Validation of the Response Speed Rule to Predict the Efficacy of a Therapeutic Regimen in Myeloma
Authors: De La Puerta Rueda Jose Enrique , Gómez Pérez Clara , Velado Rodriguez Concepción , Carrascosa Vallejo Tomas , Sancho Garaizabal Begoña , Ereño Ealo Maria José , Pastor Ausin Elixabete , Uriarte Isabel , Vicente Olabarria Iñigo , Cabrera Zubizarreta Alberto , Ontañón Garcés José María , Saralegui Prieto Ibone , Olivares Salaverri Matxalen , Barredo Santamaría Inmaculada , Sáiz López Alberto , Arana Berganza Paula , Maruri Machado Natalia , Pérez Garay Raquel , Urrechaga Igartua Eloisa , Etxeguren Urkixo Ianire , Letamendi Madariaga Garazi , Martínez Bilbao Cristina , Amarika Ibarrondo Itxaso , Casado Diez Amaia , González Vallejo Inés , Cortes Fernández Cristina , Gainza González Eukene , Ojanguren Bergaz Jesus , Ibarrondo Chamorro Paloma , Aranbarri Chamorro Ane , Goikolea Ugarte Javier , Bustos Martínez Miriam , Sierra Zabala Amaia , Aguirre Larracoechea Urko , Alonso Varela Marta 
Published: November 2020

BACKGROUND

Current treatment choices are based on generalized outcome data from clinical trials, but not all MM patients respond the same and a considerable percentage of them do not achieve a desirable treatment endpoint. Contradictory results based on the rate of descent of the monoclonal component (M-component) to predict long-term outcome have been published, but no to identify patients with insufficient response to a therapeutic regimen. The ability to identify treatment early on resistance could accelerate the introduction of another (and more effective) line of therapy.

AIM

Develop and validate a rule based on the rate of descent of the M-component, to predict the probability of disease resistance to reach a complete remission (CR) in MM patients.

METHODS

Three studies were conducted: exploratory, confirmatory, and clinical validation. A total of 87 patients treated between July 2014 and September 2018, were included for the first two. Patients who were unable to complete the planned treatment due to toxicity or comorbidities, and those treated for palliative purposes only, were excluded. A therapeutic regimen was considered to be effective if CR was achieved with it. Conversely, a therapeutic regimen was considered to be ineffective if disease progression was observed during treatment, or if CR was not achieved with it. The percentage of the daily decrease in the M-component achieved by each treatment cycle is calculated dividing the percentage of the decrease during the cycle by the number of days elapsed (n.nn% /day). Timing between measurement of the M-component do not differed more than 15% from the scheduled cycle time. In the exploratory study using the receiver operating characteristic (ROC) curve through SPSS v24, the ability to discriminate between effective and ineffective therapeutic regimen was investigated in 99 cycles, to identify the optimal cutoff, and to desing a rule; followed by a confirmatory study of the rule in 52 cycles different from those of the first study. A third clinical validation study was carried out with 62 patients, 31 with treatment guided by response speed rule (RSR-guided) and 31 not (unguided).

RESULTS

In the exploratory study it was observed that the area under the ROC curve was 0.971 (CI 95%: 0.93 - 1.00) (p&lt;0.001) to predict ineffective therapeutic regimen. The optimal threshold was 1.405% /day. The test was considered positive for therapeutic ineffectiveness if ≤1,40% /day. Sensitivity 95.0% (CI 95%: 88.0 - 99.0), specificity 94.7% (CI 95%: 74.0 - 99.8). It was estimated that the false positive results arose due to the occasional lack of adherence of the patient to oral treatment. Also, we have observed that the first therapeutic cycle usually produces a greater decrease in the M component than the successive cycles, and this was the reason for false negative results. Thus, the Response Speed Rule (RSR) was defined as a descent of ≤ 1.40% /day in two successive cycles, and &gt; 1.40% /day in a first cycle it does not indicate efficacy. In the confirmatory study it was observed for the RSR a sensitivity 100% (CI 95%: 92 - 100), specificity 100% (CI 95%: 66 - 100), reliability 100% (CI 95%: 93 - 100). In the clinical validation study the most common treatments in 1st, 2nd, and 3rd line were VBCMP/VBAD, VCD, and KRd for candidates, and VCD, Rd, DRd or KRd in non-candidates respectively. No significant differences were observed in the type of treatment used between RSR-guided and unguided patients. The median (months) to reach the CR in the RSR-guided patients was lower (8.5 vs 12.1 months; p = 0.003). RS-guided patients need fewer cycles to achieve CR (5.29 vs. 10.84; p = 0.002). The CR rate at 18 months was 94.3% (CI 95%: 84.1 - 100) and 74.2% (CI 95%: 58.4 - 90.0) for RSR-guided and unguided patients respectively, although in unguided patients the rate rose to 96.8% (CI 95%: 90.4 - 100.0) continuing treatment until 30 months. No significant differences were found in the number of lines for CR (1.96 vs 2.42; p = 0.054).

CONCLUSIONS

The Response Speed Rule (RSR), defined as a speed of M-component descent of ≤ 1.40% /day in two successive cycles, predicted with great accuracy the current ineffectiveness of a therapeutic regimen to deliver CR. During the clinical validation of this cutoff, it was shown that CR is achieved in less time and with fewer cycles using RSR. This is a simple metric that can be used broadly and accelerate the introduction of another (and more effective) line of therapy.

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Disclosures

No relevant conflicts of interest to declare.