Survival analysis part II: multivariate data analysis – an introduction to concepts and methods
Open accessAbstract
Survival analysis involves the consideration of the time between a fixed starting point (e.g. diagnosis of cancer) and a terminating event (e.g. death). The key feature that distinguishes such data from other types is that the event will not necessarily have occurred in all individuals by the time the study ends, and for these patients, their full survival times are unknown. For instance, in studies that measure the length of survival after diagnosis of cancer, it is common for a proportion of individuals to remain alive and disease-free at the end of the follow-up period, and for these patients, we know only a lower limit on their actual time to event. Thus, special methods are required for these type of data. The explanation and demonstration of some of the methods proposed to analyse such data are the basis of this series.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The proportional hazards assumption was assessed using the log(−log(survival)) plot.
“The proportional hazards assumption was assessed using the log(−log(survival)) plot, and those that failed the assumption or that were deemed to be time dependent were entered as continuous time-dependent covariates (Bradburn et al, 2003).”
From Cohort study of adherence to adjuvant endocrine therapy, breast cancer recurrence and mortality (2013) · cites this paper as Bradburn et al, 2003
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Regression Models and Life-Tables
Cox, D. R. (1972) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1972.tb00899.x · Cited by 39,793 · see citing works
Miller, R. G. (1981) · Cited by 3,299 · see citing works
Modelling for Survival Data in Medical Research
(1995) · Technometrics · doi:10.1080/00401706.1995.10485920 · Cited by 2,159 · see citing works
Modelling Survival Data in Medical Research
Collett, D. (1994) · Springer eBooks · doi:10.1007/978-1-4899-3115-3 · Cited by 1,064 · see citing works
Survival Analysis Part I: Basic concepts and first analyses
Clark, T. G., Bradburn, M. J., Love, S., & Altman, D. G. (2003) · British Journal of Cancer · doi:10.1038/sj.bjc.6601118 · Cited by 1,045 · cited 11× · see citing works
“Examples of survival and hazard functions derived from some of these parametric models were presented in the previous paper (Clark et al , 2003).”
InfluentialSelf-citationLinear regression with censored data
Buckley, J. D., & JAMES, I. R. (1979) · Biometrika · doi:10.1093/biomet/66.3.429 · Cited by 1,032 · cited 1× · see citing works
“Alternative methods include the method of Buckley and James (1979), which is discussed by Stare et al (2000), and semiparametric AFT models, in which the baseline survivor function is estimated nonparame-trically (see Wei, 1992, for an overview), but have not yet been widely implemented in…”
Modelling Survival Data in Medical Research.
McLachlan, G. J., & Collett, D. (1994) · Biometrics · doi:10.2307/2533471 · Cited by 1,023 · see citing works
Wei, L. J. (1992) · Statistics in Medicine · doi:10.1002/sim.4780111409 · Cited by 827 · cited 1× · see citing works
“…include the method of Buckley and James (1979), which is discussed by Stare et al (2000), and semiparametric AFT models, in which the baseline survivor function is estimated nonparame-trically (see Wei, 1992, for an overview), but have not yet been widely implemented in statistical software.”
A linear regression model for the analysis of life times
Aalen, O. O. (1989) · Statistics in Medicine · doi:10.1002/sim.4780080803 · Cited by 725 · cited 1× · see citing works
“These important issues will be addressed in the subsequent paper in this series.”
Multivariate survival analysis using Cox's regression model
Christensen, E. I. (1987) · Hepatology · doi:10.1002/hep.1840070628 · Cited by 372 · cited 1× · see citing works
“This information could then be displayed via tabular or Christensen (1987) based on the Cox model, but can also be used when fitting fully parametric models.”
Accelerated Life Models: Modeling and Statistical Analysis
Bagdonavičius, V., & Nikulin, M. (2001) · Cited by 325 · see citing works
Bagdonavičius, V., & Nikulin, M. (2001) · Chapman & Hall/CRC eBooks · doi:10.1201/9781420035872 · Cited by 215 · see citing works
A prognostic model for ovarian cancer
Clark, T. G., Stewart, M., Altman, D. G., Gabra, H., & Smyth, J. F. (2001) · British Journal of Cancer · doi:10.1054/bjoc.2001.2030 · Cited by 192 · cited 4× · see citing works
“In a previous analysis that involved some of the patients in the present data, Clark et al (2001) produced a nomogram to summarise the impact of these and other covariates, and thus allows the reader to predict the median survival and the 2- and 5year survival probabilities for patients with given prognostic informati…”
InfluentialSelf-citationFurther results on the non‐parametric linear regression model in survival analysis
Aalen, O. O. (1993) · Statistics in Medicine · doi:10.1002/sim.4780121705 · Cited by 176 · cited 1× · see citing works
“These plots are sometimes called Aalen plots, and they are also used to provide an informal assessment of the adequacy of the proportional hazards assumption in the Cox model, although Aalen considered its primary role as an alternative model in its own right (Aalen, 1993).”
Kay, R., & Kinnersley, N. (2002) · Drug Information Journal · doi:10.1177/009286150203600312 · Cited by 95 · cited 1× · see citing works
“As yet, however, AFT models are relatively unfamiliar and seen rarely in medical research papers (see Kay and Kinnersley, 2002).”
Flagged first, then by citations
1 of the 16 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Moons, K. G. M., Altman, D. G., Reitsma, J. B., Ioannidis, J. P. A., Macaskill, P., Steyerberg, E. W., Vickers, A. J., Ransohoff, D. F., & Collins, G. S. (2015) · Annals of Internal Medicine · doi:10.7326/m14-0698 · Cited by 5,147 · see citing works
Self-citationUALCAN: A Portal for Facilitating Tumor Subgroup Gene Expression and Survival Analyses
Chandrashekar, D. S., Bashel, B., Balasubramanya, S. A. H., Creighton, C. J., Ponce-Rodriguez, I., Chakravarthi, B. V. S. K., & Varambally, S. (2017) · Neoplasia · doi:10.1016/j.neo.2017.05.002 · Cited by 6,086 · see citing works
“In order to assess the combined survival effect of gene expression and clinical parameters such as patient race, gender, BMI, cancer subtypes, tumor grade, etc., we applied multivariate Kaplan – Meier survival analysis [46].”
MethodReporting Recommendations for Tumor Marker Prognostic Studies (REMARK): Explanation and Elaboration
Altman, D. G., McShane, L. M., Sauerbrei, W., & Taube, S. E. (2012) · PLoS Medicine · doi:10.1371/journal.pmed.1001216 · Cited by 1,019 · see citing works
“More extensive discussions of statistical analysis methods for binary outcome and for survival data can be found elsewhere [74,102,114-125].”
MethodSelf-citationA note on competing risks in survival data analysis
Satagopan, J. M., Ben‐Porat, L., Berwick, M., Robson, M. E., Kutler, D. I., & Auerbach, A. D. (2004) · British Journal of Cancer · doi:10.1038/sj.bjc.6602102 · Cited by 752 · see citing works
Shattuck, P. T., Durkin, M., Maenner, M., Newschaffer, C., Mandell, D. S., Wiggins, L., Lee, L.-C., Rice, C., Giarelli, E., Kirby, R., et al. (2009) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1097/chi.0b013e31819b3848 · Cited by 623 · see citing works
“Time ratios greater than 1 indicate an effect that delays the timing of identification; whereas, time ratios less than 1 indicate an accelerating effect on the timing of identification.(18) For instance, a time ratio of 2 would mean a 1-unit change in the covariate and was associated with a doubling of the median age…”
BackgroundBradburn, M. J., Clark, T. G., Love, S., & Altman, D. G. (2003) · British Journal of Cancer · doi:10.1038/sj.bjc.6601120 · Cited by 391 · see citing works
“607 British Journal of Cancer (2003) 89(4), 605 – 611& 2003 Cancer Research UK improve the fit to a significant degree.”
BackgroundMethodInfluentialSelf-citationBellera, C. A., MacGrogan, G. M., Debled, M., de Lara, C. T., Brouste, V., & Mathoulin‐Pélissier, S. (2010) · BMC Medical Research Methodology · doi:10.1186/1471-2288-10-20 · Cited by 385 · see citing works
“Special papers in statistics have been published in the oncology literature providing general introductions to survival analysis [5-8]; topics covered included summarizing survival data, testing for a difference between groups, presenting existing statistical models, or assessing the adequacy of a survival model.”
Reporting recommendations for tumor marker prognostic studies (REMARK): explanation and elaboration
Altman, D. G., McShane, L. M., Sauerbrei, W., & Taube, S. E. (2012) · BMC Medicine · doi:10.1186/1741-7015-10-51 · Cited by 374 · see citing works
“More extensive discussions of statistical analysis methods for binary outcome and for survival data can be found elsewhere [73,99-111].”
Self-citationTOTAL ANKLE ARTHROPLASTY IN INFLAMMATORY JOINT DISEASE WITH USE OF TWO MOBILE-BEARING DESIGNS
Doets, H. C., Brand, R., & Nelissen, R. G. H. H. (2006) · Journal of Bone and Joint Surgery · doi:10.2106/00004623-200606000-00015 · Cited by 329 · see citing works
Combs, S. E., Thilmann, C., Edler, L., Debus, J., & Schulz–Ertner, D. (2005) · Journal of Clinical Oncology · doi:10.1200/jco.2005.03.4157 · Cited by 328 · see citing works
Coens, C., Pe, M. L., Dueck, A. C., Sloan, J. A., Basch, E., Calvert, M., Campbell, A., Cleeland, C. S., Cocks, K., Collette, L., et al. (2020) · The Lancet Oncology · doi:10.1016/s1470-2045(19)30790-9 · Cited by 327 · see citing works
Evolutionary divergence of HLA class I genotype impacts efficacy of cancer immunotherapy
Chowell, D., Krishna, C., Pierini, F., Makarov, V., Rizvi, N. A., Kuo, F., Morris, L. G. T., Riaz, N., Lenz, T. L., & Chan, T. A.-T. (2019) · Nature Medicine · doi:10.1038/s41591-019-0639-4 · Cited by 309 · see citing works
Survival Analysis and Interpretation of Time-to-Event Data: The Tortoise and the Hare
Schober, P. R., & Vetter, T. R. (2018) · Anesthesia & Analgesia · doi:10.1213/ane.0000000000003653 · Cited by 308 · see citing works
Cohort study of adherence to adjuvant endocrine therapy, breast cancer recurrence and mortality
Makubate, B., Donnan, P. T., Dewar, J. A., Thompson, A. M., & McCowan, C. (2013) · British Journal of Cancer · doi:10.1038/bjc.2013.116 · Cited by 298 · see citing works
“The proportional hazards assumption was assessed using the log( log(survival)) plot, and those that failed the assumption or that were deemed to be time dependent were entered as continuous time-dependent covariates (Bradburn et al, 2003).”
BackgroundMethodBhattacharjee, S., Gopal, R. D., Lertwachara, K., Marsden, J. R., & Telang, R. (2007) · Management Science · doi:10.1287/mnsc.1070.0699 · Cited by 249 · see citing works
“Bradburn et al. (2003, p. 434) report the following important result: When the survival times follow a Weibull distribution, it can be shown that the AFT and PH models are the same.”
BackgroundMethodInfluentialSpringboard Internationalization by Emerging Market Firms: Speed of First Cross-Border Acquisition
Kumar, V., Singh, D. A., Purkayastha, A., Popli, M., & Gaur, A. S. (2019) · Journal of International Business Studies · doi:10.1057/s41267-019-00266-0 · Cited by 251 · see citing works
Decision Making in Health and Medicine: Integrating Evidence and Values
Hunink, M. G. M., Weinstein, M. C., Wittenberg, E., Drummond, M. F., Pliskin, J. S., Wong, J. B., & Glasziou, P. P. (2014) · doi:10.1017/cbo9781139506779 · Cited by 425 · see citing works
Sample Sizes for Clinical Trials
Julious, S. A. (2009) · Chapman & Hall/CRC eBooks · doi:10.1201/9781584887409 · Cited by 227 · see citing works
Time From Hearing Aid Candidacy to Hearing Aid Adoption: A Longitudinal Cohort Study
Simpson, A. N., Matthews, L. J., Cassarly, C. N., & Dubno, J. R. (2018) · Ear and Hearing · doi:10.1097/aud.0000000000000641 · Cited by 197 · see citing works
Methods to Analyze Time‐to‐Event Data: The Cox Regression Analysis
ElHafeez, S. A., D’Arrigo, G., Leonardis, D., Fusaro, M., Tripepi, G. L., & Roumeliotis, S. K. (2021) · Oxidative Medicine and Cellular Longevity · doi:10.1155/2021/1302811 · Cited by 195 · see citing works
“It is a semiparametric method because there is no assumption about the distribution of survival times, but it assumes that the effects of different variables on survival are constant over time (proportionality assumption) and additive over a particular scale [7].”
Survival Analysis Part IV: Further concepts and methods in survival analysis
Clark, T. G., Bradburn, M. J., Love, S., & Altman, D. G. (2003) · British Journal of Cancer · doi:10.1038/sj.bjc.6601117 · Cited by 187 · see citing works
Self-citationCan we predict poor recovery from recent-onset nonspecific low back pain? A systematic review
Kent, P. M., & Keating, J. L. (2007) · Manual Therapy · doi:10.1016/j.math.2007.05.009 · Cited by 185 · see citing works
Vallejo, A., Perurena, N., Guruceaga, E., Mazur, P. K., Martínez-Canarias, S., Zandueta, C., Valencia, K., Arricibita, A., Gwinn, D. M., Sayles, L. C., et al. (2017) · Nature Communications · doi:10.1038/ncomms14294 · Cited by 175 · see citing works
Effect of Hospitalist Workload on the Quality and Efficiency of Care
Elliott, D. J., Young, R. S. K., Brice, J., Aguiar, R., & Kolm, P. (2014) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2014.300 · Cited by 162 · see citing works
Gleisner, A. (2008) · Archives of Surgery · doi:10.1001/archsurg.143.12.1204 · Cited by 159 · see citing works
Janssens, G. O. R. J., Gandola, L., Bolle, S., Mandeville, H., Albiac, M. R., Beek, K. V., Benghiat, H., Hoeben, B. A. W., Madrid, A. M. L., Kortmann, R., et al. (2017) · European Journal of Cancer · doi:10.1016/j.ejca.2016.12.007 · Cited by 157 · see citing works
IPO Survival in a Reputational Market
Espenlaub, S. K., Khurshed, A., & Mohamed, A. (2012) · Journal of Business Finance & Accounting · doi:10.1111/j.1468-5957.2012.02280.x · Cited by 150 · see citing works
“The AFT model is typically expressed in terms of a log-linear function with respect to time (see e.g. Hensler et al. 1997; Bradburn et al. 2003) jp110j ...)Ln(T εβββ +++= pXX (3) Specifically, we estimate the following…”
Limitations and Biases of the Surveillance, Epidemiology, and End Results Database
Park, H. S.-M., Lloyd, S. A. J., Decker, R. H., Wilson, L. D., & Yu, J. B. (2012) · Current Problems in Cancer · doi:10.1016/j.currproblcancer.2012.03.011 · Cited by 134 · see citing works
Prognostic Models: A Methodological Framework and Review of Models for Breast Cancer
Altman, D. G. (2009) · Cancer Investigation · doi:10.1080/07357900802572110 · Cited by 129 · see citing works
“The most common analytical technique in prognostic studies in cancer is the Cox proportional hazards (PH) model, which describes the relationship between the event incidence, as expressed by the hazard function, and a set of covariates (10, 25).”
MethodSelf-citationEvaluation and comparison of multi-omics data integration methods for cancer subtyping
Duan, R., Gao, L., Gao, Y., Hu, Y., Xu, H., Huang, M., Song, K., Wang, H., Dong, Y., Jiang, C., et al. (2021) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1009224 · Cited by 122 · see citing works
Cucchetti, A., Cescon, M., Ercolani, G., Bigonzi, E., Torzilli, G., & Pinna, A. D. (2012) · Annals of Surgical Oncology · doi:10.1245/s10434-012-2450-z · Cited by 125 · see citing works
“This feature represents a potential bias that must be taken into consideration in interpreting results from observational studies even if multivariate analysis is performed.(37) Patients with HCC constitute a particular case in oncology because their prognosis relies not only on the tumor stage,”
BackgroundAntecedents of Viewers’ Live Streaming Watching: A Perspective of Social Presence Theory
Chen, J., & Liao, J. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.839629 · Cited by 134 · see citing works
“In this study, the sample data were split into groups of lower streamer attractiveness and higher streamer attractiveness according to the mean of streamer attraction (Bradburn et al., 2003).”
MethodFactors associated with recovery from anorexia nervosa
Zerwas, S., Lund, B. C., Von Holle, A., Thornton, L. M., Berrettini, W. H., Brandt, H., Crawford, S., Fichter, M. M., Halmi, K. A., Johnson, C., et al. (2013) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2013.02.011 · Cited by 111 · see citing works
“The Cox regression model is a semi-parametric regression method estimating the likelihood of recovery and includes information on individuals whose recovery status is unknown (Collett, 1994, Bradburn et al., 2003).”
MethodMorden, J. P., Lambert, P. C., Latimer, N. R., Abrams, K. R., & Wailoo, A. (2011) · BMC Medical Research Methodology · doi:10.1186/1471-2288-11-4 · Cited by 114 · see citing works
“One of the limitations of this method and its practical use is that estimates are given in the AFT model form which is less commonly seen in medical literature than hazard ratios from a proportional hazards model [34].”
MethodFractionated stereotactic radiotherapy of optic pathway gliomas: Tolerance and long-term outcome
Combs, S. E., Schulz–Ertner, D., Moschos, D., Thilmann, C., Huber, P. E., & Debus, J. (2005) · International Journal of Radiation Oncology*Biology*Physics · doi:10.1016/j.ijrobp.2004.12.081 · Cited by 105 · see citing works
The analysis of survival data in nephrology: basic concepts and methods of Cox regression
van Dijk, P. C. W., Jager, K. J., Zwinderman, A. H., Zoccali, C., & Dekker, F. W. (2008) · Kidney International · doi:10.1038/ki.2008.294 · Cited by 104 · see citing works
Multimodal deep learning to predict prognosis in adult and pediatric brain tumors
Steyaert, S., Qiu, Y. L., Zheng, Y., Mukherjee, P., Vogel, H. S., & Gevaert, O. (2023) · Communications Medicine · doi:10.1038/s43856-023-00276-y · Cited by 115 · see citing works
“Not assuming an underlying distribution of survival times combined with its multivariate nature makes Cox-PH widely accepted as the method of choice to model cancer prognosis and to compare survival characteristics between different groups 14 .”
MethodComparing proportional hazards and accelerated failure time models: an application in influenza
Patel, K., Kay, R., & Rowell, L. (2006) · Pharmaceutical Statistics · doi:10.1002/pst.213 · Cited by 103 · see citing works
“[2,3] provide a comprehensive introduction to the analysis of time-to-event data in the context of cancer trials.”
Huang, Y., Li, J., Li, M., & Aparasu, R. R. (2023) · BMC Medical Research Methodology · doi:10.1186/s12874-023-02078-1 · Cited by 108 · see citing works
Martínez-Ledesma, E., Verhaak, R. G. W., & Treviño, V. (2015) · Scientific Reports · doi:10.1038/srep11966 · Cited by 103 · see citing works
Automated image analysis of NSCLC biopsies to predict response to anti-PD-L1 therapy
Althammer, S., Tan, T. H., Spitzmüller, A., Rognoni, L., Wiestler, T., Herz, T., Widmaier, M., Rebelatto, M. C., Kaplon, H., Damotte, D., et al. (2019) · Journal for ImmunoTherapy of Cancer · doi:10.1186/s40425-019-0589-x · Cited by 98 · see citing works
Recommended Guidelines for the Conduct and Evaluation of Prognostic Studies in Veterinary Oncology
Webster, J. D., Dennis, M. M., Dervisis, N. G., Heller, J., Bacon, N. J., Bergman, P. J., Bienzle, D., Cassali, G. D., Castagnaro, M., Cullen, J. M., et al. (2010) · Veterinary Pathology · doi:10.1177/0300985810377187 · Cited by 100 · see citing works
“The use of regression models (eg, Cox’s proportional hazards model) or accelerated time function models allows for the inclusion of multiple prognostic variables.(3,4) Model building should be based on clinical as well as statistical considerations, and whereas stepwise techniques are appropriate, fully automated impl…”
MethodSurvival time tool to guide care planning in people with dementia
Haaksma, M. L., Eriksdotter, M., Rizzuto, D., Leoutsakos, J.-M. S., Olde Rikkert, M. G. M., Melis, R. J. F., & Garcia-Ptacek, S. (2020) · Neurology · doi:10.1212/wnl.0000000000008745 · Cited by 95 · see citing works
“Cox proportional hazards models were used to calculate hazard ratios (HRs) with 95% confidence intervals (CIs) for mortality.(15) The assumption of proportionality was verified by examining log minus log plots and Schoenfeld residuals.”
MethodFontaine, A., Jiolle, D., Moltini-Conclois, I., Lequime, S., & Lambrechts, L. (2016) · Scientific Reports · doi:10.1038/srep24885 · Cited by 91 · see citing works
Immune Phenotype Predicts Risk for Posttransplantation Squamous Cell Carcinoma
Carroll, R. P., Segundo, D. S., Hollowood, K., Marafioti, T., Clark, T. G., Harden, P., & Wood, K. J. (2010) · Journal of the American Society of Nephrology · doi:10.1681/asn.2009060669 · Cited by 89 · see citing works
Self-citationTreatment of Cerebral Metastases from Breast Cancer with Stereotactic Radiosurgery
Combs, S. E., Schulz–Ertner, D., Thilmann, C., Edler, L., & Debus, J. (2004) · Strahlentherapie und Onkologie · doi:10.1007/s00066-004-1299-x · Cited by 88 · see citing works
“Age and stage at primary diagnosis of breast cancer, Karnofsky performance score, size and number of cerebral lesions, extracerebral disease, previous neurosurgical resection, and clinical symptoms before SRS were determined using the log-rank test and the univariate and multivariate Cox proportional hazards model, re…”
A new method for the analysis of germination and emergence data of weed species
Onofri, A., Gresta, F., & Tei, F. (2010) · Weed Research · doi:10.1111/j.1365-3180.2010.00776.x · Cited by 88 · see citing works
Stereotactically Guided Fractionated Re-irradiation in Recurrent Glioblastoma Multiforme
Combs, S. E., Gutwein, S., Thilmann, C., Huber, P. E., Debus, J., & Schulz–Ertner, D. (2005) · Journal of Neuro-Oncology · doi:10.1007/s11060-004-2463-y · Cited by 87 · see citing works
Predictors of Psychiatric Inpatient Suicide
Madsen, T., Mortensen, P. B., Agerbo, E., & Nordentoft, M. (2011) · The Journal of Clinical Psychiatry · doi:10.4088/jcp.10m06473 · Cited by 85 · see citing works
Ofori‐Asenso, R., Zomer, E., Chin, K. L., Si, S., Markey, P. G., TACEY, M. A., Curtis, A. J., Zoungas, S., & Liew, D. (2018) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph15112532 · Cited by 82 · see citing works
“In the multivariable Cox proportional hazards model, the only variable violating the proportional hazards assumption was stroke type, and therefore this was included as a stratifying factor [23].”
MethodChaou, C., Chen, H.-H., Chang, S. H., Tang, P., Pan, S., Yen, A. M., & Chiu, T. (2017) · PLoS ONE · doi:10.1371/journal.pone.0165756 · Cited by 81 · see citing works
Longitudinal change of sleep timing: association between chronotype and longevity in older adults
Didikoğlu, A., Maharani, A., Payton, A., Pendleton, N., & Canal, M. M. (2019) · Chronobiology International · doi:10.1080/07420528.2019.1641111 · Cited by 77 · see citing works
“The Cox regression proportional hazard models estimated hazard ratios for chronotype clusters and other covariates, which indicated the extent to which a covariate was associated with increased mortality as compared with a reference (Bradburn et al. 2003).”
BackgroundBrandl, S., Paul, C., Knoke, T., & Falk, W. (2019) · Forest Ecology and Management · doi:10.1016/j.foreco.2019.117652 · Cited by 79 · see citing works
Surgical Excision versus Curettage plus Cryosurgery in the Treatment of Basal Cell Carcinoma
KUIJPERS, D. I. M., Thissen, M. R. T. M., Berretty, P. J. M., IDELER, F. H. L. B., Nelemans, P. J., & NEUMANN, M. H. A. M. (2007) · Dermatologic Surgery · doi:10.1111/j.1524-4725.2007.33117.x · Cited by 78 · see citing works
“Histopathologic type Nodular 51 45 96 Superficial 0 4 4 Localization Forehead/temple 15 (29) 12 (25) 27 (27) Cheek/chin 9 (18) 7 (14) 16 (16) Nose/paranasal 11 (22) 11 (22) 22 (22) Lips/mouth 2 (4) 3 (6) 5 (5) Periocular 6 (12) 7 (14) 13 (13) Ears/periauricular 4 (8) 3 (6) 7 (7) Neck 3 (6) 5 (10) 8 (8) Chest/back 1 (2…”
Martínez, E. Z., Achcar, J. A., Jacome, A. A. D. A., & dos Santos, J. S. (2013) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2013.07.021 · Cited by 78 · see citing works
“n the lifetime data analysis, researchers commonly use tandard non-parametrical techniques, such as Kaplan–Meier stimators or log-rank test [1], semi-parametrical models (for xample, proportional hazards model in presence of covarites [2] or standard parametrical models using some popular ifetime distributions [3].”
MethodImproved survival analysis by learning shared genomic information from pan-cancer data
Kim, S., Kim, K., Choe, J., Lee, I., & Kang, J. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btaa462 · Cited by 77 · see citing works
Oostdijk, E. A. N., de Smet, A. M. G. A., Kesecioğlu, J., & Bonten, M. J. M. (2011) · Critical Care Medicine · doi:10.1097/ccm.0b013e318208ee26 · Cited by 75 · see citing works
“47 Median onset (interquartile range) 10 (11) 13 (15.”
MethodTroiano, G., Mastrangelo, F., Caponio, V. C. A., Laino, L., Cirillo, N., & Muzio, L. L. (2018) · Journal of Dental Research · doi:10.1177/0022034518762090 · Cited by 75 · see citing works
“As shown in Figures 2 and 3, we performed a meta-analysis of subgroups for univariate and multivariate analysis, as it is well known that multivariate analysis allows for adjustment of patient-related factors, which could affect the survival time of patients (Bradburn et al. 2003).”
MethodMultivariate analysis of NMR‐based metabolomic data
Debik, J., Sangermani, M., Wang, F., Madssen, T. S., & Giskeødegård, G. F. (2021) · NMR in Biomedicine · doi:10.1002/nbm.4638 · Cited by 74 · see citing works
“Survival analysis involves analyzing the effect of one or more covariates on the expected duration of time until an event such as death, disease occurrence, or recurrence.(28) The Cox regression model may be expressed mathematically for individual i i1⁄41,.”
BackgroundAubry, L. M., Cam, E., Koons, D. N., Monnat, J., & Pavard, S. (2010) · Journal of Animal Ecology · doi:10.1111/j.1365-2656.2010.01784.x · Cited by 71 · see citing works
“Each covariate within the model is assumed to act multiplicatively (i.e. proportionally) on the baseline mortality hazard at each time step (e.g. Bradburn et al. 2003), such as hðt;XiÞ ¼ h0ðtÞ expð Pp i¼1 biXiÞ where h0 refers to the baseline hazard (i.e. hazard’s value when all covariate values…”
BackgroundFoster, T., Willetts, J., Lane, M., Thomson, P., Katuva, J., & Hope, R. (2018) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2017.12.302 · Cited by 69 · see citing works
“The techniques that fall within the survival analysis umbrella have been used extensively in medical literature due to their ability to accommodate right-censored data – that is, subjects that have not yet undergone the event of interest (such as disease onset, remission or death) by the end of an observation period (…”
Gray, J. E., Ahn, M., Oxnard, G. R., Shepherd, F. A., Imamura, F., Cheng, Y., Okamoto, I., Cho, B. C., Lin, M., Wu, Y.-L. L. C., et al. (2023) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-22-3146 · Cited by 71 · see citing works
Incidence of anaemia among HIV‐infected patients treated with highly active antiretroviral therapy*
Curkendall, S., Richardson, J., Emons, M., Fisher, A., & Everhard, F. (2007) · HIV Medicine · doi:10.1111/j.1468-1293.2007.00500.x · Cited by 68 · see citing works
Practical methods for incorporating summary time-to-event data into meta-analysis: updated guidance
Tierney, J. F., Burdett, S., & Fisher, D. J. (2025) · Systematic Reviews · doi:10.1186/s13643-025-02752-z · Cited by 67 · see citing works
“The coefficient for the effect of the research treatment from such a model provides an alternative “direct” estimate of the log HR [7], with an associated standard error (SE) and p value.”
Survival analysis: Part I — analysis of time-to-event
In, J., & Lee, D. K. (2018) · Korean Journal of Anesthesiology · doi:10.4097/kja.d.18.00067 · Cited by 66 · see citing works
“This method does not presuppose any specific distribution and can analyze any variables that may influence the occurrence, unlike Kaplan-Meier survival analysis, and is thus regarded as a semiparametric method [16,17].”
MethodHOX D13 expression across 79 tumor tissue types
Cantile, M., Franco, R., Tschan, A., Baumhoer, D., Zlobec, I., Schiavo, G., Forte, I. M., Bihl, M., Liguori, G., Botti, G., et al. (2009) · International Journal of Cancer · doi:10.1002/ijc.24438 · Cited by 65 · see citing works
Dhanorkar, S., Siemsen, E., & Linderman, K. (2017) · Management Science · doi:10.1287/mnsc.2017.2748 · Cited by 63 · see citing works
Biostatistics series module 9: Survival analysis
Hazra, A., & Gogtay, N. (2017) · Indian Journal of Dermatology · doi:10.4103/ijd.ijd_201_17 · Cited by 63 · see citing works
The initial development and assessment of an automatic alert warning of acute kidney injury
Thomas, M., Sitch, A. J., & Dowswell, G. (2010) · Nephrology Dialysis Transplantation · doi:10.1093/ndt/gfq710 · Cited by 62 · see citing works
“Weibull survival analysis [17,18] was carried out with Stata software (Stata Corp.”
MethodTang, T., Hwang, A., Liu, L.-K., Lee, W., Chen, L.-Y., Wu, Y., Huang, C., Hung, C.-H., Wang, C., Lin, M.-H., et al. (2017) · The Journals of Gerontology Series A · doi:10.1093/gerona/glx148 · Cited by 60 · see citing works
“Survival analysis by the Cox proportional hazard model was used to estimate the association of FNIH-defined sarcopenia with composite adverse outcomes and all-cause mortality, and to obtain the hazard ratios and their 95% confidence intervals (38,39).”
MethodDwivedi, A. K., & Shukla, R. (2019) · Cancer Reports · doi:10.1002/cnr2.1211 · Cited by 58 · see citing works
Brunet‐Ratnasingham, E., Anand, S. P., Gantner, P., Dyachenko, A., Moquin‐Beaudry, G., Brassard, N., Beaudoin-Bussières, G., Pagliuzza, A., Gasser, R., Benlarbi, M., et al. (2021) · Science Advances · doi:10.1126/sciadv.abj5629 · Cited by 53 · see citing works
Youth sport dropout according to the Process-Person-Context-Time model: a systematic review
Moulds, K., Galloway, S., Abbott, S., & Cobley, S. (2022) · International Review of Sport and Exercise Psychology · doi:10.1080/1750984x.2021.2012817 · Cited by 38 · see citing works
“…ts of latter measures, like hazard rates, is their capability to determine dropout occurrence during a standardised exposure time-period (Blagoev et al., 2012), while accounting for sample sizes in respective groups (e.g. Hazard Ratios - Bradburn et al., 2003); so, should be encouragingly adopted.”
BackgroundAuthier, M., Bentaleb, I., Ponchon, A., Martin, C., & Guinet, C. (2012) · PLoS ONE · doi:10.1371/journal.pone.0032026 · Cited by 48 · see citing works
“We estimated 4 individual parameters describing a broken-stick model and subsequently used them as predictors in an Accelerated Failure Time (AFT) model [50,51].”
MethodMoazemi, S., Erle, A., Lütje, S., Gaertner, F. C., Essler, M., & Bundschuh, R. A. (2021) · Diagnostics · doi:10.3390/diagnostics11020186 · Cited by 57 · see citing works
“the Kaplan–Meier estimator [20] is used to analyze and visualize the survival prediction results.”
MethodRaquin, V., Merkling, S. H., Gausson, V., Moltini-Conclois, I., Frangeul, L., Varet, H., Dillies, M., Saleh, M., & Lambrechts, L. (2017) · PLoS neglected tropical diseases · doi:10.1371/journal.pntd.0006152 · Cited by 56 · see citing works
“A Cox regression model including dsRNA injection and DENV exposure as covariates was used to compare mosquito survival across treatments [67].”
Freeman, D. E. (2018) · Equine Veterinary Journal · doi:10.1111/evj.12817 · Cited by 56 · see citing works
Santos, J. A., Leite, A., Soares, P., Duarte, R., & Nunes, C. (2021) · BMC Public Health · doi:10.1186/s12889-021-12245-y · Cited by 55 · see citing works
“Cox proportional hazards model [29] was used to estimate the effect of the clinical and sociodemographic variables on the time until the event of interest.”
MethodCoronavirus disease 2019 (COVID-19): survival analysis using deep learning and Cox regression model
Atlam, M., Torkey, H., El-Fishawy, N. A., & Salem, H. (2021) · Pattern Analysis and Applications · doi:10.1007/s10044-021-00958-0 · Cited by 54 · see citing works
Wong, S. H., Petrie, A., & Plant, G. T. (2016) · Journal of Neuro-Ophthalmology · doi:10.1097/wno.0000000000000350 · Cited by 54 · see citing works
“The guideline for number of predictors to include in a model is 10% of the outcome of interest in each of the response categories, that is, in this case, 10% of 19 patients who developed GMG within 2 years (for the logistic model) or 30 patients for the survival analyses (16,32).”
BackgroundPérez-Navarro, L. M., Restrepo, B. I., Fuentes-Domínguez, F. J., Duggirala, R., Morales‐Romero, J., López-Alvarenga, J. C., Comas, I., & Zenteno‐Cuevas, R. (2017) · Tuberculosis · doi:10.1016/j.tube.2017.01.006 · Cited by 53 · see citing works
Xu, W. V., Puligandla, M., Halbert, B. T., Haas, N. B., Flaherty, K. T., Uzzo, R. G., Dutcher, J. P., DiPaola, R. S., Sabbisetti, V. S., & Bhatt, R. S. (2021) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-21-0025 · Cited by 52 · see citing works
“Similar associations between KIM-1 and DFS were seen when using the imputed low KIM-1 values (Supplementary Table S1).”
MethodInfluentialNater, A., Martin, A. R., Sahgal, A., Choi, D., & Fehlings, M. G. (2017) · PLoS ONE · doi:10.1371/journal.pone.0171507 · Cited by 52 · see citing works
Big Data Toolsets to Pharmacometrics: Application of Machine Learning for Time‐to‐Event Analysis
Gong, X., Hu, M., & Zhao, L. Y. (2018) · Clinical and Translational Science · doi:10.1111/cts.12541 · Cited by 53 · see citing works
“With approach i, six groups of survival data sets were generated with different relationships between the predictor variables in the hazard function: (1) linear, (2) nonlinear, (3) interaction, (4) nonlinear + interaction, (5) nonlinear + interaction + correlation, and (6) high-dimension.”
MethodAbraham, J. A., Weaver, M. J., Hornick, J. L., Zurakowski, D., & Ready, J. E. (2012) · Journal of Bone and Joint Surgery · doi:10.2106/jbjs.k.00460 · Cited by 48 · see citing works
“AJCC stage* Ia 2 (2) 0 (0) Ib 1 (1) 0 (0) IIa 6 (5) 1 (17) IIb 24 (21) 8 (33) IIc 4 (3) 1 (25) III 60 (52) 36 (60) IV 18 (16) 14 (78)”
Recurrent low-grade gliomas: the role of fractionated stereotactic re-irradiation
Combs, S. E., Ahmadi, R., Schulz–Ertner, D., Thilmann, C., & Debus, J. (2005) · Journal of Neuro-Oncology · doi:10.1007/s11060-004-2029-z · Cited by 47 · see citing works
Jaskot, A., Silveyra, A. C., Plantinga, A., Flury, S., Hayes, M. J., Chisholm, J., Heckman, T., Pentericci, L., Schaerer, D., Trebitsch, M., et al. (2024) · Astrophysical Journal · doi:10.3847/1538-4357/ad58b9 · Cited by 33 · see citing works
Wolfe, M. L., Koons, D. N., Stoner, D. C., Terletzky, P. A., Gese, E. M., Choate, D. M., & Aubry, L. M. (2014) · Biological Conservation · doi:10.1016/j.biocon.2014.12.008 · Cited by 46 · see citing works
“Rather, each covariate within the model is assumed to act multiplicatively (proportionally) on the time-specific baseline mortality hazard and across covariate levels (Bradburn et al., 2003), such as hi(t) = h0(t) exp (biXi) where h0 refers to the baseline hazard (i.”
BackgroundProportional hazards models of infrastructure system recovery
Barker, K., & Baroud, H. (2014) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2013.12.004 · Cited by 45 · see citing works
“The accelerated failure time model is used especially when an underlying hazard function is known, or when the baseline hazard function would vary from observation to observation [33].”
MethodRisk of tuberculin conversion among healthcare workers and the adoption of preventive measures
Baussano, I., Bugiani, M., Carosso, A., Df, M., Barocelli, A. P., Tagna, M., Cascio, V., Piccioni, P., & Arossa, W. (2006) · Occupational and Environmental Medicine · doi:10.1136/oem.2006.028068 · Cited by 45 · see citing works
“[23,24] The following covariates were separately investigated with respect to their influence on the HR for being infected with Mycobacterium tuberculosis: age, gender, duration of employment as HCW (categorised as <1 and >1 years), working in a hospital setting rather than a community setting, occupation, workplace a…”
MethodCommitted anchor investment and IPO survival – The roles of cornerstone and strategic investors
Espenlaub, S. K., Khurshed, A., Mohamed, A., & Saadouni, B. (2016) · Journal of Corporate Finance · doi:10.1016/j.jcorpfin.2016.08.016 · Cited by 45 · see citing works
“The time ratio is calculated as the exponential of the AFT coefficient (Bradburn et al. 2003).”
Ebert, M. A., Gulliford, S., Acosta, O., de Crevoisier, R., McNutt, T., Heemsbergen, W. D., Witte, M. G., Palma, G., Rancati, T., & Fiorino, C. (2021) · Physics in Medicine and Biology · doi:10.1088/1361-6560/ac0681 · Cited by 44 · see citing works
Self-image and suicide in a Swedish national eating disorders clinical register
Runfola, C. D., Thornton, L. M., Pisetsky, E. M., Bulik, C. M., & Birgegård, A. (2013) · Comprehensive Psychiatry · doi:10.1016/j.comppsych.2013.11.007 · Cited by 44 · see citing works
“The Cox regression model allows for unequal follow-up time of participants and includes information from individuals whose suicide attempt status is unknown [64,65].”
Biron, V. L., Lentsch, E. J., Gerry, D. R., & Bewley, A. F. (2014) · Head & Neck · doi:10.1002/hed.23686 · Cited by 43 · see citing works
Batson, S., Greenall, G., & Hudson, P. (2016) · PLoS ONE · doi:10.1371/journal.pone.0154870 · Cited by 43 · see citing works
“The results of the current review suggest that it is likely that Cox regression models are routinely chosen by trialists due to its widespread application, and to aid comparability with results of other trials [37].”
ResultRoessiger, J., Griess, V. C., Härtl, F., Clasen, C., & Knoke, T. (2013) · Ecological Modelling · doi:10.1016/j.ecolmodel.2013.01.019 · Cited by 42 · see citing works
Radiochemotherapy in Patients With Primary Glioblastoma Comparing Two Temozolomide Dose Regimens
Combs, S. E., Wagner, J., Bischof, M., Welzel, T., Edler, L., Rausch, R., Wagner, F., Bois, A. Z.-D., Debus, J., & Schulz-Ertner, D. (2008) · International Journal of Radiation Oncology*Biology*Physics · doi:10.1016/j.ijrobp.2007.11.064 · Cited by 42 · see citing works
“using the univariate and multivariate Cox proportional regression model (12, 13).”
MethodKim, I.-H., Castillo, J. C., Aryan, A., Martín-Martín, I., Nouzová, M., Noriega, F. G., Barletta, A. B. F., Calvo, E., Adelman, Z. N., Ribeiro, J. M. C., et al. (2020) · PLoS Pathogens · doi:10.1371/journal.ppat.1008288 · Cited by 40 · see citing works
“The data were analyzed using the log-rank test as well as a fit to an accelerated time failure model with a Weibull distribution [15].”
MethodLalos, A., Tülek, A., Tosti, N., Mechera, R., Wilhelm, A., Soysal, S. D., Däster, S., Kancherla, V., Weixler, B., Spagnoli, G. C., et al. (2021) · Scientific Reports · doi:10.1038/s41598-020-80382-2 · Cited by 40 · see citing works
Osborne, J. L., Hindt, L. A., Lutz, N. M., Hodgkinson, N., & Leon, S. C. (2021) · Children and Youth Services Review · doi:10.1016/j.childyouth.2021.106000 · Cited by 39 · see citing works
- Authors
- Bradburn, M. J., Clark, T. G., Love, S. B., & Altman, D. G.
- Affiliations
- Cancer Research UK (GB)
- Corresponding author
- Bradburn, M J
- Venue
- British Journal of Cancer
- Published
- 2003-07-29
- Volume
- 89
- Issue
- 3
- Pages
- 431-436
- ISSN
- 0007-0920 (ISSN-L)
- 1532-1827
- PMC
- PMC2394368
- OpenAlex
- W2107482271
- Cited by
- 741
- References
- 16
- Citations by year
- 2026: 31 · 2025: 55 · 2024: 86 · 2023: 67 · 2022: 54 · 2021: 91 · 2020: 55 · 2019: 41 · 2018: 43 · 2017: 35 · 2016: 26 · 2015: 21 · 2014: 27 · 2013: 15 · 2012: 24
- FWCI
- 7.17
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc-sa
- www.springer.com/tdm (unspecified)
- Locations
- British Journal of Cancer (publishedVersion, cc-by-nc-sa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
- LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
- Funders
- Cancer Research UK
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Distribution Estimation and Applications
- Keywords
- survival analysis, multivariate survival data, censored data, time to event, cancer survival, censoring
- MeSH terms
- Clinical Trials as Topic, Humans, Neoplasms, Models, Statistical, Multivariate Analysis, Survival Analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review