Real-world experience and clinical impact of drug-drug interactions in HR+/HER2- advanced breast cancer patients treated with abemaciclib plus endocrine therapy: the AB-ITALY study

doi:10.21203/rs.3.rs-3047347/v1

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Real-world experience and clinical impact of drug-drug interactions in HR+/HER2- advanced breast cancer patients treated with abemaciclib plus endocrine therapy: the AB-ITALY study

https://doi.org/10.21203/rs.3.rs-3047347/v1

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published 17 Jul, 2024

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BACKGROUND

Abemaciclib demonstrated clinical benefit in women affected by HR+/HER2- advanced breast cancer (aBC). Drug-drug interactions (DDIs) can lead to a 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.

METHODS

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 analysis were performed to identify predictors of patients PFS or toxicity.

RESULTS

One hundred seventy-three patients were included. 13% of patients had > 75years. Overall response rate (ORR) was 63%. The median PFS (mPFS) of the overall population was 22 months (mo), while mOS was 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 diarrhoea, asthenia and neutropenia detected in 63%,49%,49% of patients, respectively. 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 diarrhoea was 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)

CONCLUSIONS

Efficacy and safety of abemaciclib plus ET were confirmed in a real-world setting, even in elderly population and patients with comorbidities. Evaluation of DDIs with Drug-PIN appear to be an independent predictor of PFS.

Health sciences/Oncology/Cancer/Breast cancer

Health sciences/Oncology/Cancer/Tumour biomarkers

Health sciences/Oncology/Cancer/Cancer therapy/Targeted therapies

Health sciences/Health care/Drug regulation

The discovery of cyclin-dependent kinases 4/6 (CDK4/6) inhibitors significantly reshaped the therapeutic landscape of hormone-receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative advanced breast cancer (aBC).¹ Among them, abemaciclib showed statistically significant and clinically meaningful improvements in progression-free survival (PFS) and overall survival (OS) while maintaining the health-related quality of life (HRQoL), both when given with fulvestrant in endocrine-resistant aBC and when given with a non-steroidal aromatase inhibitor in endocrine-sensitive aBC. Though this meaningful increase in clinical outcomes, final results for overall survival in endocrine-sensitive aBC for are still awaited^2–6. Furthermore, abemaciclib showed improved invasive disease-free survival (iDFS) in patients with HR+/HER2-, high-risk early breast cancer (eBC) when combined with standard-of-care adjuvant endocrine therapy after surgery⁷.

An age-specific subgroup analysis of patients older than 65 years enrolled in MONARCH-2 and MONARCH-3 trials showed higher rates of nausea, decreased appetite and venous thromboembolic events⁸. Since a major share of HR+/HER2- aBC occur in older women with high rates of comorbidities and concomitant medications, post-marketing surveillance studies and real-world studies are pivotal to confirm the safety and the efficacy of abemaciclib in a wider, unselected populations.^9,10

The increasing use of CDK4/6i in HR+/HER2- aBC in clinical practice has rekindled the interest in drug-drug interactions (DDIs), since interactions cause one drug to affect the other drugs and can lead to a reduced treatment efficacy or increased toxicity, with a potential effect on clinical outcomes.^11,12

Pharmacokinetics and pharmacodynamics-based DDIs in cancer patients taking multiple concomitant medications may indeed alter anti-cancer drugs’ therapeutic index, thus causing reduced compliance, unwanted adverse drug reactions (ADRs) and treatment failure.^13,14 Despite this relevant clinical issue, only few retrospective analyses have been conducted to evaluate DDIs in patients receiving anti-cancer treatments and, among these, study populations were wide heterogeneous. Moreover, most patients were treated with intravenous chemotherapy and no data were available for patients with aBC treated with CDK4/6 inhibitors.^15,16

Abemaciclib is primarily metabolized by the liver through various cytochrome P450 (CYP) enzymes. The main enzymes involved in its metabolism are CYP3A4 and, to a lesser extent, CYP2C9. Abemaciclib itself is considered the major active component. The primary metabolites formed during its metabolism, M2 and M20, have shown minimal pharmacological activity in preclinical studies. Therefore, the therapeutic effects are primarily attributed to the drug itself. Abemaciclib and its major active metabolites inhibit renal transporters, such as transporter of organic cation 2 (OCT2), the multidrug and toxin extrusion protein (MATE1) and the MATE2-K. In vivo, interactions may occur with relevant substrates of these carriers such as creatinine and metformine.¹⁷

Patients on abemaciclib may suffer from clinically relevant drug interactions causing altered drug exposure; in particular, patients with multiple comorbidities and elderly ones could be the higher risk population.

Therefore, it is evident that analysis of multiple layers of data from the same patients can be critical in shaping clinical outcomes.

In this multicentre, retrospective study we aimed to investigate the impact of poly-pharmacotherapy and drug interactions in a real-world cohort of patients with either endocrine-resistant or endocrine-sensitive aBC treated with abemaciclib plus standard endocrine therapy (ET).

Clinical and pathological features of patients were collected from referral hospitals to treat aBC in Italy. Patients with histological and radiological confirmation of HR+/HER2- aBC who received abemaciclib in combination with aromatase inhibitor (AI) or fulvestrant (F) as upfront or second-line treatment were included in the study. Endocrine sensitivity or resistance was defined according to ESMO guidelines.¹⁸ Complete clinical data about comorbidities, concurrent medications, clinical outcomes of the treatment and the completion of at least one month of abemaciclib were further inclusion criteria. Patients treated with a different CDK4/6i or affected by another malignancy were excluded. The best response was evaluated following RECIST 1.1 criteria.¹⁹ CTCAE v5 was used to evaluate treatment-related toxicities.²⁰ Overall response rate (ORR) was defined as the proportion of patients who achieved a partial or complete response.

Drug-PIN® was used to assess the pharmacological interaction between drugs. Drug-PIN® (Personalized Interactions Network) is a medical software able to evaluate clinical, biochemical and demographic patients’ data and combine them with a simultaneous DDIs profile, exploring possible effects also between active and/or pro-drug forms.^21–23

Moreover, the software combines and analyses the clinical data (age, weight, liver and renal function), the DDIs, and, if available, the genomic profile of patients. The output of Drug-PIN system is a numerical score (Drug-PIN score) that indicates the risk of DDIs, and a tier (Drug-PIN tier: green, yellow, dark yellow and red), which indicates how high is the risk of interactions and if the concomitant drugs have to be changed, in a drug reconciliation process. The following features were considered for each patient: age, race, smoking habit, alcohol consumption, and concomitant medications. The software performed a multi-pass analysis using machine learning algorithms, integrating data for each element added to the patient’s record. A specific drug-PIN score/tier was obtained for every patient, both without and with abemaciclib addition.

Univariate analysis (UVA) was conducted using the Kaplan and Meier curves of PFS and OS. The differences between the Kaplan Meier curves were assessed using the log-rank test. At the UVA, the optimal cut-off of both drug pin and tier score was determined by varying the cut-off and selecting the value minimizing the p-value of Kaplan Meier curves of PFS. The multivariate Cox proportional hazard regression model (MVA) was implemented to assess the early predictor of patient clinical outcomes, while the logistic multivariate regression analysis was conducted to identify early predictors of toxicity or best response.

The treatment response/toxicity was used as the gold standard for non-parametric clustered ROC analysis to evaluate the predictive utility of the univariate or multivariate model. By comparing observed and calculated toxicity, the sensitivity and the specificity of each investigated variable or model were plotted using the receiver operating characteristic (ROC) curve and determining the 95% Confidence interval (CI). When a perfect correlation of predicted versus observed response was found, the area under the curve (AUC) was equal to 1, whereas random assignment of outcome led to a ROC/AUC of 0.5.^24,25

Data were collected in an anonymous database and analysed with R-package and SPSS v.26

The study was approved by the Institutional Review Board (IRB) of the coordinating centre (Sapienza n° 0799/2020) and by the IRBs of each participating centre. All procedures performed were in accordance with the Helsinki Declaration. Overall, 12 Italian centres adhered to the initiative. It is noteworthy that more participating centres referred to one single IRB. All the patients who were alive at the time of the study approval signed a specifically conceived informed consent form.

One hundred seventy-three (173) patients were retrospectively included. Patients’ characteristics are reported in Table 1. The median age was 60 years (range 37–87). Sixty-eight patients (39%) were 65 years old or older, with 23 (13%) over 75 years old. The majority of patients presented a postmenopausal status (59%). Globally, 106 (61%) patients had at least one comorbidity and 23 (13%) had two or more. The remaining reported no significant comorbidities. 40% of patients were receiving at least 2 concomitant medications and 27 patients (15%) assumed more than 5 medications per day (Fig. 1). Median Drug-PIN score was 3.25 (range 0 -114). Moreover, 149, 7, 14 and 3 patients were in the green, yellow, dark yellow and red tier, respectively. According to this result, about 10% of patients had a high risk drug interaction. Median Drug-PIN score and Drug-PIN tiers remains similar with the addition of abemaciclib to the patients’ concomitant therapy (3.25 vs 4.9, p = 0.44), indicating that DDIs are mostly related to concomitant medications. Abemaciclib was received as the upfront treatment in 144 (80%) patients. Globally, abemaciclib was administered in combination with AI or fulvestrant in 81 (47%) and 92 (53%) patients, respectively. In the context of the first line, 53% of patients were endocrine-sensitive and received abemaciclib in combination with AI, while 47% were endocrine-resistant and treated with abemaciclib plus fulvestrant.

Table 1

Patients’ characteristics
Characteristics	N (%)
Age
median, years (range)	60 (37–87)
> 60 years	85 (49)
≤ 60 years	88 (51)
Menopausal status
premenopausal	69 (40)
postmenopausal	103 (59)
other/men	1 (1)
Comorbidities
any	67 (39)
none	106 (61)
Comorbidities, number
0	67 (39)
1–2	83 (48)
>2	23 (13)
Concomitant medications
median, no. (range)	1 (0–11)
Concomitant medications, number
0	54 (31)
1–2	70 (40)
3–5	31 (18)
6–10	17 (10)
>10	1 (0)
Advanced disese, timing
synchronous	42 (24)
metachronous	131 (76)
Endocrine therapy partner
NSAI	81 (47)
fulvestrant	92 (53)

Among patients with misurable disease (156), the overall response rate (ORR) was 63% and the clinical benefit rate (CBR) was 92%. The best response was complete response (CR) or partial response (PR) in 6 (4%) and 92 (59%) patients respectively; stable disease (SD), and progression disease (PD) was reported in 46 (29%), and 12 (8%) patients, respectively (Table 2). At a median follow up of 30 months (11–46), the median PFS (mPFS) in our population was 22 months (range 1–37) (Fig. 2).

Table 2

Overall response according to RECIST criteria.
Best response	N (%)
complete response (CR)	6 (4)
partial response (PR)	92 (59)
stable disease (SD)	46 (29)
progressive disease (PD)	12 (8)
ORR	98 (63)
CBR	144 (92)

Firstly, we evaluated the impact of the main clinical features on PFS. Patients treated with upfront abemaciclib + AI had a PFS of 36 months compared to 19 months of the combination abemaciclib + fulvestrant, administered in the endocrine-resistant population (Fig. 3; p < 0.0001). Patients with endocrine sensitivity had a longer PFS compared to endocrine resistance (p = 0.003; Suppl Fig. 1). The number of comorbidities did not seem to have an impact on clinical outcomes (Suppl Fig. 2 and Fig. 3; p = 0.998; p = 0.766). We grouped patients by age in < 65y, 65y to 70y, 71y to 74y, and ≥ 75y. An age ≥ 75y was associated with a shorter PFS if compared to the younger group (Suppl Fig. 4, 18 vs 25 months, p = 0.009), while there was no significant difference among the other age-based groups.

Furthermore, we focused on the impact of concomitant medication and the consequent DDIs. Polypharmacy and the number of concomitant drug assumed by the patients did not show a significant impact on PFS (Fig. 4, 22 vs 17 months, p = 0.068). However, the identification of high DDIs was significantly associated with a worse PFS. Patients with a Drug-PIN tier indicating an high risk of interaction had a PFS of 15 months compared to 23 months of those with low risk interactions (Fig. 5, p = 0.005). A similar result was obtained evaluating the Drug-PIN score (Fig. 6, p = 0.017). Moreover, to avoid a possible selection bias, we evaluated the effect of DDIs in both the abemaciclib + AI and abemaciclib + fulvestrant populations. PFS was significantly worse in patients with high risk DDIs compared to patients with low risk DDIs, regardless of treatment received (Fig. 7A and B; p = 0.02 and p = 0.0014). Altogether, using a UVA, the association with AI or Fulvestrant (p < 0.0001), the age (p < 0.009) and the Drug-PIN tier (high risk interactions, from dark yellow to red, p = 0.005) were significant predictive factors of decreased PFS. Finally, using a multivariate cox regression model, a significant association was shown between Drug-PIN tier and PFS, confirming the high DDIs risk as an independent predictive factor of worse PFS (HR 2.529, 95% CI 1.402–4.561; p = 0.002; Suppl Fig. 5).

Overall survival data are still immature and the median Overall Survival (mOS) of the entire population is still not reached (Fig. 1A). However, in patients with high risk DDIs there is a trend in shorter OS if compared to the rest of the population (Suppl Fig. 6).

Treatment-related toxicities are summarized in Table 3. Any grade adverse events (AEs) were registered in 133 (77%) patients. Thirty-one (18%) patients experienced a severe AE (G3/G4). Diarrhoea was the most common toxicity and was reported in 109 patients (63%; any grade). However, severe diarrhoea was experienced only by 4% of patients. The time of onset was the first month/cycle for the majority of patients (median 1 month; range 1–17) and lasted 1 week or less for 48% of patients (median 1 week; range 1–40 weeks). Other common AEs were asthenia (85 pts; 49% any grade) and neutropenia (85 pts; 49% any grade). Anaemia was registered in 62 patients (36%; any grade). The most common G3/G4 toxicities were neutropenia, diarrhea, anemia, and asthenia observed respectively in 18, 8, 5 and 4 patients. Deep vein thrombosis (DVT)/pulmonary embolism was registered in 3 patients (1.7%). A dose reduction was required in 32% of patients and 10% discontinued due to toxicity. AEs were similar in young and elderly patients. In particular, no difference in AEs of any grade, severe AEs and diarrhea was detected among patients with ≥ 65y and ≥ 75y compared to younger ones (Table 4). Menopausal status and comorbidities were not related with the occurrence of AEs. The use of fulvestrant was associated with a higher toxicity rate (AUC ROC of Fulvestrant vs AI for overall AEs 0.602; 95% CI = 0.525 to 0.675; p-value = 0.0373). Drug-PIN score or Drug-PIN tier were not associated with overall toxicity (p = 0.44), severe AEs (p = 0.11) or dose reduction (p = 0.27). Using a UVA, DDIs were associated as a trend with severe diarrhoea, DVT and anaemia of any grade (Suppl table 1). AEs does not seem to have an impact on both PFS (Fig. 8, p = 0.44) and OS (Suppl Fig. 7, p = 0.65).

Table 3

Treatment-related adverse events.
Adverse events	N (%)
Adverse event, any
yes	133 (77)
no	40 (23)
Dose reduction, any
yes	56 (32)
no	117 (68)
Diarrhea
any grade	109 (62)
grade 3/4	8 (4)
Neutropenia
any grade	85 (49)
grade 3/4	18 (10)
Ashtenia
any grade	85 (49)
grade 3/4	4 (2)
Anemia
any grade	62 (36)
grade 3/4	5 (3)
Nausea
any grade	15 (8)
grade 3/4	1 (0)
Hepatotoxicity
any grade	14 (7)
grade 3/4	3 (1)
Renal toxicity
any grade	35 (19)
grade 3/4	1 (0)
DVT/pulmunary embolism
yes	6 (3)
no	167 (97)

Table 4

AEs per age category
Adverse events	age category		p	age category		p
Adverse events	< 65	≥ 65	p	< 75	≥ 75	p
any grade AEs	79%	79%	0.95	79%	82%	0.66
severe AEs	15%	23%	0.17	17%	26%	0.31
diarrhea	67%	61%	0.43	67%	52%	0.15
severe diarrhea	6%	6%	0.96	5%	8%	0.51

In HR+/HER2- aBC, CDK4/6 inhibitors plus ET have become the current standard of care as first or second-line treatment, giving the impressive clinical benefits in both endocrine-sensitive and endocrine-resistant disease.^{3,5, 26–29}

In our study, we retrospectively investigate the efficacy and toxicity profile of abemaciclib in a real-world setting of HR+/HER2- aBC patients. In addition, we also assess DDIs and their potential impact on clinical outcomes.

Abemaciclib appeared to be effective and safe in our unselected population, also in older patients and patients with comorbidities. In our real-world population there is a high rate of ≥ 65 years old patients (40%), with several patients aged > 75 years old (13%). Abemaciclib demonstrated to be safe in this particular population, with a similar number and grade of AEs in the elderly compared to younger patients. No difference was detected in PFS among patients with > 65y. However, patients ≥ 75y had a worse PFS, probably due to the worse general clinical conditions and more comorbidities, as normally observed in clinical practice. Moreover, the sample size is limited, and a specific prospective, real-world study should be conducted in this particular population. In this real-world study, the efficacy of abemaciclib was comparable to clinical trials. We found an ORR of 63%, similarly to what has been reported in registration trials (about 50–60%).^3,5 The high ORR confirms the relevant tumor shrinkage determined by abemaciclib plus ET, which makes the combination useful even in conditions of high tumor burden.

Regarding the survival outcomes, PFS in the overall population was 22 months, while the median OS is still not reached. As expected, PFS was longer in patients treated in the endocrine sensitive setting with abemaciclib plus AI (mPFS 35 months) as compared to patients treated with abemaciclib plus fulvestrant in the endocrine resistant setting (mPFS 19 months). In particular, in both subgroups, the real-world PFS is comparable and consistent with the respective registrative clinical trials (i.e. Monarch 3 (abemaciclib + AI; mPFS 29 months) and Monarch 2 (abemaciclib + fulvestrant; mPFS 17 months).^3,30 This crucial data confirms the efficacy of abemaciclib both in combination with AI and fulvestrant in unselected, real-world population.

The median follow-up of our study was 30 months. This observation period is long enough to evaluate PFS but is relatively short for OS. In fact, the expected mOS in patients with HR+/HER2- aBC who receive CDK4/6i as first line may range from 50 to 65 months.³¹ As expected, the mOS of our population is not reached (Fig. 1). Anyway, we consider the known limitations of a real life study especially on the assessment of disease outcomes such as non-uniformity among different centres in detecting the exact time of progression, different timing of radiological re-evaluation, non-centralisation of radiological imaging assessments and possible delays in defining progressions or knowing the exact death of the patient.

Reported AEs were also consistent with known literature, without any signal of a different safety profile.⁸ Toxicities of any grade were reported in 77% of patients, with an 18% of severe AEs. No treatment-related death was reported. As expected, diarrhoea was the most frequent AE (63%). The rate of severe diarrhoea was very low (4%) and the duration of diarrhoea was short (1 week), confirming the manageability of this AE even in the real-world population. DVT was a rare adverse event (< 2%) and no interstitial lung disease (ILD) was reported. Elderly patients had a similar toxicity profile of younger patients and no differences in discontinuation rate were detected. Our study adds important information on the safety of abemaciclib in this particular population, which is underrepresented in clinical trials.

Polypharmacy was confirmed as a relevant clinical issue, with 119/173 (69%), 49/173 (28%) and 18/173 (10%) patients taking > 1, >3 and > 5 drugs every day, respectively.

Hepatic metabolism primarily by cytochrome P450 (CYP) 3A4 is the main route of clearance for abemaciclib; therefore, abemaciclib’s pharmacokinetics are significantly impacted by CYP3A4 inhibitors and inducers.^32–34 Moreover, when patients take many concomitant drugs, the DDI can be complex and involve both pharmacokinetic and pharmacodynamic mechanisms.^{23, 35–37} This complex system of interactions can be barely predicted and modulated by a single specialist as the oncologist in the absence of dedicated tools. Drug-PIN is a software that combines clinical data (age, weight, liver and renal function) with the DDIs, and, if available, the pharmacogenomics profile. The output of Drug-PN system indicates how high is the risk of interactions and if the concomitant drugs have to be changed, in a drug reconciliation process. This software allows reaching a highly tailored approach for every patient. In our real-world population, even if the majority of patients had no to low risk interactions, about 10% of patients had a potentially dangerous drug interaction. This rate is in line with data coming from another large study.^38,39 However, we calculated the Drug-PIN output before and after the introduction of abemaciclib in the routinary treatment of the patients and no significant difference was detected in the overall median score. Indeed, the addition of abemaciclib to the baseline medications did not affect the score in the majority of patients, confirming that abemaciclib is characterized by a low risk of DDIs itself.

The survival analysis showed that the group of patients with high Drug-PIN score and tier had a significant worse PFS compared to patients with no/low DDIs (23 vs 15 months; p = 0.005). Conversely, it is relevant to note that the number of concomitant drugs and the polypharmacy were not associated with survival outcomes. This emphasizes the importance of the quality of drug interactions over the sheer quantity of medications taken by the patient. Considering the expected different PFS among patients treated with abemaciclib + AI vs abemaciclib + fulvestrant, we evaluated the DDIs separately for the two groups. The predictive value of Drug-PIN was confirmed in both endocrine sensitive and endocrine resistant settings: patients with high risk DDIs had a shorter PFS regardless of treatment received. Finally, the MVA confirmed Drug-PIN as an independent predictive factor of PFS (p = 0.002), together with age and ET association.

With all the limitations of a retrospective/prospective real-wold study and a limited sample size, the results allow us to hypothesize that DDIs can have a significant impact on the efficacy of oncological therapy, even in the absence of a direct interaction. The reduced efficacy could be due to an unexpected metabolic alteration or to a greater frailty of the patient with DDIs. Further investigations are needed to clarify this point.

However, no significant difference in number or severity of AEs were reported in patients with or without high DDIs. We found only a numerical higher number of severe diarrhea (p = 0.07), DVT (p = 0.09) and anaemia of any grade (p = 0.06) in patients with high Drug-PIN score. These trends would probably be more significant by expanding the sample size.

In conclusion, we confirmed that abemaciclib is safe and effective in a real-world population, also in an elderly population and patients with comorbidities. DDIs evaluation seems to be an independent predictor of PFS. Further real-world, country-based studies with similar large populations are encouraged to support our results. Prospective studies with the addition of pharmacogenomic evaluations would be useful to better clarify the impact of DDIs on cancer treatments.

Funding: This research received no external funding.

Institutional Review Board Statement: The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Ethics Committee (Ethical Committee no. Sapienza n° 0799/2020, Sapienza University of Rome, Rome, Italy).

Data Availability Statement: The datasets analysed during the current study are available from the corresponding author on reasonable request. Please mail to [email protected]

Conflicts of Interest: 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, Seagen.
Competing interests: Maurizio Simmaco (MS), Paolo Marchetti and Robert Preissner (RP) are member of the Advisory Board of Drug-PIN AG (software expressly cited in the text). The Drug-PIN AG is holder of the patent PCT/IB2019/052310.

The remaining authors declare no Competing Financial or Non-Financial Interests.

Author Contributions: Conceptualization, SS, AB; methodology, SS, AB, LS, RP; software, LS, RP, MS; validation DS, GC, EC, PM, UdG, MdL, PV; formal analysis SS, AF, AB, LS; investigation SP, GM, FD, CP, SdL, RC, AT, BTS, AC, SPa, GT, AO, RS, IP, GD, MP, AF, ER, MS; resources AB, AF, AT, UDG, DS, PM, EC, GC, PV, OG, MDL, RP, ML; data curation, SS, AB, LS and SP; writing-original draft preparation, SS and SP; writing-review and editing: all authors; visualization LS, BC, ML; supervision MDL, GC, UDG, AT, AF, OG, AB, IP, PM, DS, MS, RP, EC; project administration SS, SP, MDL, GC, UDG, AT, AF, OG, AB, PM and DS. All authors have read and agreed to the published version of the manuscript.

Acknowledgments: SP e AC are fellow of the Phd Network Oncology and Precision Medicine, Department of Experimental Medicine, Sapienza University of Rome.

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There is a conflict of interest 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, Seagen. Competing interests: Maurizio Simmaco (MS), Paolo Marchetti and Robert Preissner (RP) are member of the Advisory Board of Drug-PIN AG (software expressly cited in the text). The Drug-PIN AG is holder of the patent PCT/IB2019/052310. The remaining authors declare no Competing Financial or Non-Financial Interests.

supplementaryfigure1.jpg
Suppl Fig 1: PFS according to endocrine resistance
supplementaryfigure2.jpg
Suppl Fig 2: PFS according to comorbidity
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Suppl fig 3: PFS according to stratified comorbidities
supplementaryfigure4.jpg
Suppl Fig 4: PFS according to age-based groups
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Suppl Fig 5: MVA of PFS according to the three variable (Drug associated, Drug-PIN tier and age)
supplementaryfigure6.jpg
Suppl Fig 6: OS according to Drug-PIN tier and DDIs high vs low risk
supplementaryfigure7.jpg
Suppl Fig 7: OS according to treatment toxicity
SupplTable1.docx
Suppl Table 1: UVA of association between Drug-PIN score or light with different AEs

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Real-world experience and clinical impact of drug-drug interactions in HR+/HER2- advanced breast cancer patients treated with abemaciclib plus endocrine therapy: the AB-ITALY study

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