Breast cancer and the black swan

Abstract

Most current research in cancer is attempting to find ways of preventing patients from dying after metastatic relapse. Driven by data and analysis, this project is an approach to solve the problem upstream, i.e., to prevent relapse. This project started with the unexpected observation of bimodal relapse patterns in breast and a number of other cancers. This was not explainable with the current cancer paradigm that has guided cancer therapy and early detection for many years. After much analysis using computer simulation and input from a number of medical specialties, we eventually came to the conclusion that the surgery to remove the primary tumour produced systemic inflammation for a week after surgery. This systemic inflammation apparently caused exits of cancer cells and micrometastases from dormant states and resulted in relapses in the first 3 years post-surgery. It was determined in a retrospective study that the common inexpensive perioperative non-steroidal anti-inflammatory drug (NSAID) ketorolac could curtail the early relapse events after breast cancer surgery. A second retrospective study strongly confirmed this but an apparently underpowered prospective study showed no advantage. We are analysing these data and are now proposing to test the perioperative NSAID at Beth Israel Deaconess Medical Centre with triple-negative breast cancer (TNBC) patients, the category that could respond best to the perioperative NSAID. If this works as well as we expect, we would then transfer this technology to low- and/or middle-incomes countries (LMICs), starting with Nigeria where early onset type of TNBC is common. There is an unmet need in LMICs, especially in countries like Nigeria (190 million population), for a means to prevent surgery induced relapse that we are attempting to resolve. This work aims, thus, to describe eventual mechanisms, and ways to test a solution addressing an unmet need. But first, we consider the context, including within an historical perspective, important to explain how and why a Kuhnian paradigm shift may be considered.

Keywords: bimodal relapse hazard; breast cancer; computer simulation; early relapse; mechanisms; perioperative NSAID ketorolac; proposed solution; surgery induced systemic inflammation; unmet need in Nigeria.

Figure 1.. Relapse hazard for postmenopausal breast cancer patient vs. months since mastectomy.

Figure 2.. Relapse hazard for premenopausal breast cancer patients versus months since mastectomy.

Figure 3.. Disease Free Survival vs Years post-surgery from Bonadonna et al [1]. Data were transcribed from the original paper.

Figure 4.. Description of the collaboration between Retsky, Demicheli and Valagussa.

Figure 5.. Simulation of breast cancer using the Milan data.

Figure 6.. Data from Fisher, Sass and Fisher [8]. This figure has been transcribed from the original. The relapses in the first 3 years and after 6 years can be seen especially for the N = 0 and the N > 12 data. The magnitudes vary but the timing is quite similar from N = 0 to N > 12 data.

Figure 7.. Breast cancer relapses after breast cancer surgery, observed by Forget et al in 2010. Purple is for patients having received ketorolac vs. no ketorolac in blue.

Figure 8.. Forget et al data updated by Sarah Amar and analyzed by Demicheli. Note the five-fold reduction in relapses months 9–18 (3 versus 15 events). This histogram is useful to visually show the large reduction in early relapses.

Figure 9.. Number of times ketorolac is mentioned in PubMed since 1980. It was apparently brought into significant use starting in 1990.

Figure 10.. Proposed mechanism along with the conventional mechanisms.

Figure 11.. TNBC recurrence data from Milan as seen in Figure 11 is quite similar to the no-ketorolac arm of Forget et al data (Figure 7). This strongly suggested to us that perioperative ketorolac will be effective in sub-Saharan Africa where TNBC is common (See chapter 6.) The low cost will be another enhancing factor. Low and Middle Income Countries have 70% of the world’s cancer burden but 5% of the financial resources [75].

Figure 12.. Data from Milan show that the benefit of adjuvant chemotherapy is mainly to reduce the early relapses. This is consistent with the analysis based on the computer simulation.