dichotomized at the median value of 11\%. Results Higher values of Ki-67 LI were associated with adverse prognostic factors and with worse DFS (hazard ratio [HR; high:low] = 1.8; 95\% CI, 1.4 to 2.3). The magnitude of the treatment benefit for Let versus Tam was greater among patients with high tumor Ki-67 LI (HR [Let:Tam] = 0.53; 95\% CI, 0.39 to 0.72) than among patients with low tumor Ki-67 LI (HR [Let:Tam] = 0.81; 95\% CI, 0.57 to 1.15; interaction P = .09). Conclusion Ki-67 LI is confirmed as a prognostic factor in this study. High Ki-67 LI levels may identify a patient group that particularly benefits from initial Let adjuvant therapy. },
	author = {Viale, Giuseppe and Giobbie-Hurder, Anita and Regan, Meredith M. and Coates, Alan S. and Mastropasqua, Mauro G. and Dell'Orto, Patrizia and Maiorano, Eugenio and MacGrogan, Ga{\"e}tan and Braye, Stephen G. and {\"O}hlschlegel, Christian and Neven, Patrick and Orosz, Zsolt and Olszewski, Wojciech P. and Knox, Fiona and Th{\"u}rlimann, Beat and Price, Karen N. and Castiglione-Gertsch, Monica and Gelber, Richard D. and Gusterson, Barry A. and Goldhirsch, Aron},
	date-added = {2021-01-04 17:20:44 +0100},
	date-modified = {2021-03-02 14:48:26 +0100},
	journal = {{Journal of Clinical Oncology}},
	number = {34},
	pages = {5569--5575},
	title = {{Prognostic and Predictive Value of Centrally Reviewed Ki-67 Labeling Index in Postmenopausal Women With Endocrine-Responsive Breast Cancer: Results From Breast International Group Trial 1-98 Comparing Adjuvant Tamoxifen With Letrozole}},
	volume = {26},
	year = {2008},
	bdsk-url-1 = {https://doi.org/10.1200/JCO.2008.17.0829}}
