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Cancers 2014, 6(4), 2343-2355; doi:10.3390/cancers6042343

Multimodal Hazard Rate for Relapse in Breast Cancer: Quality of Data and Calibration of Computer Simulation

1
Molecular and Integrative Physical Science, Harvard School of Public Health, Boston, MA 02115, USA
2
Royal Free and UCL Medical School, Centre for Clinical Science and Technology, University College London, Clerkenwell Building, Archway Campus, Highgate Hill, London N19 5LW, UK
3
Scientific Directorate, Fondazione IRCCS Istituto Nazionale Tumori, Via Venezian 1, 20133 Milan, Italy
*
Author to whom correspondence should be addressed.
Received: 11 July 2014 / Revised: 18 November 2014 / Accepted: 21 November 2014 / Published: 27 November 2014
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Abstract

Much has occurred since our 2010 report in Cancers. In the past few years we published several extensive reviews of our research so a brief review is all that will be provided here. We proposed in the earlier reports that most relapses in breast cancer occur within 5 years of surgery and seem to be associated with some unspecified manner of surgery-induced metastatic initiation. These events can be identified in relapse data and are correlated with clinical data. In the last few years an unexpected mechanism has become apparent. Retrospective analysis of relapse events by a Brussels anesthesiology group reported that a perioperative NSAID analgesic seems to reduce early relapses five-fold. We then proposed that primary surgery produces a transient period of systemic inflammation. This has now been identified by inflammatory markers in serum post mastectomy. That could explain the early relapses. It is possible that an inexpensive and non-toxic NSAID can reduce breast cancer relapses significantly. We want to take this opportunity to discuss database quality issues and our relapse hazard data in some detail. We also present a demonstration that the computer simulation can be calibrated with Adjuvant-on-line, an often used clinical tool for prognosis in breast cancer. View Full-Text
Keywords: breast cancer; bimodal and multimodal relapse patterns; database quality; early relapses; surgery; perioperative NSAID; transient systemic inflammation breast cancer; bimodal and multimodal relapse patterns; database quality; early relapses; surgery; perioperative NSAID; transient systemic inflammation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Retsky, M.; Demicheli, R. Multimodal Hazard Rate for Relapse in Breast Cancer: Quality of Data and Calibration of Computer Simulation. Cancers 2014, 6, 2343-2355.

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