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. 2024 Jul 17;10(1):58.
doi: 10.1038/s41523-024-00657-z.

Clinical impact of drug-drug interactions on abemaciclib in the real-world experience of AB-ITALY study

Simone Scagnoli  1 , Simona Pisegna  2 , Angela Toss  3   4 , Roberta Caputo  5 , Michelino De Laurentiis  5 , Michela Palleschi  6 , Ugo de Giorgi  6 , Enrico Cortesi  1 , Agnese Fabbri  7 , Alessandra Fabi  8   9 , Ida Paris  10 , Armando Orlandi  11 , Giuseppe Curigliano  12   13 , Carmen Criscitiello  12   13 , Ornella Garrone  14 , Gianluca Tomasello  14 , Giuliana D'Auria  15 , Patrizia Vici  16 , Enrico Ricevuto  17 , Federica Domati  4 , Claudia Piombino  3 , Sara Parola  5 , Roberta Scafetta  18 , Alessio Cirillo  1   19 , Beatrice Taurelli Salimbeni  12 , Francesca Sofia Di Lisa  16 , Lidia Strigari  20 , Robert Preissner  21 , Maurizio Simmaco  22   23 , Daniele Santini  24   25 , Paolo Marchetti  26 , Andrea Botticelli  1
Affiliations

Clinical impact of drug-drug interactions on abemaciclib in the real-world experience of AB-ITALY study

Simone Scagnoli et al. NPJ Breast Cancer. .

Erratum in

  • Author Correction: Clinical impact of drug-drug interactions on abemaciclib in the real-world experience of AB-ITALY study.
    Scagnoli S, Pisegna S, Toss A, Caputo R, De Laurentiis M, Palleschi M, de Giorgi U, Cortesi E, Fabbri A, Fabi A, Paris I, Orlandi A, Curigliano G, Criscitiello C, Garrone O, Tomasello G, D'Auria G, Vici P, Ricevuto E, Domati F, Piombino C, Parola S, Scafetta R, Cirillo A, Taurelli Salimbeni B, Di Lisa FS, Strigari L, Preissner R, Simmaco M, Santini D, Marchetti P, Botticelli A. Scagnoli S, et al. NPJ Breast Cancer. 2024 Aug 2;10(1):68. doi: 10.1038/s41523-024-00682-y. NPJ Breast Cancer. 2024. PMID: 39095493 Free PMC article. No abstract available.

Abstract

Abemaciclib demonstrated clinical benefit in women affected by HR+/HER2- advanced breast cancer (aBC). Drug-drug interactions (DDIs) can lead to reduced treatment efficacy or increased toxicity. This retro-prospective study aimed to evaluate outcomes, DDIs' impact, and toxicities of abemaciclib combined with endocrine therapy in a real-world setting. Patients from 12 referral Italian hospitals with HR+/HER2- aBC who received abemaciclib were included. Clinical data about comorbidities, concurrent medications, outcomes, and adverse events (AE) were collected. Drug-PIN® (Personalized Interactions Network) is a tool recognizing the role of multiple interactions between active and/or pro-drug forms combined with biochemical and demographic patient data. The software was used to define the Drug-PIN score and Drug-PIN tier (green, yellow, dark yellow, and red) for each patient. Univariate and multivariate analyses were performed to identify predictors of patients' PFS or toxicity. One hundred seventy-three patients were included. 13% of patients had >75years. The overall response rate (ORR) was 63%. The general population's median PFS (mPFS) was 22 months (mo), while mOS were not reached. Patients treated with abemaciclib in combination with AI and fulvestrant had a mPFS of 36 and 19 mo, respectively. The most common toxicities were diarrhea, asthenia, and neutropenia detected in 63%,49%, and 49% of patients. The number of concomitant medications and comorbidities were not associated with survival outcomes (22 vs 17 mo, p = 0.068, p = 0.99). Drug-PIN tier from dark yellow to red and Drug-PIN score >12 were associated with shorter PFS compared to no/low-risk DDIs and score <12 (15 vs 23, p = 0.005, p = 0.0017). Drug interaction was confirmed as an independent biomarker in a multivariate model (p = 0.02). No difference in any grade AE, severe toxicities, and diarrhea were detected among different age subgroups. No association was found between Drug-PIN score or Drug-PIN tier and overall toxicity (p = 0.44), severe AEs (p = 0.11), or drug reduction (p = 0.27). The efficacy and safety of abemaciclib plus ET were confirmed in a real-world setting, even in the elderly population and patients with comorbidities. Evaluation of DDIs with Drug-PIN appears to be an independent predictor of PFS.

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Conflict of interest statement

Simone Scagnoli (SS) speaker: novartis, pfizer, roche, lilly, BMS, MSD; Simona Pisegna (SP) speaker for Novartis, Lilly, Pfizer, Roche; Angela Toss (AT) speaker and advisory board Lilly, Novartis, Pfizer, AstraZeneca, MSD; Roberta Caputo (RC) advisory role Roche, Lilly, Novartis, MSD, Gilead, Daiichi Sankyo, Pierre-Fabre; Michelino De Laurentis (MdL) consultation for astrazeneca, amgen, celgene, daiichi sankyo, EIsai, Eli lilly, Exact science, Gilead, MSD, novartis, pfizer, pierre fabre, roche, seagen; Michela Palleschi (MP) advisory for Novartis and Lilly; Ugo de Giorgi (UdG) advisory Merck, BMS, Janssen, astellas, sanofi, bayer, pfizer, ipsen, novartis, ; grants: astrazeneca, sanofi, roche; Enrico Cortesi (EC) honoraria from MSD and astellas, advisory role for astellas, bayer; research found from merck; Agnese Fabbri (AF) advisory and speaker for lilly, pfizer, roche, novartis, gilead; Alessandra Fabi (AF) advisory board roche, pfizer, novartis, gilead, sophos, Seagen, Astrazeneca, lilly, pierre Fabre, exact science; Ida Paris (IP) fee for Novartis, Gentili, Italfarmaco, Genetic, advisory role for Gilead, AstraZeneca, Lilly, Pfizer, Seagen; Armando Orlandi (AO) fee speaker and advisory: amgen, lilly, pfizer, novartis, daiichi sankyo, gilead; Giuseppe Curigliano (GC) has/had a consultant/advisory role for Roche-Genentech, MSD, Pfizer, BMS, Amgen, Novartis, Pierre Fabre, Gilead, Eli-Lilly, Seagen, Exact Science; Carmen Criscitiello (CC) had consultancy/advisory role/speaker bureau Pfizer Roche msd Novartis Lilly seagen gilead Daiichi-Sankyo; Giuliana D’Auria (GdA) advisory role for amgen, pfizer, lilly, novartis, eisai; Patrizia Vici (PV) advisory role for Pfizer, lilly, eisai, Novartis; Alessio Cirillo (AC) speaker for Novartis, MSD; Daniele Santini (DS) advisory role for Angen, Janssen, Astellas, Bayer, Servier, Novartis, MSD. Merck, Pfizer, Ipsen; Paolo Marchetti (PM) has/had a consultant/advisory role for BMS, Roche, Genentech, MSD, Novartis, Amgen, Merck Serono, Pierre-Fabre, and Incyte. Andrea Botticelli (AB) has/had a consultant/advisory role for Roche-Genentech, MSD, Pfizer, BMS, Amgen, Novartis, Pierre Fabre, Gilead, Eli-Lilly, and Seagen. Competing interests: Maurizio Simmaco (MS), Paolo Marchetti, and Robert Preissner (RP) are members of the Advisory Board of Drug-PIN AG (software expressly cited in the text). The Drug-PIN AG is the holder of the patent PCT/IB2019/052310. The remaining authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Concomitant medications in the study population.
Number of concomitant medications divided into five groups of patients. On the x-axis is reported the number of concomitant medications. On the y-axis is reported the number of patients. The cumulative number of patients per group is represented by the height of the histogram and reported at the top of the columns.
Fig. 2
Fig. 2. OS and PFS in the study population.
Kaplan–Meier estimates of OS (A) and PFS (B) in the overall population (red lines). mOS was not reached. mPFS was 22 (range) months. The gray area represents the confidence interval. Tick marks represent data censored at the last time the patient was known to be alive.
Fig. 3
Fig. 3. FS according to abemaciclib companion.
Kaplan–Meier estimates of PFS, according to the combination of abemaciclib + Aromatase Inhibitor (yellow line) or abemaciclib + fulvestrant(blue line); 35 months vs 19 months, p < 0.0001). The colored area represents the confidence interval. Tick marks represent data censored at the last time the patient was known to be alive.
Fig. 4
Fig. 4. PFS according to polypharmacy.
Kaplan–Meier estimates of PFS, according to polypharmacotherapy (no polipharmacotherapy, yellow line; yes polypharmacotherapy, blue line any grade; 22 months vs 17 months, p = 0.068). The colored area represents the confidence interval. Tick marks represent data censored at the last time the patient was known to be alive.
Fig. 5
Fig. 5. PFS according to Drug-PIN tier.
Kaplan–Meier estimates of PFS, according to Drug-PIN tier (≦1 low-risk interactions, yellow line; >1, high-risk interactions; 23 vs 15 months, p = 0.005). The colored area represents the confidence interval. Tick marks represent data censored at the last time the patient was known to be alive.
Fig. 6
Fig. 6. PFS according to Drug-PIN Score.
Shown are Kaplan–Meier estimates of PFS, according to Drug-PIN score (<30, yellow line; ≥30, blue line any grade; 23 vs 15 months, p = 0.005). The colored area represents the confidence interval. Tick marks represent data censored at the last time the patient was known to be alive.
Fig. 7
Fig. 7. PFS according to Drug-PIN tier in different settings.
Shown are Kaplan–Meier estimates of PFS, according to Drug Pin tier (≦1 low-risk interaction, yellow line; >1, high-risk interactions) in the two different populations of patients treated with upfront abemaciclib + AI (A; p = 0.02) or abemaciclib + fulvestrant (B; p = 0.0014). PFS was significantly worse in patients with high-risk DDIs compared to patients with low-risk risk DDIs, regardless of the treatment received. The colored area represents the confidence interval. Tick marks represent data censored at the last time the patient was known to be alive.
Fig. 8
Fig. 8. PFS according to treatment toxicity.
Shown are Kaplan–Meier estimates of PFS, according to toxicity group (0 = no toxicity, yellow line; 1 = at least one toxicity of any grade, blue line any grade; 21 vs 22 months, p = 0.44). The colored area represents the confidence interval. Tick marks represent data censored at the last time the patient was known to be alive.
See this image and copyright information in PMC

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