stat.bib

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@Electronic{odac_pembro,
  author = {FDA},
  month  = {{Feb}},
  note   = {https://www.fda.gov/media/145654/download},
  title  = {Combined FDA and Applicant ODAC Briefing Document},
  url    = {https://www.fda.gov/media/145654/download},
  year   = {2021},
}

@Article{schmid_20,
  author  = {Schmid, Peter and Cortes, Javier and Pusztai, Lajos and McArthur, Heather and Kümmel, Sherko and Bergh, Jonas and Denkert, Carsten and Park, Yeon Hee and Hui, Rina and Harbeck, Nadia and Takahashi, Masato and Foukakis, Theodoros and Fasching, Peter A. and Cardoso, Fatima and Untch, Michael and Jia, Liyi and Karantza, Vassiliki and Zhao, Jing and Aktan, Gursel and Dent, Rebecca and O’Shaughnessy, Joyce},
  journal = {New England Journal of Medicine},
  title   = {Pembrolizumab for Early Triple-Negative Breast Cancer},
  year    = {2020},
  note    = {PMID: 32101663},
  number  = {9},
  pages   = {810-821},
  volume  = {382},
  doi     = {10.1056/NEJMoa1910549},
  eprint  = {https://doi.org/10.1056/NEJMoa1910549},
  url     = {https://doi.org/10.1056/NEJMoa1910549},
}

@Article{tai_21,
  author  = {Ting-An Tai and Nicholas R. Latimer and Ágnes Benedict and Zsofia Kiss and Andreas Nikolaou},
  journal = {Value in Health},
  title   = {Prevalence of Immature Survival Data for Anti-Cancer Drugs Presented to the National Institute for Health and Care Excellence and Impact on Decision Making},
  year    = {2021},
  issn    = {1098-3015},
  number  = {4},
  pages   = {505-512},
  volume  = {24},
  doi     = {https://doi.org/10.1016/j.jval.2020.10.016},
  url     = {https://www.sciencedirect.com/science/article/pii/S1098301520344648},
}

@Article{benaharon_20,
  author   = {Ben-Aharon, Omer and Magnezi, Racheli and Leshno, Moshe and Goldstein, Daniel A.},
  journal  = {JCO Oncology Practice},
  title    = {Mature Versus Registration Studies of Immuno‐Oncology Agents: Does Value Improve With Time?},
  year     = {2020},
  note     = {PMID: 32196423},
  number   = {8},
  pages    = {e779-e790},
  volume   = {16},
  doi      = {10.1200/JOP.19.00725},
}

@Article{altman_95_surv,
  Title                    = {{{R}eview of survival analyses published in cancer journals}},
  Author                   = {Altman, D. G. and De Stavola, B. L. and Love, S. B. and Stepniewska, K. A.},
  Journal                  = {Br. J. Cancer},
  Year                     = {1995},
  Month                    = {Aug},
  Number                   = {2},
  Pages                    = {511--518},
  Volume                   = {72}
}

@Misc{ich_19,
  author = {{ICH}},
  title  = {Addendum on Estimands and Sensitivity Analysis in Clinical Trials to the guideline on statistical principles for clinical trials {E9(R1)}},
  year   = {2019},
  note   = {Accessible via \url{https://database.ich.org/sites/default/files/E9-R1_Step4_Guideline_2019_1203.pdf}},
}

@Article{huang_14,
  Title                    = {{{T}he use of phase 2 interim analysis to expedite drug development decisions}},
  Author                   = {Huang, J. and Das, A. and Burger, H. U. and Zhong, W. and Zhang, W. and Lieberman, G.},
  Journal                  = {Contemp Clin Trials},
  Year                     = {2014},
  Month                    = {Jul},
  Number                   = {2},
  Pages                    = {235--244},
  Volume                   = {38}
}

@Article{xue_17,
  author          = {Xue, Xiaonan and Agalliu, Ilir and Kim, Mimi Y and Wang, Tao and Lin, Juan and Ghavamian, Reza and Strickler, Howard D},
  journal         = {BMC medical research methodology},
  title           = {New methods for estimating follow-up rates in cohort studies.},
  year            = {2017},
  issn            = {1471-2288},
  month           = dec,
  pages           = {155},
  volume          = {17},
  abstract        = {The follow-up rate, a standard index of the completeness of follow-up, is important for assessing the validity of a cohort study. A common method for estimating the follow-up rate, the "Percentage Method", defined as the fraction of all enrollees who developed the event of interest or had complete follow-up, can severely underestimate the degree of follow-up. Alternatively, the median follow-up time does not indicate the completeness of follow-up, and the reverse Kaplan-Meier based method and Clark's Completeness Index (CCI) also have limitations. We propose a new definition for the follow-up rate, the Person-Time Follow-up Rate (PTFR), which is the observed person-time divided by total person-time assuming no dropouts. The PTFR cannot be calculated directly since the event times for dropouts are not observed. Therefore, two estimation methods are proposed: a formal person-time method (FPT) in which the expected total follow-up time is calculated using the event rate estimated from the observed data, and a simplified person-time method (SPT) that avoids estimation of the event rate by assigning full follow-up time to all events. Simulations were conducted to measure the accuracy of each method, and each method was applied to a prostate cancer recurrence study dataset. Simulation results showed that the FPT has the highest accuracy overall. In most situations, the computationally simpler SPT and CCI methods are only slightly biased. When applied to a retrospective cohort study of cancer recurrence, the FPT, CCI and SPT showed substantially greater 5-year follow-up than the Percentage Method (92%, 92% and 93% vs 68%). The Person-time methods correct a systematic error in the standard Percentage Method for calculating follow-up rates. The easy to use SPT and CCI methods can be used in tandem to obtain an accurate and tight interval for PTFR. However, the FPT is recommended when event rates and dropout rates are high.},
  citation-subset = {IM},
  completed       = {2018-07-16},
  country         = {England},
  doi             = {10.1186/s12874-017-0436-z},
  issn-linking    = {1471-2288},
  issue           = {1},
  keywords        = {Algorithms; Data Interpretation, Statistical; Follow-Up Studies; Humans; Kaplan-Meier Estimate; Male; Neoplasm Recurrence, Local, mortality; Prostatic Neoplasms, mortality; Competing risk; Loss to follow-up; Median survival time; Person-time; Reverse Kaplan-Meier survival curve},
  nlm-id          = {100968545},
  owner           = {NLM},
  pii             = {10.1186/s12874-017-0436-z},
  pmc             = {PMC5709923},
  pmid            = {29191174},
  pubmodel        = {Electronic},
  pubstatus       = {epublish},
  revised         = {2018-11-13},
}

@Article{wu_08,
  author  = {Wu, Y. and Takkenberg, J. J. and Grunkemeier, G. L.},
  journal = {Ann. Thorac. Surg.},
  title   = {{{M}easuring follow-up completeness}},
  year    = {2008},
  month   = apr,
  number  = {4},
  pages   = {1155--1157},
  volume  = {85},
}

@Article{shuster_91,
  author  = {Shuster, J. J.},
  journal = {J. Clin. Oncol.},
  title   = {{{M}edian follow-up in clinical trials}},
  year    = {1991},
  month   = jan,
  number  = {1},
  pages   = {191--192},
  volume  = {9},
}

@Article{schemper_96,
  author  = {Schemper, M. and Smith, T.L.},
  journal = {Control Clin Trials},
  title   = {{{A} note on quantifying follow-up in studies of failure time}},
  year    = {1996},
  pages   = {343--346},
  volume  = {17},
}

@Article{pocock_02,
  author  = {Pocock, S. J. and Clayton, T. C. and Altman, D. G.},
  journal = {Lancet},
  title   = {{{S}urvival plots of time-to-event outcomes in clinical trials: good practice and pitfalls}},
  year    = {2002},
  month   = may,
  number  = {9318},
  pages   = {1686--1689},
  volume  = {359},
}

@Article{gebski_18,
  author          = {Gebski, Val and Gares, Valerie and Gibbs, Emma and Byth, Karen},
  journal         = {International journal of epidemiology},
  title           = {Data maturity and follow-up in time-to-event analyses.},
  year            = {2018},
  issn            = {1464-3685},
  month           = jun,
  pages           = {850--859},
  volume          = {47},
  abstract        = {We propose methods to determine the minimum number of subjects remaining at risk after which Kaplan-Meier survival plots for time-to-event outcomes should be curtailed, as, once the number remaining at risk drops below this minimum, the survival estimates are no longer meaningful in the context of the investigation. The size of the decrease of the Kaplan-Meier survival estimate S(t) at time t if one extra event should occur is considered in two ways. In the first approach, the investigator sets a maximum acceptable absolute decrease in S(t) should one extra event occur. In the second, a minimum acceptable number of subjects still at risk is calculated by comparing the size of the decrease in S(t) if an extra event should occur with the variability of the survival estimate had all subjects been followed to that time (confidence interval approach). We recommend calculating both limits for the number still at risk and then making an informed choice in the context of the particular investigation. We explore further how the amount of information actually available can assist in considering issues of data maturity for studies whose outcome of interest is a survival percentage at a particular time point. We illustrate the approaches with a number of published studies having differing sample sizes and censoring issues. In particular, one study was the subject of some controversy regarding how far in time the Kaplan-Meier plot should be extended. The proposed methods allow for limits to be calculated simply using the output provided by most statistical packages.},
  citation-subset = {IM},
  country         = {England},
  doi             = {10.1093/ije/dyy013},
  issn-linking    = {0300-5771},
  issue           = {3},
  keywords        = {Kaplan-Meier curve; data maturity; data presentation; follow-up; number at risk; percentage of actual information available; sensitivity index; time-to-event},
  nlm-id          = {7802871},
  owner           = {NLM},
  pii             = {4851146},
  pmid            = {29444326},
  pubmodel        = {Print},
  pubstatus       = {ppublish},
  revised         = {2020-01-23},
}

@Article{clark_02,
  author  = {Clark, T. G. and Altman, D. G. and De Stavola, B. L.},
  journal = {Lancet},
  title   = {{{Q}uantification of the completeness of follow-up}},
  year    = {2002},
  month   = apr,
  number  = {9314},
  pages   = {1309--1310},
  volume  = {359},
}

@Article{betensky_15,
  author  = {Betensky, R. A.},
  journal = {Clin Trials},
  title   = {{{M}easures of follow-up in time-to-event studies: {W}hy provide them and what should they be?}},
  year    = {2015},
  month   = aug,
  number  = {4},
  pages   = {403--408},
  volume  = {12},
}

@Article{morris_19,
  author       = {Morris, Tim P and Jarvis, Christopher I and Cragg, William and Phillips, Patrick P J and Choodari-Oskooei, Babak and Sydes, Matthew R},
  journal      = {BMJ Open},
  title        = {Proposals on Kaplan{\textendash}Meier plots in medical research and a survey of stakeholder views: KMunicate},
  year         = {2019},
  number       = {9},
  volume       = {9},
  doi          = {10.1136/bmjopen-2019-030215},
  elocation-id = {e030215},
  eprint       = {https://bmjopen.bmj.com/content/9/9/e030215.full.pdf},
  publisher    = {British Medical Journal Publishing Group},
  url          = {https://bmjopen.bmj.com/content/9/9/e030215},
}

@Article{marcus_17,
  Title                    = {{{O}binutuzumab for the {F}irst-{L}ine {T}reatment of {F}ollicular {L}ymphoma}},
  Author                   = {Marcus, R. and Davies, A. and Ando, K. and Klapper, W. and Opat, S. and Owen, C. and Phillips, E. and Sangha, R. and Schlag, R. and Seymour, J. F. and Townsend, W. and Trneny, M. and Wenger, M. and Fingerle-Rowson, G. and Rufibach, K. and Moore, T. and Herold, M. and Hiddemann, W.},
  Journal                  = {N. Engl. J. Med.},
  Year                     = {2017},
  Month                    = {Oct},
  Number                   = {14},
  Pages                    = {1331--1344},
  Volume                   = {377}
}

@Article{townsend_20,
  author  = {Townsend, William and Buske, Christian and Cartron, Guillaume and Cunningham, David and Dyer, Martin J.S. and Gribben, John G. and Zhang, Zilu and Rufibach, Kaspar and Nielsen, Tina and Herold, Michael and Hiddemann, Wolfgang and Marcus, Robert},
  journal = {Journal of Clinical Oncology},
  title   = {Comparison of efficacy and safety with obinutuzumab plus chemotherapy versus rituximab plus chemotherapy in patients with previously untreated follicular lymphoma: Updated results from the phase III Gallium Study.},
  year    = {2020},
  number  = {15\_suppl},
  pages   = {8023-8023},
  volume  = {38},
  doi     = {10.1200/JCO.2020.38.15\_suppl.8023},
  url     = {https://doi.org/10.1200/JCO.2020.38.15_suppl.8023},
}

@Article{korn_86,
  author   = {Korn, Edward L.},
  journal  = {Statistics in Medicine},
  title    = {Censoring distributions as a measure of follow-up in survival analysis},
  year     = {1986},
  number   = {3},
  pages    = {255-260},
  volume   = {5},
  abstract = {Abstract The mean or median of the follow-up times as a measure of the quality or completeness of the follow-up in a survival analysis can sometimes be misleading—a more severe disease will have shorter follow-up times because of earlier deaths. We suggest here that estimates of the censoring distribution provide a more useful measure of the follow-up. This paper gives estimation procedures for both grouped-time (cohort) data and continuous data, and provides an application.},
  doi      = {https://doi.org/10.1002/sim.4780050306},
  eprint   = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/sim.4780050306},
  keywords = {Loss to follow-up, Bivariate survival analysis, Life-table method},
  url      = {https://onlinelibrary.wiley.com/doi/abs/10.1002/sim.4780050306},
}


@Article{blum_19,
  author  = {Blum, Kristie A. and Polley, Mei-Yin and Jung, Sin-Ho and Dockter, Travis J. and Anderson, Sarah and Hsi, Eric D. and Wagner-Johnston, Nina and Christian, Beth and Atkins, Jim and Cheson, Bruce D. and Leonard, John P. and Bartlett, Nancy L.},
  journal = {{CANCER}},
  title   = {{Randomized trial of ofatumumab and bendamustine versus ofatumumab, bendamustine, and bortezomib in previously untreated patients with high-risk follicular lymphoma: CALGB 50904 (Alliance)}},
  year    = {{2019}},
  number  = {{19}},
  pages   = {{3378-3389}},
  volume  = {{125}},
  doi     = {{10.1002/cncr.32289}},
}

@Article{uno_14,
  Title                    = {{{M}oving beyond the hazard ratio in quantifying the between-group difference in survival analysis}},
  Author                   = {Uno, H. and Claggett, B. and Tian, L. and Inoue, E. and Gallo, P. and Miyata, T. and Schrag, D. and Takeuchi, M. and Uyama, Y. and Zhao, L. and Skali, H. and Solomon, S. and Jacobus, S. and Hughes, M. and Packer, M. and Wei, L. J.},
  Journal                  = {J. Clin. Oncol.},
  Year                     = {2014},
  Month                    = {Aug},
  Number                   = {22},
  Pages                    = {2380--2385},
  Volume                   = {32}
}

@Article{ahern_16,
  author  = {A’Hern, Roger P.},
  journal = {Journal of Clinical Oncology},
  title   = {Restricted Mean Survival Time: An Obligatory End Point for Time-to-Event Analysis in Cancer Trials?},
  year    = {2016},
  note    = {PMID: 27507871},
  number  = {28},
  pages   = {3474-3476},
  volume  = {34},
  doi     = {10.1200/JCO.2016.67.8045},
  eprint  = {https://doi.org/10.1200/JCO.2016.67.8045},
  url     = {https://doi.org/10.1200/JCO.2016.67.8045},
}

@Article{huang_14,
  Title                    = {{{T}he use of phase 2 interim analysis to expedite drug development decisions}},
  Author                   = {Huang, J. and Das, A. and Burger, H. U. and Zhong, W. and Zhang, W. and Lieberman, G.},
  Journal                  = {Contemp Clin Trials},
  Year                     = {2014},
  Month                    = {Jul},
  Number                   = {2},
  Pages                    = {235--244},
  Volume                   = {38}
}

@Article{mick_15,
  author    = {Mick, Rosemarie and Chen, Tai-Tsang},
  journal   = {Cancer Immunology Research},
  title     = {Statistical Challenges in the Design of Late-Stage Cancer Immunotherapy Studies},
  year      = {2015},
  issn      = {2326-6066},
  number    = {12},
  pages     = {1292--1298},
  volume    = {3},
  doi       = {10.1158/2326-6066.CIR-15-0260},
  eprint    = {https://cancerimmunolres.aacrjournals.org/content/3/12/1292.full.pdf},
  publisher = {American Association for Cancer Research},
  url       = {https://cancerimmunolres.aacrjournals.org/content/3/12/1292},
}

@Article{schoenfeld_83,
  Title                    = {Sample-size formula for the proportional-hazards regression model},
  Author                   = {Schoenfeld, D.},
  Journal                  = {Biometrics},
  Year                     = {1983},
  Pages                    = {499-503},
  Volume                   = {39},
  Abstract                 = {The asymptotic distribution under alternative hypotheses is derived for a class of statistics used to test the equality of two survival distributions in the presence of arbitrary, and possibly unequal, right censoring. The test statistics include equivalents to the log rank statistic, the modified Wilcoxon statistic and the class of rank invariant test procedures introduced by Peto & Peto. When there are equal censoring distributions and the hazard functions are proportional the sample size formula for the F test used to compare exponential samples is shown to be valid for the log rank test. In certain situations the power of the log rank test falls as the amount of censoring decreases.},
  Eprint                   = {http://biomet.oxfordjournals.org/content/68/1/316.full.pdf+html},
  Owner                    = {rufiback},
  Timestamp                = {2014.09.24}
}

@Article{yung_20,
  author   = {Yung, Godwin and Liu, Yi},
  journal  = {Biometrics},
  title    = {Sample size and power for the weighted log-rank test and Kaplan-Meier based tests with allowance for nonproportional hazards},
  year     = {2020},
  number   = {3},
  pages    = {939-950},
  volume   = {76},
  doi      = {https://doi.org/10.1111/biom.13196},
  eprint   = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/biom.13196},
  keywords = {asymptotic theory, clinical trial, randomization ratio, survival analysis},
  url      = {https://onlinelibrary.wiley.com/doi/abs/10.1111/biom.13196},
}

@Article{struthers_86,
  Title                    = {Misspecified proportional hazard models},
  Author                   = {Struthers, C. A. and Kalbfleisch, J. D.},
  Journal                  = {Biometrika},
  Year                     = {1986},
  Number                   = {2},
  Pages                    = {363-369},
  Volume                   = {73},
  Eprint                   = {http://biomet.oxfordjournals.org/content/73/2/363.full.pdf+html}
}

@misc{rufibach_22,
  doi = {10.48550/arxiv.2206.05216},
  
  url = {https://arxiv.org/abs/2206.05216},
  
  author = {Rufibach, Kaspar and Grinsted, Lynda and Li, Jiang and Weber, Hans-Jochen and Zheng, Cheng and Zhou, Jiangxiu},
  
  keywords = {Methodology (stat.ME), Applications (stat.AP), FOS: Computer and information sciences, FOS: Computer and information sciences, 62N02},
  
  title = {Quantification of follow-up time in oncology clinical trials with a time-to-event endpoint: Asking the right questions},
  
  publisher = {arXiv},
  
  year = {2022},
  
  copyright = {Creative Commons Attribution 4.0 International}
}


@Article{roychoudhury_21,
  author    = {Satrajit Roychoudhury and Keaven M Anderson and Jiabu Ye and Pralay Mukhopadhyay},
  journal   = {Statistics in Biopharmaceutical Research},
  title     = {Robust Design and Analysis of Clinical Trials With Nonproportional Hazards: A Straw Man Guidance From a Cross-Pharma Working Group},
  year      = {2021},
  number    = {0},
  pages     = {1-15},
  volume    = {0},
  doi       = {10.1080/19466315.2021.1874507},
  eprint    = {https://doi.org/10.1080/19466315.2021.1874507},
  publisher = {Taylor & Francis},
  url       = {https://doi.org/10.1080/19466315.2021.1874507},
}

  @Manual{rpact,
    title = {rpact: Confirmatory Adaptive Clinical Trial Design and Analysis},
    author = {Gernot Wassmer and Friedrich Pahlke},
    year = {2021},
    note = {R package version 3.1.1},
    url = {https://CRAN.R-project.org/package=rpact},
  }
  
@Comment{jabref-meta: databaseType:bibtex;}