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Retsky M, Demicheli R. Multimodal hazard rate for relapse in breast cancer: quality of data and calibration of computer simulation. Cancers (Basel). 2014;6(4):2343-55doi: 10.3390/cancers6042343.
Retsky, M., & Demicheli, R. (2014). Multimodal hazard rate for relapse in breast cancer: quality of data and calibration of computer simulation. Cancers, 6(4), 2343-55. https://doi.org/10.3390/cancers6042343
Retsky, Michael, and Demicheli, Romano. "Multimodal hazard rate for relapse in breast cancer: quality of data and calibration of computer simulation." Cancers vol. 6,4 (2014): 2343-55. doi: https://doi.org/10.3390/cancers6042343
Retsky M, Demicheli R. Multimodal hazard rate for relapse in breast cancer: quality of data and calibration of computer simulation. Cancers (Basel). 2014 Nov 27;6(4):2343-55. doi: 10.3390/cancers6042343. PMID: 25437254; PMCID: PMC4276970.
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Cancers (Basel). 2014 Nov 27;6(4):2343-55. doi: 10.3390/cancers6042343.

Multimodal hazard rate for relapse in breast cancer: quality of data and calibration of computer simulation.

Cancers

Michael Retsky, Romano Demicheli

Affiliations

  1. Molecular and Integrative Physical Science, Harvard School of Public Health, Boston, MA 02115, USA. [email protected].
  2. Scientific Directorate, Fondazione IRCCS Istituto Nazionale Tumori, Via Venezian 1, 20133 Milan, Italy. [email protected].

PMID: 25437254 PMCID: PMC4276970 DOI: 10.3390/cancers6042343

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.

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