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TKI dose reduction in CML
LSCs population when compared to standard dose (Online Supplementary Figure S4). Our model also predicts that returning to the full dose regimen at a later point completely restores the original response levels of proliferating LSCs within a few months (Online Supplementary Figure S5).
Patient-specific optimal dose can be estimated after an initial dose reduction
The calculation of patient-specific optimal TKI doses requires the knowledge of model parameters 𝑝𝑌𝑋, 𝑝𝑋𝑌, 𝑒𝑇𝐾𝐼, and 𝑝𝑌. Whereas 𝑝𝑌𝑋, 𝑝𝑋𝑌, and 𝑞=𝑒𝑇𝐾𝐼−𝑝𝑌 can be estimated from time course data, the LSC proliferation rate 𝑝𝑌 is con- founded with the individual TKI-effect 𝑒𝑇𝐾𝐼 and cannot be deduced directly. Therefore, we propose to estimate 𝑝𝑌 by observing the transient increase in proliferating LSCs occurring after a first favorable dose reduction. Technically, we suggest a moderate initial reduction to fraction 𝑓 of the standard dose, after the patient’s response under standard dose has been sufficiently quantified in terms of the kinetic parameters (𝛼,𝛽,𝐴,𝐵) (Figure 3A). Although dose-halving (i.e. 𝑓=0.5) seems to be safe for this first de-escalation (see below), the proposed approach is valid for any reasonable reduction. After a transient increase in the BCR-ABL1 levels, a new intercept 𝐵′ can be observed approximately 18 months after the dose reduc- tion (Figure 3B). Based on the difference of intercepts 𝐵 and 𝐵′, and the reduction fraction 𝑓, the proliferation rate 𝑝𝑌 can be estimated (Online Supplementary Text S9) by
and the individual optimal dose reduction fraction 𝑓𝑂𝑃𝑇 can be calculated using equation (E5). This dose is predict- ed to retain the original long-term treatment efficiency (Figure 3C and D).
A population-based estimate predicts that the majority of patients in sustained remission retain the long-term treatment efficiency after dose-halving
As pointed out above, the LSC proliferation rate 𝑝𝑌, as an indicator of the ‘aggressiveness’ of the untreated dis- ease, is intrinsically unknown. In order to circumvent this limitation, we also used a population-based estimate derived from CML latency times, i.e. the time between the first leukemic transformation and diagnosis, given that no secondary events change the kinetics of disease emer- gence (Online Supplementary Figure S6A). Sampling from a distribution of CML latency times as reported by Radivoyevitch et al.27 [median latency time = 6.9 years, IQR (5.0,10.1)] (Online Supplementary Figure S6B) and tak- ing into account the observed TKI response, we obtained an individual distribution of possible proliferation rates 𝑝𝑌 for each patient (Online Supplementary Figure S6C). In other words, we fit our mathematical model several times under different, plausible assumptions about the aggressiveness of the underlying leukemia. For each of those hypothetical but realistic scenarios we calculate the reduction level 𝑓𝑂𝑃𝑇 (Online Supplementary Figure S6D).
Based on these different possible scenarios (i.e. different leukemia growth parameters), we calculated for each patient the fraction of its individual values of 𝑓𝑂𝑃𝑇 which are below 0.5 (Online Supplementary Figure S6F). This frac- tion indicates whether dose-halving appears as a suitable treatment option or not. With these estimates, our model
predicts that 90% of the patients in the German IRIS cohort and 81% of the patients in the CML-IV trial who once achieved MR3, could have safely decreased their TKI dose by at least 50%, while maintaining the overall thera- py effect on quiescent LSCs (Online Supplementary Figure S7A). Therefore, dose-halving is expected to be safe for the majority of patients in sustained remission and might serve as the initial step to estimate the optimal individual dose.
Our results also suggest that the ratio 𝛼/𝛽 can be used to identify patients who are likely to benefit from dose reduction. We predict that patients with 𝛼/𝛽>15 are very likely to retain the original long-term treatment efficiency after a 50% dose reduction (Online Supplementary Figure S7B and C). Furthermore, we derived a condition to iden- tify patients who do not obtain sufficient TKI dose initial- ly. Specifically, we found that patients with slopes 𝛼/𝛽<2 would benefit from dose escalation, while only patients with 𝛼/𝛽≫2 benefit from dose de-escalation (Online Supplementary Figure S8).
The model predictions are similar to results from the DESTINY trial and support the design of new, informative trials
We compared our model results with findings from the DESTINY trial, which studies dose-halving in 174 TKI- treated patients with CML (being either in MR4 or MR3 for at least 12 months) before TKI cessation. The pub- lished DESTINY interim-analysis indicates that 93% of the patients showed no loss of MR3 within 12 months post dose reduction.15 We simulated this scenario by pre- dicting virtual treatment responses from BCR-ABL1 meas- urements in the IRIS/CML-IV trials. In particular, we identified 122 patient time courses fulfilling the inclusion criteria of the DESTINY protocol (> 3 years under TKI, > 1 year in MR3) and simulated a virtual TKI dose reduction according to the DESTINY protocol at the end of the available follow up for each of those patients. Using the same distribution of latency times as above, we calculat- ed for each patient the fraction of values of 𝑝𝑌, which lead to loss of MR3 within one year after de-escalation (Online Supplementary Figure S6E). This fraction can be interpreted as an estimate for the patient-specific risk of a molecular relapse. We also calculated the expected proportion of relapsed patients within the overall population, as well as in the corresponding subcohorts of patients being in either MR3 or MR4 within the last year before dose reduction (Figure 4A). Although a quantitative compari- son should be considered with caution due to potential differences in the study populations and patient compli- ance, the results predicted for the IRIS/CML-IV patients show qualitatively similar relapse rates as observed in the DESTINY trial. Our findings also suggest that the individ- ual relapse probability is related to the remission level before de-escalation, with patients below MR3.5 having a very low probability of relapse (Figure 4B). Furthermore, we predict that most of the observed relapses are tran- sient, i.e. MR3 regain is expected when continuing the half-dose regimen (Figure 4C). Therefore, we argue that the current focus on exceeding MR3 as an indicator for a potential relapse might be reconsidered in the context of dose de-escalation strategies, while closer monitoring of the disease dynamics following dose reductions should be applied to distinguish transient from permanent BCR- ABL1 regrowth dynamics.
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