Data-Powered Decision-Making in Personalized Medicine: High Return On Investment of Proactively Managing the Quality of Companion Diagnostic Testing - Diaceutics

Data-Powered Decision-Making in Personalized Medicine: High Return On Investment of Proactively Managing the Quality of Companion Diagnostic Testing

August 5th, 2013

Maria Fe Paz

An overview of the Labceutics External Quality Assurance (EQA) modelled study [2013] looking at the impact of inter-laboratory variability of BCR-ABL1 testing. An abstract was submitted to ESH iCMLf International Conference on CML, Biology and Therapy.

BCR-ABL1 testing serves a key clinical need in helping patients manage their blood cancer therapies or achieve a major molecular response (MMR) with Glivec, Tasigna and Sprycel. This is currently an estimated $6 billion treatment market.

The achievement of an MMR (at 12 or 18 months post imatinib initiation) predicts superior long-term clinical outcomes, namely, progression-free survival (PFS) and event-free survival. Similarly, the failure to achieve an MMR after 18 months of imatinib therapy has become a consensus criterion for defining a ‘suboptimal’ response and for the consideration of a possible change in therapy.[i]

However, inter-laboratory variation in BCR-ABL1 to control gene ratios is widely recognized and attempts at converting local laboratory results to an International Scale (IS) via laboratory-specific conversion factors (CFs), has been demonstrated to work well in only 50 per cent of laboratories. Like many complex molecular tests multiple reasons can exist for BCR-ABL1 variability between laboratories. These include:

·       Lack of clear standardization for techniques and processes used for testing in different labs

·       Different RNA extraction and cDNA preparation steps

·       Different control genes

·       Data reporting terminology differences

·       Variable concordance with MMR International Scale in terms of the statistical approach taken to CFs

·       Some labs use their own ‘Conversion Factor’ to convert their results to the International Scale; not all labs have their own conversion factor

·       Incidence of CML is relatively low, therefore many oncologists and labs encounter relatively low number of cases – most will use same lab consistently

·       Testing the same sample in more than one lab is unusual

·       Difficulties in tracking imprecision as it can occur depending on the RQ-PCR technique in use, the patients selected for analysis and the control gene that is employed to normalise results of the assay.

[ii]Inter-laboratory variability has become a common feature of companion diagnostic marketplaces. For example, the problems this created in developing an efficient HER2 testing market for Herceptin are equally well-documented for those who want to dig into the topic in more detail.

So we asked ourselves, could we use the insights we gained from this study and our subsequent direct qualitative analysis with the laboratories themselves, to assess the dollar value of proactively managing the quality of laboratory testing, using BCR-ABL1 as a surrogate example? In discussions with our experts in the study, it was determined that, provided the same laboratory was monitoring the BCR-ABL1 levels for the same patient over time then, despite its non-correlation to an IS standard, the patient would be unlikely to be receiving suboptimal therapy management.

So we asked how many patients are NOT tested consistently in the same lab? Let’s call these ‘CML roamers’.  The answer was no one could say since this has not been measured. There are an estimated 5,920 new cases of CML in the US annually [iii]. Some of our study participants thought CML roamers was a small number, less than 3 per cent (or 177 CML roamers using our US numbers) and others that it was a larger number >10 per cent (or 592 CML roamers using our US numbers) given the chronic nature of the disease and our modern globetrotting lifestyles. With the lack of certainty around the scale of this problem here, we have used two numbers in our financial analysis, namely a 1 per cent problem and a 10 per cent problem. Table 1 below sets out our estimates of impact.

Table 1: Estimated Dollar Impact of Addressing Inter-Laboratory Variability on BCR-ABL1

Dosing would increase by 20% to achieve MMR Dosing would increase by 40% to achieve MMR Dosing would increase by 60% to achieve MMR
Assuming only 1% of the $6bn treatment market is suboptimally dosed $12m $24m $36m
Assuming only 10% of the $6bn treatment market is suboptimally dosed $120m $240m $360m

So there you have it, the potential financial values to companies in the TKI space of proactively reducing inter-laboratory variability in a chronic cancer. Given that the modest costs of proactively managing inter-laboratory consistency (an EQA study ranges from $400K to $750K depending upon the region and number of laboratories included), the return on investment for avoiding this issue from the outset is significant.

[i] Hughes, T. et al, Monitoring CML patients responding to treatment with tyrosine kinase inhibitors: review and recommendations for harmonizing current methodology for detecting BCR-ABL transcripts and kinase domain mutations and for expressing results, Bloodjournal 108: 28-37, 2006, Jabbour, E. J. & Quintas-Cardama, A., Molecular monitoring 101, Leukemia & Lymphoma, 2012; 53(8):1452-1460 , Branford et al, BLOOD VOL 112/8, 2008  Oncologist. 2010 July; 15(7): 744–749.

[ii] Soverini, S., et al, BCR-ABL1 kinase domain mutation analysis in chronic myeloid leukemia patients treated with tyrosine kinase inhibitors: recommendations from an expert panel on behalf of European LeukemiaNet, Blood, 2011; VOL 118/5

[iii] American Cancer Society: Cancer Facts and Figures 2013. Atlanta, Ga: American Cancer Society, 2013.  Last accessed May 2, 2013.


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