Steatotic liver disease in metastatic breast cancer treated with endocrine therapy and CDK4/6 inhibitor

Steatotic liver disease in metastatic breast cancer treated with endocrine therapy and CDK4/6 inhibitor | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Steatotic liver disease in metastatic breast cancer treated with endocrine therapy and CDK4/6 inhibitor Diego Malon, Consolacion Molto, Shopnil Prasla, Danielle Cuthbert, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4770215/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Dec, 2024 Read the published version in Breast Cancer Research and Treatment → Version 1 posted 14 You are reading this latest preprint version Abstract Purpose In early-stage breast cancer, steatotic liver disease (SLD) is associated with increased recurrence, cardiovascular events, and non-cancer death. Endocrine therapy (ET) increases the risk of SLD. The impact of cyclin-dependent kinases 4/6 inhibitors (CDK4/6i) on SLD and prognostic association in metastatic breast cancer is unknown. We characterized the incidence, prevalence, risk factors, and treatment outcomes of SLD in metastatic HR+/HER2- breast cancer receiving CDK4/6i. Methods This single institution, retrospective, cohort study included patients with metastatic HR+/HER2- breast cancer receiving first-line ET and CDK4/6i from January 2018 to June 2022. SLD was defined as a Liver Attenuation Index (LAI) > 25 HU on contrast-enhanced CT scans and/or > 10 HU on plain CT scans. Univariable binary-logistic regression was used to assess associations with SLD. Time to treatment failure (TTF) and overall survival (OS) were analyzed using Cox proportional hazards modeling. Results Among 87 patients with a median age of 58 years and 65.5% postmenopausal, 50 (57.5%) had SLD at anytime (24 at baseline, 26 acquired). SLD at baseline was quantitatively but not statistically associated with age > 65, post-menopausal status, diabetes, smoking, and HER2-low status. SLD at anytime was statistically significantly associated with longer TTF (median 470 vs 830.5 days, HR = 0.38, p < 0.001). No significant differences in OS or grade 3/4 adverse events were observed between groups. Conclusion This study demonstrated a high prevalence of SLD in this population, with SLD presence associated with longer TTF. SLD may be an indicator of better outcomes in metastatic HR+/HER2- breast cancer patients treated with CDK4/6i. Metastatic breast cancer CDK 4/6 inhibitors endocrine therapy SLD NAFLD MASLD computed tomography Figures Figure 1 Figure 2 Introduction The standard first line systemic therapy for HR positive, HER2 negative breast cancer (HR+/HER2-) metastatic breast cancer is cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) combined with endocrine therapy (ET). Data from pivotal phase III trials have shown an improvement in progression free survival and overall survival with a median treatment duration of 20–24 months when CDK 4/6i are added to ET [ 1 , 2 ]. Although disease remains incurable, the median overall survival is 5–6 years. As women live longer, the acute and medium-term toxicities from systemic therapy must be diagnosed and managed, as these could impact quality of life, and potentially cancer outcomes. Cellular metabolics and energetics are hallmarks of the proliferative capacity of cancer cells [ 3 ]. Lipid metabolism is particularly critical, supplying energy, components for biological membranes, and signaling molecules for proliferation, survival, and metastasis. Lipids are also involved in several other functions within tumor microenvironment such as angiogenesis and immunomodulation. Lipid metabolism can influence treatment response and toxicity [ 4 – 6 ]. Clinically, cancer patients may exhibit changes in body composition or accumulation of visceral fatty tissue, such as steatotic liver disease (SLD). Body composition parameters are attracting attention for their association with treatment efficacy and toxicity in breast cancer; sarcopenia is associated with a poor prognosis, but obesity can be associated with either a better or worse prognosis depending on the disease and setting [ 7 – 12 ]. In early-stage breast cancer, obesity is also associated with worse disease-related outcomes; in the advanced setting both sarcopenia and obesity are associated with worse outcomes, although these associations are controversial due to the scarcity of studies and varying results [ 13 – 15 ]. SLD is strongly associated with metabolic syndrome. This condition, now known as metabolic dysfunction-associated steatotic liver disease (MASLD), was previously referred to as non-alcoholic fatty liver disease (NAFLD) [ 16 ]. MASLD is a common cause of chronic liver disease, and up to 30% of cases can progress to steatohepatitis which may lead to cirrhosis [ 17 , 18 ]. The prevalence of MASLD in patients with any stage of breast cancer is significantly higher than in healthy controls (45.2% vs 16.4%), with over 60% of newly diagnosed breast cancer patients having this diagnosis [ 19 ] which may reflect an overlap of risk factors. MASLD is associated with menopausal status [ 20 ], poor metabolic profile, and cancer treatments, leading to insulin resistance and cardiovascular complications [ 21 ]. In most studies on early-stage breast cancer, MASLD is linked to increased breast cancer recurrence [ 22 , 23 ] and higher risk of non-cancer-related deaths (from cardiovascular and chronic liver disease) [ 24 , 25 ]. The incidence and prevalence of MASLD has been documented in the curative setting for both pre- and postmenopausal women with breast cancer on adjuvant ET. Tamoxifen increases the risk of developing MASLD and exacerbates pre-existing MASLD as early as 3 months into treatment, typically within the first 2 years [ 26 – 29 ]. Aromatase inhibitors are hypothesized to increase the risk of MASLD due to estrogen synthesis inhibition, although less so than tamoxifen [ 30 – 32 ]. Body composition has been demonstrated to potentially influence treatment response and disease recurrence/progression [ 10 , 15 , 33 ]. CDK4/6i play a dual role in regulating both cancer proliferation and metabolism including lipid synthesis [ 34 ] and may impact on body fat mass [ 35 , 36 ]. The impact of CDK4/6i combined with ET on SLD and its prognostic significance in metastatic breast cancer remains unknown. In this study, we characterize the incidence, prevalence, risk factors, and treatment outcomes of SLD in women with metastatic HR+/HER2- breast cancer receiving first line ET with a CDK4/6i. We hypothesize that the prevalence of SLD in advanced disease is higher than the non-cancer population and that this may negatively impact treatment tolerance and cancer outcomes. Materials and methods Study Design: We conduced a longitudinal retrospective cohort study in patients with metastatic ER+/Her2- breast cancer who received first-line ET combined with CDK4/6i at the Princess Margaret Cancer Centre in Toronto, Canada. The study adhered to the principles outlined in the Declaration of Helsinki, and research ethics approval was obtained (approval number 22-5856). We included all patients diagnosed with locally advanced, unresectable or metastatic breast cancer who started on first line endocrine therapy (aromatase-inhibitor or fulvestrant) and CDK 4/6i between January 2018 and June 2022. To ensure comprehensive data collection, patients had to have received the majority of their care (at least 80%) at our institution, which allowed access to radiology reports and required them to undergo regular CT scan (at least every 3–6 months during most of treatment period). Participants were excluded if they had a documented prior history of any chronic liver disease, had received chemotherapy for breast cancer in the metastatic setting, or had undergone systemic therapy for any other malignancy. Receiving chemotherapy in the adjuvant or neoadjuvant setting was allowed. Data were extracted through retrospective chart review up to and including December 31, 2022. The collected data included baseline demographics (age, ECOG status, menopausal status, BMI, smoking and alcoholic habit, details of metabolic profile), baseline clinical data (presence of diabetes (DM), dyslipidemia (DL) or high blood pressure (HBP)), and oncologic diagnosis details (sites of metastasis, de novo or recurrent disease, pathology biomarkers). Visceral metastases were categorized as those in the liver, lung, peritoneum (ascites), pleura (effusion), and central nervous system. Non-visceral metastases included those in bone, skin, and lymph nodes. Additionally, we extracted oncology history (type of CDK 4/6i and ET, number of subsequent lines of therapy, and date of death or last follow-up). Clinical data related to CDK4/6i use were extracted, including duration of treatment, toxicity (type of toxicity with focus on neutropenia and hepatotoxicity and grade, categorized using the Common Terminology Criteria for Adverse Events (CTCAE) version 5.0), and dose reductions. Outcomes: The primary outcome was to describe the incidence, prevalence, and associated clinical and demographic factors of SLD in this population. Secondary outcomes included characterizing treatment exposure, toxicity, and assessment of the impact of SLD on subsequent lines of treatment, time-to-treatment-failure (TTF), and overall survival (OS). The primary outcome, SLD, was measured using the Liver Attenuation Index (LAI) on CT scan performed according to the standard response follow-up protocol for this population at our centre. The LAI was assessed at baseline and at each re-staging CT scan. LAI was calculated as the difference between mean hepatic attenuation and mean splenic attenuation. Hepatic and spleen attenuation (measured in Hounsfield Units, HU) were visually assessed on a CT workstation by two oncologists independently and reviewed by two radiologists. Images were displayed using standardized abdominal window settings (window width 150 HU; level 50 HU). Attenuation values (HU) in the liver and spleen were measured using circular regions of interest (ROIs) of 250 mm squared (Fig. 1 ). The presence of SLD was defined as an LAI greater than 25 HU on contrast-enhanced portal venous phase CT and greater than 10 HU on non-contrast CT [ 37 – 39 ]. If available, the validated fatty liver HSI model was calculated with aspartate aminotransferase (AST), alanine aminotransferase (ALT), BMI, sex and diabetes mellitus status from the nearest time point before the CT scan. An HSI > 36 indicated SLD with a specificity of 92.4% [ 40 ]. A contrast-enhanced portal venous phase computed tomography (CT) image of a normal liver, showing ROIs positioned in liver segments 2, 7, and 8 based on Couinaud’s segmental classification, while avoiding visible vessels, bile ducts and any potential liver lesions. An additional ROI was placed in the spleen. For this example, LAI = -20.83 HU. For further analysis, two extra ROIs were recorded in the paraspinal muscles. TTF was defined as the interval of time from the initiation of treatment to discontinuation for any reason. Reasons for premature discontinuation could include cancer progression, adverse events, patient decision, or death. OS was defined as the time from initiation of treatment to death. Statistical analysis: Data were analysed using descriptive statistics, including means and standard deviations, or proportions where appropriate. Univariable binary-logistic regression analysis was utilized to evaluate independent associations for SLD. Quantitative significance was determined according to the Burnand criteria, where a hazard ratio (HR) > 2.2 deemed quantitatively significant [ 41 ]. With a small number of patients with SLD, we were unable to perform multivariable analysis due to concerns about poor model fit. TTF and OS were analyzed using Kaplan-Meier analysis and differences between presence or absence of SLD were compared with Cox proportional hazards modeling. Cohen's kappa coefficient was employed to assess the agreement between the diagnosis of SLD based on the LAI in CT scans and the HSI model. Statistical analysis was conducted using IBM® SPSS Statistics, version 20. Statistical significance was defined as p < 0.05 where appropriate. No corrections were made for multiple significance testing. Results Study population: Out of 146 patients identified in the Cancer Registry with advanced ER+/Her2- breast cancer on first line therapy, 87 met eligibility and were included in this analysis with a median age of 58 years and 65.5% postmenopausal. The flow chart depicting patient selection is shown in Figure 2. At the time of analysis, 35 patients remained on CDK4/6i (40.2%), and 59 were alive (67.8%). Among the 87 patients, 50 (57.5%) had SLD at any time: 24 had SLD present at baseline and 26 acquired during treatment. Among those with SLD at baseline, 13 maintained it throughout the follow-up period (11 met criteria in more than 50.0% of CT assessments). In those who acquired SLD during treatment, 11 had it present at last assessment and 8 met criteria in more than 50.0% of CT assessments. The median time to acquisition of SLD was 313 days (range: 47,1278). Clinicopathological baseline features of patients in the entire cohort are presented in Table 1, stratified based on SLD categories (never, baseline, or acquired) in Table 2. Of 87 patients, 80.0% with SLD had at least one cardiometabolic risk factor, meeting the criteria for MASLD. Table 1 Clinicopathological features of patients in the whole group Parameters n (%) Age Median years 58 <65 years 26 (29.9) ≥65 years 61 (70.1) ECOG performance status 0 63 (72.4) 1 21 (24.1) 2 3 (3.4) Menopausal status Premenopausal 30 (34.5) Postmenopausal 57 (65.5) Body mass index <30 kg/ m2 59 (67.8) ≥30 kg/m2 28 (32.2) <25 kg/m2 23 (26.4) ≥25 kg/m2 64 (73.6) Diabetes mellitus No 76 (87.4) Yes 11 (12.6) HBP No 67 (77.0) Yes 20 (23.0) Dyslipidemia No 72 (82.8) Yes 15 (17.2) Smoker No 79 (90.8) Yes 8 (9.2) Alcohol No 84 (96.6) Yes 3 (3.4) De novo disease No 29 (33.3) Yes 58 (66.7) Previous adjuvant chemotherapy No 67 (77.0) Yes 20 (23.0) Previous adjuvant endocrine therapy No 63 (72.4) Yes 24 (27.6) Grade 1 3 (3.4) 2 28 (32.2) 3 18 (20.7) Unknown 38 (43.7) ER status 75-100% 79 (90.8) 50-75% 3 (3.4) 25-50% 4 (4.6) <25% 0 Unknown 1 (1.1) PR status Negative 22 (25.3) Positive 61 (70.1) Unknown 4 (4.6) HER2 status Negative 35 (40.2) Low* 51 (58.6) Unknown 1 (1.1) Metastatic location No visceral 38 (43.7) Visceral 49 (56.3) Treatment regimen Palbociclib 66 (75.9) Ribociclib 20 (23.0) Abemaciclib 1 (1.1) Hormonal therapy Letrozole 81 (93.2) Exemestane 1 (1.1) Anastrozole 0 Tamoxifen 1 (1.1) Fulvestrant 4 (4.6) SLD baseline No 63 (72.4) Yes 24 (27.6) CT scans Contrast 82 (94.2) Plain 5 (5.8) ECOG Eastern Cooperative Oncology Group, ER Estrogen Receptor, PR Progesterone Receptor, HBP high blood pressure, HER2 Human Epidermal growth factor Receptor, SLD Steatotic Liver Disease *HER2 low = IHC score 1+ or 2+/in situ hybridization (ISH)-negative. Table 2 Baseline characteristics and clinical data based on groups SLD. Parameter SLD Category n (%) Never (n=37) Baseline (n=24) Acquired (n=26) Age in years, median (range) 54.0 (33,92) 63.5 (45,80) 57.5 (35,87) Age > 65 9 (24.3) 11 (45.8) 6 (23.1) BMI > 30 12 (32.4) 7 (29.2) 9 (3 4.6) Postmenopausal 18 (48.6) 20 (83.3) 19 (73.1) ECOG 0 28 (75.5) 16 (66.7) 19 (73.1) HBP 7 (18.9) 7 (29.2) 6 (23.1) Diabetes M. 4 (10.8) 5 (20.8) 2 (7.7) Dyslipidemia 6 (16.2) 6/ (25) 3 (11.5) Alcohol 1 (2.7) 1 (4.2) 1 (3.8) Smoker 1 (2.7) 4 (16.7) 3 (11.5) Prior Breast Cancer 13 (35.1) 6 (25) 10 (38.5) Prior Chemotherapy 11 (29.7) 4 (16.7) 5 (19.2) Prior Endocrine Therapy 11 (29.7) 5 (20.8) 8 (30.8) Grade 3 10 (27) 6 (25) 3 (11.5) ER > 75% 36 (97.3) 20 (83.3) 23 (88.5) PR negative 7 (18.9) 6 (25.0) 9 (34.6) HER2 low 19 (51.4) 18 (75.0) 14 (53.8) Visceral Disease 21 (56.8) 14 (58.3) 14 (53.8) SLD Steatotic Liver Disease, BMI Body Mass Index, ECOG Eastern Cooperative Oncology Group, HBP high blood pressure, ER Estrogen Receptor, PR Progesterone Receptor, HER2 Human Epidermal growth factor Receptor *HER2 low = IHC score 1+ or 2+/in situ hybridization (ISH)-negative. SLD association: Risk factors for SLD. The presence of SLD at anytime was quantitatively though not statistically significantly associated with post-menopausal status and smoking (Table 3). The presence of SLD at baseline was quantitatively though not statistically significantly associated with age > 65, post-menopausal status, smoking, DM, and HER 2-low (Table 3). Table 3 Risk factors for SLD. Logistic regression (binary univariable) Dependent variable: SLD SLD at anytime (Baseline + acquired) SLD at baseline Covariable: 1 (reference, presence of each variable analyzed) Variable OR (95%, CI) Univariable P value OR (95%, CI) Univariable P value Age at diagnosis (up to 65 vs more 65-year-old) 1.60 (0.62 to 4,15) 0.332 2.71 (1.01 to 7.29) 0.049 Menopause (yes vs no) 3.74 (1.48 to 9.48) 0.005 3.51 (1.07 to 11.49) 0.038 Alcohol (yes vs no) 1.50 (0.13 to 17,19) 0.745 1.33 (0.11 to 15.33) 0.821 Smoking (yes vs no) 5.86 (0.69 to 49,89) 0.106 2.95 (0.67 to 12.90) 0.151 HBP (yes vs no) 1.51 (0.53 to 4,25) 0.439 1.58 (0.54 to 4,62) 0.400 DM (yes vs no) 1.34 (0.36 to 4,97) 0.659 2.50 (0.68 to 9.13) 0.166 DL (yes vs no) 1.13 (0.36 to 3,52) 0.828 2.00 (0.62 to 6.40) 0.243 BMI>30 0.98 (0.39 to 2,43) 0.966 0.82 (0.30 to 2.29) 0.710 Diagnosis (Recurrence vs De-Novo) 0.87 (0.35 to 2,13) 0.759 0.58 (0.20 to 1.67) 0.312 Prior Chemotherapy (yes vs no) 0.52 (0.19 to 1,42) 0.202 0.59 (0.17 to 1.98) 0.391 Prior ET (yes vs no) 0.83 (0.32 to 2,14) 0.701 0.61 (0.20 to 1.87) 0.387 Grade 3 (yes vs no) 0.59 (0.21 to 1.65) 0.316 1.28 (0.42 to 3.88) 0.660 ER > 75% (yes vs no) 0.17 (0.02 to 1.45) 0.106 0.34 (0.77 to 1.48) 0.151 PR negative (yes vs no) 1.84 (0.66 to 5.10) 0.243 0.98 (0.33 to 2.89) 0.970 HER2 low (yes vs no) 1.68 (0.71 to 4.00) 0.238 2.73 (0.96 to 7.78) 0.061 Visceral disease (yes vs no) 0.97 (0.41 to 2.28) 0.944 01.12 (0.43 to 2.90) 0.815 SLD Steatotic Liver Disease, DM diabetes, DL dyslipidemia, HBP high blood pressure, ET endocrine therapy, ER estrogen receptor, PR progesterone receptor, HER2 Human Epidermal growth factor Receptor SLD and cancer outcomes The presence of SLD at any time was statistically significantly associated with longer TTF (median 470 vs 830.5 days, HR=0.38, p<0.001) and numerically longer but not statistically significant OS. Patients with SLD at baseline also exhibited longer TTF and OS compared to those without SLD at baseline, but this difference was not statistically significance. Among patients who had SLD at any time, 50.0% were still on CDK4/6i at the time of data cut-off compared with 27.0% in those without it. There were no significant differences in the number of subsequent treatment lines (Table 4). It is essential to note that in the groups with SLD, a higher percentage of patient were still on first-line treatment, so it is premature to assess the impact on subsequent lines and OS. Table 4 Cancer Outcomes Outcome SLD Category Never (n=37) Baseline (n=24) Acquired (n=26) Best response n (%) PR 14 (37.8) SD 19 (51.4) PD 4 (10.8) PR 10 (41.7) SD 11 (45.8) PD 3 (12.5) PR 11 (42.3) SD 15 (57.7) PD 0 Treatment Failure n (%) 27 (73) 14 (58.3) 11 (42.3) TTF Median (days) 470.0 830.5 866.5 Cox Regression Median (days) HR (95% CI), p Cox Regression Median (days) HR (95% CI), p Never vs any time (Baseline + Acquired) 470.00 vs 830.50 0.38 (0.21 to 0.67), p<0.001 No baseline (Never + Acquired) vs Baseline 648.00 vs 830.50 0.80 (0.43 to 1.48), p<0.481 Subsequent lines mean/median still on treatment n (%) 0 lines n (%) 1 lines n (%) 2 lines n (%) 3 lines n (%) 4 lines n (%) 5 lines n (%) 6 lines n (%) 7 lines n (%) 8 lines n (%) 2.26/2 10 (27.0) 5 (13.5) 5 (13.5) 6 (16.2) 6 (16.2) 3 (8.1) 0 (0.0) 6 (2.7) 0 (0.0) 8 (2.7) 1.36/1 10 (41.7) 1 (37.5) 2 (20.8) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 1.55/1 15 (57.7) 1 (3.8) 5(19.2) 4 (15.4) 0 (0.0) 1 (3.8) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) Alive n (%) 24 (64.9) 16 (66.7) 19 (73.1) OS Median (days) 916.0 1152.0 1254.5 Cox Regression Median (days) HR (95% CI) p Cox Regression Median (days) HR (95% CI) p Never vs any time (Baseline + Acquired): 929.0 vs 1173.0 0.55 (0.26 to 1.18) p<0.127 No baseline (Never + Acquired) vs Baseline: 973.0 vs 1152.0 0.91 (0.40 to 2.07) p<0.826 SLD Steatotic Liver Disease, PR partial response, SD stable disease, PD progression disease, TTF time to treatment failure, OS overall survival SLD and toxicity No statistically significant differences were observed in adverse events between different groups. However, the presence of SLD at anytime and at baseline was quantitatively associated with a higher neutropenia of any grade (Tables 5 and 6). Table 5 Toxicity Adverse Event SLD Category Never (n=37) Baseline (n=24) Acquired (n=26) Grade 3/4 any type n (%) 28 (75.7) 19 (79.2) 23 (88.5) Neutropenia n (%) Grade 3/4 29 (78.4) 27 (73.0) 23 (95.8) 17 (70.9) 25 (96.2) 22 (84.6) Transaminitis n (%) Grade 1 Grade 2 Grade 3 5 (13.5) 3 (8.1) 1 (2.7) 1 (2.7) 4 (16.7) 3 (12.5) 1 (4.2) 0 (0.0) 5 (19.2) 5 (19.2) 0 (0.0) 0 (0.0) Dose reductions n (%) 1 reduction 2 reductions 3 reductions 19 (51.4) 8 (21.6) 10 (27.0) 1 (2.7) 16 (66.7) 9 (37.5) 4 (16.7) 3 (12.5) 17 (65.4) 11 (42.3) 2 (7.7) 4 (15.4) SLD Steatotic Liver Disease Table 6 Toxicity and SLD. Logistic regression (binary univariable) Dependent variable: SLD SLD at anytime (Baseline + acquired) SLD at baseline Covariable: 1 (reference, presence of each variable analyzed) Variable OR (95%, CI) Univariable P value OR (95%, CI) Univariable P value Grade 3/4 any type (yes vs no) 1.69 (0.58 to 4.90) 0.336 0.89 (0.28 to 2.88) 0.851 Neutropenia any grade (yes vs no) 6.62 (1.31 to 33.34) 0.022 3.83 (0.46 to 32.03) 0.215 Neutropenia grade 3/4 (yes vs no) 1.31 (0.49 to 3.52) 0.589 0.69 (0.24 to 2.01) 0.500 Transaminitis (yes vs no) 1.40 (0.43 to 4.60) 0.575 1.06 (0.30 to 3.77) 0.928 Dose reductions (yes vs no) 1.84 (0.77 to 4.39) 0.170 1.50 (0.56 to 4.01) 0.420 SLD Steatotic Liver Disease SLD vs HSI model Cohen's kappa coefficient, used to assess the agreement level of SLD diagnosis between LAI in CT scans and the HSI model, was calculated as 0.253 (p 0.017), indicating fair agreement. The sensitivity was determined to be 76%, while the specificity was 49%. Discussion Our study represents a comprehensive analysis of SLD presence and its impact in HR + HER2- metastatic breast cancer treated with CDK4/6i in combination with ET. Notably, we found that 27.6% of our patients had SLD at baseline, and 57.5% had SLD at any time during their treatment. This prevalence is almost double the general population, where SLD affects up to 30% of adults and similar in early stages of breast cancer [ 42 ]. Consistent with findings in the general population, the presence of SLD at baseline in our study was quantitatively associated with factors such as age > 65, post-menopausal status, and other comorbidities such as DM or smoking. Visceral obesity has been associated with to worse metastasis-free survival in early stages breast cancer, but conflicting results have emerged regarding prognosis and treatment response in the advanced setting [ 43 ]. There is limited data regarding to HR + HER2- metastatic breast cancer; however, some studies have explored the association between BMI or body composition and outcomes. Retrospective data have yield conflicting findings related to BMI and ET monotherapy in first line. While studies with fulvestrant have shown both positive and negative associations, data with aromatase inhibitors show no associations [ 14 , 44 – 46 ]. More recently evidence on current standard first line treatment, suggests that overweight patients with metastatic breast cancer may derive greater benefit in progression-free survival (PFS) from the addition of CDK4/6i to ET [ 47 ]. However, neutral findings have also been reported, such as in the pool analysis of trials MONARCH-2 and 3 with abemaciclib, which found no difference in PFS across different BMI categories [ 48 ]. The above results only assessed associations with BMI. CT scans offer more precise information for assessing body composition, particularly visceral adipose tissue (VAT) and SLD. Studies have shown greater consistency in assessment of VAT with CT scans and associations with treatment response compared to BMI although the data are also retrospective. Studies by Yücel, K. B et al [ 49 ] and Franzoi et al [ 50 ] have demonstrated that a higher VAT index is associated with longer PFS in patients treated with CDK 4/6i. Specifically, Yücel reported a PFS of 20.4 vs 9.3 months ( p = 0.033) and Franzoi found a PFS of 20.8 vs 10.4 months (HR: 0.40; 95% CI 0.16–0.99 p = 0.041). Additionally, Kripa et al [ 51 ] observed that a favorable response to therapy correlated with higher VAT value. However, there are conflicting findings regarding the changes in visceral fat during treatment. Franzoi et al. noted no significant changes in body composition throughout the treatment period, whereas Yücel, K. B et al observed a statistically significant decrease in VAT at 6 months, suggesting an antiadipogenic effect of CDK4/6i. Our study demonstrated that the presence of SLD at any time was significantly associated with longer TTF. These outcomes were also superior in patients who only had SLD at baseline although the differences were not statistically significant, possibly due to low power. In relation to the evolution of SLD during treatment, our findings indicate that while a significant portion of patients who had SLD before treatment retained it (54.2%), a considerable percentage of those who did not have SLD at baseline acquired it during treatment (41.3%), with a substantial proportion maintaining it until the last follow up (42.3%). Our findings may suggest survivor treatment bias, wherein disease with more favourable biology and thereby improved outcomes results in prolonged exposure to ET and CDK4/6i which in turn leads to more opportunity to observe SLD (i.e. a form of immortal time bias). Alternatively, it could indicate these groups represent distinct populations with different molecular pathways, resulting in variations in treatment, prognosis, and metabolic dysregulation. Importantly, the median time to develop SLD in the acquired group was 313 days, and the group that never developed it had a treatment duration longer than this, which argues against the survivor treatment bias hypothesis. The alternative hypothesis suggests there could be a different metabolic pathway could enhance sensitivity and prolong the response to CDK4/6i treatment. However, it may also induce adverse metabolic effects, such as increased lipid synthesis, as observed in preclinical models. For instance, emerging research indicates that E2F1 acts as a regulator of metabolism [ 52 ], SIRT6 is implicated in MASLD [ 53 ], and RB1 deficiency induces mitochondrial oxidative phosphorylation in breast cancer [ 54 ]. Due to the dual role of this molecular pathway, CDK4/6i are also being tested in diet-induced obesity (DIO) [ 55 ]. However, our study also shows that a high percentage of patients undergoing treatment maintain or even acquire SLD. This is significant concerning long-term cardiovascular and hepatic risks and the potential conditioning of future treatments in advanced disease, which also can produce metabolic toxicity (e.g. hyperglycemia with phosphatidylinositol 3-kinase (PI3K) inhibitors). Furthermore, CDK4/6i have recently become part of the standard adjuvant treatment in early-stage high-risk patients, exposing more patients with curative intent to potential long-term effects, which is particularly important for individualized decision-making. Reassuringly, data in early stage breast cancer with higher BMI, for example, with palbociclib in PALLAS study, did not show an increase in short-term toxicity such as neutropenia [ 56 ]. Further studies are warranted to establish correlations between metabolic changes and clinical and molecular data to better characterize these pathways and a more comprehensive understanding of the long-term consequences. This could pave the way for a holistic therapeutic approach incorporating physical exercise, dietary modifications, or pharmacological interventions alongside CDK4/6i. If these pathways are shared, such interventions could not only synergistically improve cancer outcomes but also mitigate metabolic consequences, reduce cardiovascular risks, and enhance patients' functional reserves for future lines of therapy. There are important limitations in our study in addition to the biases discussed above. First, it is a retrospective single-centre study with patients predominantly receiving palbociclib. Results may not be generalizable to other CDK4/6i. Second, the gold standard to evaluate SLD with imaging is MRI or US, but we used CT scans due to their widespread availability and utilization as the standard response assessment in metastatic breast cancer. Although CT scans may have a limited accuracy in detecting mild steatosis, they exhibit high specificity (nearly 100%) and sensitivity (75–80%) in diagnosing moderate to severe cases [ 57 ]. A notable strength of our study is the regular assessment of SLD status during each re-staging CT scan. Finally, the shorter follow-up period may be insufficient to evaluate the impact on OS and subsequent treatment lines adequately. An update on these outcomes with longer follow-up may be warranted. In summary, this analysis reveals a high incidence and prevalence of SLD in HR + HER2- metastatic breast cancer undergoing treatment with CDK4/6i with ET. These findings are consistent with previous reports in other breast cancer settings. A positive association was observed between the presence of SLD and longer TTF. This observation may suggest that these patients represent distinct populations with increased sensitivity to treatment with CDK4/6i and better outcomes, although accompanied by adverse metabolic alterations, particularly in lipid synthesis. If substantiated, this hypothesis underscores the potential for a synergistic therapeutic approach integrating CDK4/6i with interventions such as physical exercise, dietary modifications, or pharmacological strategies. Such a comprehensive approach could not only enhance cancer treatment outcomes but also ameliorate harmful metabolic changes, and mitigate associated health risks, including cardiovascular complications. Declarations Acknowledgements The authors would like to acknowledge all the women who participated in this study. The authors are solely responsible for the design of the study, data collection, the analysis or interpretation of the data, the writing of the article, or the decision to submit for publication. This project represents independent research. We extend our gratitude to the Hold'em for Life Oncology Fellowships at the University of Toronto's Temerty Faculty of Medicine for supporting Dr. Diego Malon as a Clinical Fellow, enabling this work to be carried out. Author contributions Diego Malon, MD (Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Software; Writing—original draft; review & editing; Funding acquisition), Consolacion Molto, MD, PhD (Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Software; review & editing), Shopnil Prasla, MD (Investigation; Methodology; Software; Supervision; review & editing), Danielle Cuthbert, MD (Writing— review & editing), Neha Pathak, MD (Writing—review & editing), Yael Berner-Wygoda, MD (Writing—review & editing), Massimo Di lorio, MD (Writing—review & editing), Meredith Li, MD (Writing—review & editing), Jacqueline Savill, NP (Writing—review & editing), Abhenil Mittal, MD (Writing—review & editing), Eitan Amir, MD, PhD (Formal analysis; Investigation; Methodology; Resources, Software; Supervision; Writing— review & editing), Kartik Jhaveri, MD (Investigation; Methodology; Software; Supervision; Writing—review & editing), Michelle B. Nadler, MD (Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Software; Supervision; Writing—original draft; review & editing; Funding acquisition). All authors read and approved the final manuscript. Funding Dr. Diego Malon was supported as a clinical Fellow by Hold'em for Life Oncology Fellowships at the University of Toronto’s Temerty Faculty of Medicine. Data availability The data described in the manuscript were stored in a coded data extraction spreadsheet on a password-protected computer, in accordance with the research ethics approval. The study data will be retained for auditing purposes for 10 years after the study's completion and will be made available upon reasonable request through written proposals to the corresponding author. Conflict of interest Dr. Diego Malon reports honoraria/speaking fee from Bristol Meyers Squibb. Dr. Consolacion Molto reports honoraria/speaking fees from AstraZeneca and Merck. Dr. Eitan Amir reports honoraria/consulting or Advisory role fees from Seagen, Gilead, AstraZeneca and Novartis. Dr. Nadler reports speaker honorarium and consulting fees from Novartis and Exact Sciences. All of them outside of the scope of this submitted work. No Conflict of Interest for Shopnil Prasla, Danielle Cuthbert, Neha Pathak, Yael Berner-Wygoda, Massimo Di lorio, Meredith Li, Jacqueline Savill, Abhenil Mittal and Kartik Jhaveri. Ethics approval This study was performed in line with the principles of the Declaration of Helsinki and The University Health Network Research Ethics Board approval was obtained (approval number 22-5856). Consent to participate Due to the characteristics of the study written informed consent of the participants is not required. A waiver of consent will not adversely affect the rights and welfare of the subjects. This research will not affect clinical care of the individuals. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4770215","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":339861393,"identity":"dfcc926a-bd44-425c-a8a1-0c658a72a33c","order_by":0,"name":"Diego Malon","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABD0lEQVRIie3PsUrDQBjA8SsH1+WSrCkB8woXAkFp1VfpRyFTEcTFsdNNlqzxLepydGvkBpeoD3CLpSAd41LopNe00iq54uhw/+HuG+7H8SFks/3H5O52N0e/HnGB/0TInpD+cVIckm2UHSXuE5bLComQtMdyOR/2rjyvXAXXUxR6o2bSkSQ9y5GKOH1JT0GkN53RswjuSxTlRTNhkiYxRarF/WHCQEiYPI5F4HC9l5F4qw253JFPmEn6XpPQ/AteaAKaxG8gCpgQSmrCDETvkrRypgaclgkCMYC8JHHX4X70YCDuq1xU1a06z9p38cdaXECWyblyeC88MRAd8RH7Hvb5zY+34er3YLPZbLYffQGkJlqIZo0aUAAAAABJRU5ErkJggg==","orcid":"","institution":"Princess Margaret Cancer Centre","correspondingAuthor":true,"prefix":"","firstName":"Diego","middleName":"","lastName":"Malon","suffix":""},{"id":339861394,"identity":"c8f3f25a-d35f-45bb-9c65-bae4a4ada172","order_by":1,"name":"Consolacion Molto","email":"","orcid":"","institution":"Department of Oncology, Queen’s University, Kingston (Ontario), Canada","correspondingAuthor":false,"prefix":"","firstName":"Consolacion","middleName":"","lastName":"Molto","suffix":""},{"id":339861395,"identity":"f9dd4d0d-dbfb-4c42-92b5-a08449baa5d7","order_by":2,"name":"Shopnil Prasla","email":"","orcid":"","institution":"Joint Department of Medical Imaging (JDMI), University Health Network, Toronto (Ontario), Canada","correspondingAuthor":false,"prefix":"","firstName":"Shopnil","middleName":"","lastName":"Prasla","suffix":""},{"id":339861396,"identity":"1c3de66d-eba1-4bf6-8f32-480aecf49d0c","order_by":3,"name":"Danielle Cuthbert","email":"","orcid":"","institution":"Princess Margaret Cancer Centre","correspondingAuthor":false,"prefix":"","firstName":"Danielle","middleName":"","lastName":"Cuthbert","suffix":""},{"id":339861397,"identity":"0894bba4-6f25-494a-a85d-800020e92583","order_by":4,"name":"Neha Pathak","email":"","orcid":"","institution":"Princess Margaret Cancer Centre","correspondingAuthor":false,"prefix":"","firstName":"Neha","middleName":"","lastName":"Pathak","suffix":""},{"id":339861398,"identity":"1efb0eca-2895-420b-bbe6-2c7619332569","order_by":5,"name":"Yael Berner-Wygoda","email":"","orcid":"","institution":"Princess Margaret Cancer Centre","correspondingAuthor":false,"prefix":"","firstName":"Yael","middleName":"","lastName":"Berner-Wygoda","suffix":""},{"id":339861399,"identity":"4354f2c7-50e9-44cf-af8d-824c8f14b38e","order_by":6,"name":"Massimo Di lorio","email":"","orcid":"","institution":"Princess Margaret Cancer Centre","correspondingAuthor":false,"prefix":"","firstName":"Massimo","middleName":"Di","lastName":"lorio","suffix":""},{"id":339861400,"identity":"cfb5fe49-b722-4994-a028-b2a88427adfd","order_by":7,"name":"Meredith Li","email":"","orcid":"","institution":"Princess Margaret Cancer Centre","correspondingAuthor":false,"prefix":"","firstName":"Meredith","middleName":"","lastName":"Li","suffix":""},{"id":339861401,"identity":"42e57c86-b2a1-4ad4-a732-253da1abc3ab","order_by":8,"name":"Jacqueline Savill","email":"","orcid":"","institution":"Princess Margaret Cancer Centre","correspondingAuthor":false,"prefix":"","firstName":"Jacqueline","middleName":"","lastName":"Savill","suffix":""},{"id":339861402,"identity":"303b1b1c-6a9e-4a44-becc-d715502def41","order_by":9,"name":"Abhenil Mittal","email":"","orcid":"","institution":"Department of Oncology, Health Sciences North, Sudbury (Ontario), Canada","correspondingAuthor":false,"prefix":"","firstName":"Abhenil","middleName":"","lastName":"Mittal","suffix":""},{"id":339861403,"identity":"8149ba5b-1a54-4fe9-9f66-a2a26666ecb1","order_by":10,"name":"Eitan Amir","email":"","orcid":"","institution":"Princess Margaret Cancer Centre","correspondingAuthor":false,"prefix":"","firstName":"Eitan","middleName":"","lastName":"Amir","suffix":""},{"id":339861404,"identity":"31689fd5-bc5e-4729-9f3a-8aedec718e8f","order_by":11,"name":"Kartik Jhaveri","email":"","orcid":"","institution":"Joint Department of Medical Imaging (JDMI), University Health Network, Toronto (Ontario), Canada","correspondingAuthor":false,"prefix":"","firstName":"Kartik","middleName":"","lastName":"Jhaveri","suffix":""},{"id":339861405,"identity":"feb7af71-9c4e-40c4-941f-ac675b62c21e","order_by":12,"name":"Michelle B. Nadler","email":"","orcid":"","institution":"Princess Margaret Cancer Centre","correspondingAuthor":false,"prefix":"","firstName":"Michelle","middleName":"B.","lastName":"Nadler","suffix":""}],"badges":[],"createdAt":"2024-07-19 21:23:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4770215/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4770215/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10549-024-07578-2","type":"published","date":"2024-12-25T15:57:47+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":62730767,"identity":"20e6ac22-7557-4117-9190-327e9e2270a0","added_by":"auto","created_at":"2024-08-18 23:22:57","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":398051,"visible":true,"origin":"","legend":"\u003cp\u003eCircular regions of interest (ROIs) for Steatotic Liver Disease (SLD) assessment\u003c/p\u003e\n\u003cp\u003eA contrast-enhanced portal venous phase computed tomography (CT) image of a normal liver, showing ROIs positioned in liver segments 2, 7, and 8 based on Couinaud’s segmental classification, while avoiding visible vessels, bile ducts and any potential liver lesions. An additional ROI was placed in the spleen. For this example, LAI = -20.83 HU. For further analysis, two extra ROIs were recorded in the paraspinal muscles.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4770215/v1/498e89b7e4beef1d6406d675.png"},{"id":62730765,"identity":"b893b228-8610-4648-adc0-fd5c5046f749","added_by":"auto","created_at":"2024-08-18 23:22:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":53564,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart for patient selection\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4770215/v1/054e7dcbf65c42768bc4ed72.png"},{"id":72640827,"identity":"27d05f1e-e40b-4cec-ba31-8fadb1ad2847","added_by":"auto","created_at":"2024-12-30 16:10:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1585978,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4770215/v1/75189d53-eaca-4dbb-b381-6100afd38be0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Steatotic liver disease in metastatic breast cancer treated with endocrine therapy and CDK4/6 inhibitor","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe standard first line systemic therapy for HR positive, HER2 negative breast cancer (HR+/HER2-) metastatic breast cancer is cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) combined with endocrine therapy (ET). Data from pivotal phase III trials have shown an improvement in progression free survival and overall survival with a median treatment duration of 20\u0026ndash;24 months when CDK 4/6i are added to ET [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Although disease remains incurable, the median overall survival is 5\u0026ndash;6 years. As women live longer, the acute and medium-term toxicities from systemic therapy must be diagnosed and managed, as these could impact quality of life, and potentially cancer outcomes.\u003c/p\u003e \u003cp\u003eCellular metabolics and energetics are hallmarks of the proliferative capacity of cancer cells [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Lipid metabolism is particularly critical, supplying energy, components for biological membranes, and signaling molecules for proliferation, survival, and metastasis. Lipids are also involved in several other functions within tumor microenvironment such as angiogenesis and immunomodulation. Lipid metabolism can influence treatment response and toxicity [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Clinically, cancer patients may exhibit changes in body composition or accumulation of visceral fatty tissue, such as steatotic liver disease (SLD). Body composition parameters are attracting attention for their association with treatment efficacy and toxicity in breast cancer; sarcopenia is associated with a poor prognosis, but obesity can be associated with either a better or worse prognosis depending on the disease and setting [\u003cspan additionalcitationids=\"CR8 CR9 CR10 CR11\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In early-stage breast cancer, obesity is also associated with worse disease-related outcomes; in the advanced setting both sarcopenia and obesity are associated with worse outcomes, although these associations are controversial due to the scarcity of studies and varying results [\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSLD is strongly associated with metabolic syndrome. This condition, now known as metabolic dysfunction-associated steatotic liver disease (MASLD), was previously referred to as non-alcoholic fatty liver disease (NAFLD) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. MASLD is a common cause of chronic liver disease, and up to 30% of cases can progress to steatohepatitis which may lead to cirrhosis [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The prevalence of MASLD in patients with any stage of breast cancer is significantly higher than in healthy controls (45.2% vs 16.4%), with over 60% of newly diagnosed breast cancer patients having this diagnosis [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] which may reflect an overlap of risk factors. MASLD is associated with menopausal status [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], poor metabolic profile, and cancer treatments, leading to insulin resistance and cardiovascular complications [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In most studies on early-stage breast cancer, MASLD is linked to increased breast cancer recurrence [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] and higher risk of non-cancer-related deaths (from cardiovascular and chronic liver disease) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The incidence and prevalence of MASLD has been documented in the curative setting for both pre- and postmenopausal women with breast cancer on adjuvant ET. Tamoxifen increases the risk of developing MASLD and exacerbates pre-existing MASLD as early as 3 months into treatment, typically within the first 2 years [\u003cspan additionalcitationids=\"CR27 CR28\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Aromatase inhibitors are hypothesized to increase the risk of MASLD due to estrogen synthesis inhibition, although less so than tamoxifen [\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Body composition has been demonstrated to potentially influence treatment response and disease recurrence/progression [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. CDK4/6i play a dual role in regulating both cancer proliferation and metabolism including lipid synthesis [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] and may impact on body fat mass [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe impact of CDK4/6i combined with ET on SLD and its prognostic significance in metastatic breast cancer remains unknown. In this study, we characterize the incidence, prevalence, risk factors, and treatment outcomes of SLD in women with metastatic HR+/HER2- breast cancer receiving first line ET with a CDK4/6i. We hypothesize that the prevalence of SLD in advanced disease is higher than the non-cancer population and that this may negatively impact treatment tolerance and cancer outcomes.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design:\u003c/h2\u003e \u003cp\u003eWe conduced a longitudinal retrospective cohort study in patients with metastatic ER+/Her2- breast cancer who received first-line ET combined with CDK4/6i at the Princess Margaret Cancer Centre in Toronto, Canada. The study adhered to the principles outlined in the Declaration of Helsinki, and research ethics approval was obtained (approval number 22-5856).\u003c/p\u003e \u003cp\u003e We included all patients diagnosed with locally advanced, unresectable or metastatic breast cancer who started on first line endocrine therapy (aromatase-inhibitor or fulvestrant) and CDK 4/6i between January 2018 and June 2022. To ensure comprehensive data collection, patients had to have received the majority of their care (at least 80%) at our institution, which allowed access to radiology reports and required them to undergo regular CT scan (at least every 3\u0026ndash;6 months during most of treatment period). Participants were excluded if they had a documented prior history of any chronic liver disease, had received chemotherapy for breast cancer in the metastatic setting, or had undergone systemic therapy for any other malignancy. Receiving chemotherapy in the adjuvant or neoadjuvant setting was allowed.\u003c/p\u003e \u003cp\u003eData were extracted through retrospective chart review up to and including December 31, 2022. The collected data included baseline demographics (age, ECOG status, menopausal status, BMI, smoking and alcoholic habit, details of metabolic profile), baseline clinical data (presence of diabetes (DM), dyslipidemia (DL) or high blood pressure (HBP)), and oncologic diagnosis details (sites of metastasis, de novo or recurrent disease, pathology biomarkers). Visceral metastases were categorized as those in the liver, lung, peritoneum (ascites), pleura (effusion), and central nervous system. Non-visceral metastases included those in bone, skin, and lymph nodes. Additionally, we extracted oncology history (type of CDK 4/6i and ET, number of subsequent lines of therapy, and date of death or last follow-up). Clinical data related to CDK4/6i use were extracted, including duration of treatment, toxicity (type of toxicity with focus on neutropenia and hepatotoxicity and grade, categorized using the Common Terminology Criteria for Adverse Events (CTCAE) version 5.0), and dose reductions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eOutcomes:\u003c/h2\u003e \u003cp\u003eThe primary outcome was to describe the incidence, prevalence, and associated clinical and demographic factors of SLD in this population. Secondary outcomes included characterizing treatment exposure, toxicity, and assessment of the impact of SLD on subsequent lines of treatment, time-to-treatment-failure (TTF), and overall survival (OS).\u003c/p\u003e \u003cp\u003eThe primary outcome, SLD, was measured using the \u003cem\u003eLiver Attenuation Index (LAI)\u003c/em\u003e on CT scan performed according to the standard response follow-up protocol for this population at our centre. The LAI was assessed at baseline and at each re-staging CT scan. LAI was calculated as the difference between mean hepatic attenuation and mean splenic attenuation. Hepatic and spleen attenuation (measured in Hounsfield Units, HU) were visually assessed on a CT workstation by two oncologists independently and reviewed by two radiologists. Images were displayed using standardized abdominal window settings (window width 150 HU; level 50 HU). Attenuation values (HU) in the liver and spleen were measured using circular regions of interest (ROIs) of 250 mm squared (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The presence of SLD was defined as an LAI greater than 25 HU on contrast-enhanced portal venous phase CT and greater than 10 HU on non-contrast CT [\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. If available, the validated fatty liver HSI model was calculated with aspartate aminotransferase (AST), alanine aminotransferase (ALT), BMI, sex and diabetes mellitus status from the nearest time point before the CT scan. An HSI\u0026thinsp;\u0026gt;\u0026thinsp;36 indicated SLD with a specificity of 92.4% [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA contrast-enhanced portal venous phase computed tomography (CT) image of a normal liver, showing ROIs positioned in liver segments 2, 7, and 8 based on Couinaud\u0026rsquo;s segmental classification, while avoiding visible vessels, bile ducts and any potential liver lesions. An additional ROI was placed in the spleen. For this example, LAI = -20.83 HU. For further analysis, two extra ROIs were recorded in the paraspinal muscles.\u003c/p\u003e \u003cp\u003eTTF was defined as the interval of time from the initiation of treatment to discontinuation for any reason. Reasons for premature discontinuation could include cancer progression, adverse events, patient decision, or death. OS was defined as the time from initiation of treatment to death.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis:\u003c/h2\u003e \u003cp\u003eData were analysed using descriptive statistics, including means and standard deviations, or proportions where appropriate. Univariable binary-logistic regression analysis was utilized to evaluate independent associations for SLD. Quantitative significance was determined according to the Burnand criteria, where a hazard ratio (HR)\u0026thinsp;\u0026gt;\u0026thinsp;2.2 deemed quantitatively significant [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. With a small number of patients with SLD, we were unable to perform multivariable analysis due to concerns about poor model fit. TTF and OS were analyzed using Kaplan-Meier analysis and differences between presence or absence of SLD were compared with Cox proportional hazards modeling. Cohen's kappa coefficient was employed to assess the agreement between the diagnosis of SLD based on the LAI in CT scans and the HSI model. Statistical analysis was conducted using IBM\u0026reg; SPSS Statistics, version 20. Statistical significance was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 where appropriate. No corrections were made for multiple significance testing.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e\u003cu\u003eStudy population:\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOut of 146 patients identified in the Cancer Registry with advanced ER+/Her2- breast cancer on first line therapy, 87 met eligibility and were included in this analysis with a median age of 58 years and 65.5% postmenopausal. The flow chart depicting patient selection is shown in Figure 2. At the time of analysis, 35 patients remained on CDK4/6i (40.2%), and 59 were alive (67.8%). Among the 87 patients, 50 (57.5%) had SLD at any time: 24 had SLD present at baseline and 26 acquired during treatment. Among those with SLD at baseline, 13 maintained it throughout the follow-up period (11 met criteria in more than 50.0% of CT assessments). In those who acquired SLD during treatment, 11 had it present at last assessment and 8 met criteria in more than 50.0% of CT assessments. The median time to acquisition of SLD was 313 days (range: 47,1278). Clinicopathological baseline features of patients in the entire cohort are presented in Table 1, stratified based on SLD categories (never, baseline, or acquired) in Table 2. Of 87 patients, 80.0% with SLD had at least one cardiometabolic risk factor, meeting the criteria for MASLD.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e Clinicopathological features of patients in the whole group\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameters\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Median years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e58\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;65 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e26 (29.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;65 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e61 (70.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eECOG performance status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e63 (72.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e21 (24.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e3 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eMenopausal status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003ePremenopausal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e30 (34.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003ePostmenopausal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e57 (65.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eBody mass index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;30 kg/\u0026nbsp;m2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e59 (67.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;30 kg/m2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e28 (32.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;25 kg/m2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e23 (26.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;25 kg/m2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e64 (73.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eDiabetes mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e76 (87.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e11 (12.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eHBP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e67 (77.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e20 (23.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eDyslipidemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e72 (82.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e15 (17.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eSmoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e79 (90.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e8 (9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eAlcohol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e84 (96.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e3 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eDe novo disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e29 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e58 (66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003ePrevious adjuvant chemotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e67 (77.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e20 (23.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003ePrevious adjuvant endocrine therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e63 (72.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e24 (27.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eGrade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e3 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e28 (32.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e18 (20.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e38 (43.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eER status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e75-100%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e79 (90.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e50-75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e3 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e25-50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e4 (4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;25%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e1 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003ePR status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e22 (25.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e61 (70.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e4 (4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eHER2 status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e35 (40.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eLow*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e51 (58.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e1 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eMetastatic location\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eNo visceral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e38 (43.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eVisceral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e49 (56.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eTreatment regimen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003ePalbociclib\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e66 (75.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eRibociclib\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e20 (23.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eAbemaciclib\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e1 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eHormonal therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eLetrozole\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e81 (93.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eExemestane\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e1 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eAnastrozole\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eTamoxifen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e1 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eFulvestrant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e4 (4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eSLD baseline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e63 (72.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e24 (27.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eCT scans\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eContrast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e82 (94.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003ePlain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e5 (5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eECOG Eastern Cooperative Oncology Group, ER Estrogen Receptor, PR Progesterone Receptor, HBP high blood pressure, HER2 Human Epidermal growth factor Receptor, SLD Steatotic Liver Disease\u003c/p\u003e\n \u003cp\u003e*HER2 low = IHC score 1+ or 2+/in situ hybridization (ISH)-negative.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"641\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e Baseline characteristics and clinical data based on groups SLD.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.017160686427456%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"70.98283931357254%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSLD Category n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.18681318681319%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNever\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=37)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.40659340659341%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBaseline\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=24)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.40659340659341%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAcquired\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=26)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.017160686427456%\" valign=\"top\"\u003e\n \u003cp\u003eAge in years, median (range)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.556942277691107%\" valign=\"top\"\u003e\n \u003cp\u003e54.0 (33,92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e63.5 (45,80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e57.5 (35,87)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.017160686427456%\" valign=\"top\"\u003e\n \u003cp\u003eAge \u0026gt; 65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.556942277691107%\" valign=\"top\"\u003e\n \u003cp\u003e9 (24.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e11 (45.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e6 (23.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.017160686427456%\" valign=\"top\"\u003e\n \u003cp\u003eBMI \u0026gt; 30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.556942277691107%\" valign=\"top\"\u003e\n \u003cp\u003e12 (32.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e7 (29.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e9 (3 4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.017160686427456%\" valign=\"top\"\u003e\n \u003cp\u003ePostmenopausal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.556942277691107%\" valign=\"top\"\u003e\n \u003cp\u003e18 (48.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e20 (83.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e19 (73.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.017160686427456%\" valign=\"top\"\u003e\n \u003cp\u003eECOG 0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.556942277691107%\" valign=\"top\"\u003e\n \u003cp\u003e28 (75.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e16 (66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e19 (73.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.017160686427456%\" valign=\"top\"\u003e\n \u003cp\u003eHBP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.556942277691107%\" valign=\"top\"\u003e\n \u003cp\u003e7 (18.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e7 (29.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e6 (23.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.017160686427456%\" valign=\"top\"\u003e\n \u003cp\u003eDiabetes M.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.556942277691107%\" valign=\"top\"\u003e\n \u003cp\u003e4 (10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e5 (20.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e2 (7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.017160686427456%\" valign=\"top\"\u003e\n \u003cp\u003eDyslipidemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.556942277691107%\" valign=\"top\"\u003e\n \u003cp\u003e6 (16.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e6/ (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e3 (11.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.017160686427456%\" valign=\"top\"\u003e\n \u003cp\u003eAlcohol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.556942277691107%\" valign=\"top\"\u003e\n \u003cp\u003e1 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e1 (4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e1 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.017160686427456%\" valign=\"top\"\u003e\n \u003cp\u003eSmoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.556942277691107%\" valign=\"top\"\u003e\n \u003cp\u003e1 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e4 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e3 (11.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.017160686427456%\" valign=\"top\"\u003e\n \u003cp\u003ePrior Breast Cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.556942277691107%\" valign=\"top\"\u003e\n \u003cp\u003e13 (35.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e6 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e10 (38.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.017160686427456%\" valign=\"top\"\u003e\n \u003cp\u003ePrior Chemotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.556942277691107%\" valign=\"top\"\u003e\n \u003cp\u003e11 (29.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e4 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e5 (19.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.017160686427456%\" valign=\"top\"\u003e\n \u003cp\u003ePrior Endocrine Therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.556942277691107%\" valign=\"top\"\u003e\n \u003cp\u003e11 (29.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e5 (20.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e8 (30.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.017160686427456%\" valign=\"top\"\u003e\n \u003cp\u003eGrade 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.556942277691107%\" valign=\"top\"\u003e\n \u003cp\u003e10 (27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e6 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e3 (11.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.017160686427456%\" valign=\"top\"\u003e\n \u003cp\u003eER \u0026gt; 75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.556942277691107%\" valign=\"top\"\u003e\n \u003cp\u003e36 (97.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e20 (83.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e23 (88.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.017160686427456%\" valign=\"top\"\u003e\n \u003cp\u003ePR negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.556942277691107%\" valign=\"top\"\u003e\n \u003cp\u003e7 (18.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e6 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e9 (34.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.017160686427456%\" valign=\"top\"\u003e\n \u003cp\u003eHER2 low\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.556942277691107%\" valign=\"top\"\u003e\n \u003cp\u003e19 (51.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e18 (75.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e14 (53.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.017160686427456%\" valign=\"top\"\u003e\n \u003cp\u003eVisceral Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.556942277691107%\" valign=\"top\"\u003e\n \u003cp\u003e21 (56.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e14 (58.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.712948517940717%\" valign=\"top\"\u003e\n \u003cp\u003e14 (53.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eSLD Steatotic Liver Disease, BMI Body Mass Index, ECOG Eastern Cooperative Oncology Group, HBP high blood pressure, ER Estrogen Receptor, PR Progesterone Receptor, HER2 Human Epidermal growth factor Receptor\u003c/p\u003e\n \u003cp\u003e*HER2 low = IHC score 1+ or 2+/in situ hybridization (ISH)-negative.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eSLD association:\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRisk factors for SLD.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe presence of SLD at anytime was quantitatively though not statistically significantly associated with post-menopausal status and smoking (Table 3). The presence of SLD at baseline was quantitatively though not statistically significantly associated with age \u0026gt; 65, post-menopausal status, smoking, DM, and HER 2-low (Table 3).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"643\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3\u0026nbsp;\u003c/strong\u003eRisk factors for SLD. Logistic regression (binary univariable)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.8006230529595%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDependent variable: SLD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.931464174454828%\" colspan=\"2\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSLD at anytime\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Baseline + acquired)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.26791277258567%\" colspan=\"2\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSLD at baseline\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCovariable: 1 (reference, presence of each variable analyzed)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.8006230529595%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.18380062305296%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR (95%, CI) Univariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.74766355140187%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.052959501557634%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR (95%, CI) Univariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.214953271028037%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.8006230529595%\" valign=\"top\"\u003e\n \u003cp\u003eAge at diagnosis (up to 65 vs more 65-year-old)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.18380062305296%\" valign=\"top\"\u003e\n \u003cp\u003e1.60 (0.62 to 4,15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.74766355140187%\" valign=\"top\"\u003e\n \u003cp\u003e0.332\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.052959501557634%\" valign=\"top\"\u003e\n \u003cp\u003e2.71 (1.01 to 7.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.214953271028037%\" valign=\"top\"\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.8006230529595%\" valign=\"top\"\u003e\n \u003cp\u003eMenopause (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.18380062305296%\" valign=\"top\"\u003e\n \u003cp\u003e3.74 (1.48 to 9.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.74766355140187%\" valign=\"top\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.052959501557634%\" valign=\"top\"\u003e\n \u003cp\u003e3.51 (1.07 to 11.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.214953271028037%\" valign=\"top\"\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.8006230529595%\" valign=\"top\"\u003e\n \u003cp\u003eAlcohol (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.18380062305296%\" valign=\"top\"\u003e\n \u003cp\u003e1.50 (0.13 to 17,19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.74766355140187%\" valign=\"top\"\u003e\n \u003cp\u003e0.745\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.052959501557634%\" valign=\"top\"\u003e\n \u003cp\u003e1.33 (0.11 to 15.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.214953271028037%\" valign=\"top\"\u003e\n \u003cp\u003e0.821\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.8006230529595%\" valign=\"top\"\u003e\n \u003cp\u003eSmoking (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.18380062305296%\" valign=\"top\"\u003e\n \u003cp\u003e5.86 (0.69 to 49,89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.74766355140187%\" valign=\"top\"\u003e\n \u003cp\u003e0.106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.052959501557634%\" valign=\"top\"\u003e\n \u003cp\u003e2.95 (0.67 to 12.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.214953271028037%\" valign=\"top\"\u003e\n \u003cp\u003e0.151\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.8006230529595%\" valign=\"top\"\u003e\n \u003cp\u003eHBP (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.18380062305296%\" valign=\"top\"\u003e\n \u003cp\u003e1.51 (0.53 to 4,25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.74766355140187%\" valign=\"top\"\u003e\n \u003cp\u003e0.439\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.052959501557634%\" valign=\"top\"\u003e\n \u003cp\u003e1.58 (0.54 to 4,62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.214953271028037%\" valign=\"top\"\u003e\n \u003cp\u003e0.400\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.8006230529595%\" valign=\"top\"\u003e\n \u003cp\u003eDM (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.18380062305296%\" valign=\"top\"\u003e\n \u003cp\u003e1.34 (0.36 to 4,97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.74766355140187%\" valign=\"top\"\u003e\n \u003cp\u003e0.659\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.052959501557634%\" valign=\"top\"\u003e\n \u003cp\u003e2.50 (0.68 to 9.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.214953271028037%\" valign=\"top\"\u003e\n \u003cp\u003e0.166\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.8006230529595%\" valign=\"top\"\u003e\n \u003cp\u003eDL (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.18380062305296%\" valign=\"top\"\u003e\n \u003cp\u003e1.13 (0.36 to 3,52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.74766355140187%\" valign=\"top\"\u003e\n \u003cp\u003e0.828\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.052959501557634%\" valign=\"top\"\u003e\n \u003cp\u003e2.00 (0.62 to 6.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.214953271028037%\" valign=\"top\"\u003e\n \u003cp\u003e0.243\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.8006230529595%\" valign=\"top\"\u003e\n \u003cp\u003eBMI\u0026gt;30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.18380062305296%\" valign=\"top\"\u003e\n \u003cp\u003e0.98 (0.39 to 2,43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.74766355140187%\" valign=\"top\"\u003e\n \u003cp\u003e0.966\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.052959501557634%\" valign=\"top\"\u003e\n \u003cp\u003e0.82 (0.30 to 2.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.214953271028037%\" valign=\"top\"\u003e\n \u003cp\u003e0.710\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.8006230529595%\" valign=\"top\"\u003e\n \u003cp\u003eDiagnosis (Recurrence vs De-Novo)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.18380062305296%\" valign=\"top\"\u003e\n \u003cp\u003e0.87 (0.35 to 2,13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.74766355140187%\" valign=\"top\"\u003e\n \u003cp\u003e0.759\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.052959501557634%\" valign=\"top\"\u003e\n \u003cp\u003e0.58 (0.20 to 1.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.214953271028037%\" valign=\"top\"\u003e\n \u003cp\u003e0.312\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.8006230529595%\" valign=\"top\"\u003e\n \u003cp\u003ePrior Chemotherapy (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.18380062305296%\" valign=\"top\"\u003e\n \u003cp\u003e0.52 (0.19 to 1,42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.74766355140187%\" valign=\"top\"\u003e\n \u003cp\u003e0.202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.052959501557634%\" valign=\"top\"\u003e\n \u003cp\u003e0.59 (0.17 to 1.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.214953271028037%\" valign=\"top\"\u003e\n \u003cp\u003e0.391\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.8006230529595%\" valign=\"top\"\u003e\n \u003cp\u003ePrior ET (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.18380062305296%\" valign=\"top\"\u003e\n \u003cp\u003e0.83 (0.32 to 2,14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.74766355140187%\" valign=\"top\"\u003e\n \u003cp\u003e0.701\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.052959501557634%\" valign=\"top\"\u003e\n \u003cp\u003e0.61 (0.20 to 1.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.214953271028037%\" valign=\"top\"\u003e\n \u003cp\u003e0.387\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.8006230529595%\" valign=\"top\"\u003e\n \u003cp\u003eGrade 3 (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.18380062305296%\" valign=\"top\"\u003e\n \u003cp\u003e0.59 (0.21 to 1.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.74766355140187%\" valign=\"top\"\u003e\n \u003cp\u003e0.316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.052959501557634%\" valign=\"top\"\u003e\n \u003cp\u003e1.28 (0.42 to 3.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.214953271028037%\" valign=\"top\"\u003e\n \u003cp\u003e0.660\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.8006230529595%\" valign=\"top\"\u003e\n \u003cp\u003eER \u0026gt; 75% (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.18380062305296%\" valign=\"top\"\u003e\n \u003cp\u003e0.17 (0.02 to 1.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.74766355140187%\" valign=\"top\"\u003e\n \u003cp\u003e0.106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.052959501557634%\" valign=\"top\"\u003e\n \u003cp\u003e0.34 (0.77 to 1.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.214953271028037%\" valign=\"top\"\u003e\n \u003cp\u003e0.151\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.8006230529595%\" valign=\"top\"\u003e\n \u003cp\u003ePR negative (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.18380062305296%\" valign=\"top\"\u003e\n \u003cp\u003e1.84 (0.66 to 5.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.74766355140187%\" valign=\"top\"\u003e\n \u003cp\u003e0.243\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.052959501557634%\" valign=\"top\"\u003e\n \u003cp\u003e0.98 (0.33 to 2.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.214953271028037%\" valign=\"top\"\u003e\n \u003cp\u003e0.970\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.8006230529595%\" valign=\"top\"\u003e\n \u003cp\u003eHER2 low (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.18380062305296%\" valign=\"top\"\u003e\n \u003cp\u003e1.68 (0.71 to 4.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.74766355140187%\" valign=\"top\"\u003e\n \u003cp\u003e0.238\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.052959501557634%\" valign=\"top\"\u003e\n \u003cp\u003e2.73 (0.96 to 7.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.214953271028037%\" valign=\"top\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.8006230529595%\" valign=\"top\"\u003e\n \u003cp\u003eVisceral disease (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.18380062305296%\" valign=\"top\"\u003e\n \u003cp\u003e0.97 (0.41 to 2.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.74766355140187%\" valign=\"top\"\u003e\n \u003cp\u003e0.944\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.052959501557634%\" valign=\"top\"\u003e\n \u003cp\u003e01.12 (0.43 to 2.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.214953271028037%\" valign=\"top\"\u003e\n \u003cp\u003e0.815\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eSLD Steatotic Liver Disease, DM diabetes, DL dyslipidemia, HBP high blood pressure, ET endocrine therapy, ER estrogen receptor, PR progesterone receptor, HER2 Human Epidermal growth factor Receptor\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eSLD and cancer outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe presence of SLD at any time\u0026nbsp;was statistically significantly associated with longer TTF (median 470 vs 830.5 days, HR=0.38, p\u0026lt;0.001) and numerically longer but not statistically significant OS.\u0026nbsp;Patients with SLD at baseline also exhibited longer TTF and OS compared to those without SLD at baseline, but this difference was not statistically significance. Among patients who had SLD at any time, 50.0% were still on CDK4/6i at the time of data cut-off compared with 27.0% in those without it. There were no significant differences in the number of subsequent treatment lines (Table 4). It is essential to note that in the groups with SLD, a higher percentage of patient were still on first-line treatment, so it is premature to assess the impact on subsequent lines and OS.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"690\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 4\u003c/strong\u003e Cancer Outcomes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.798842257597684%\" colspan=\"2\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutcome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.1027496382055%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.049204052098407%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSLD Category\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.049204052098407%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.829268292682926%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNever\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=37)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.58536585365854%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBaseline\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=24)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.58536585365854%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAcquired\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=26)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.798842257597684%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBest response\u003c/strong\u003e n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.1027496382055%\" valign=\"top\"\u003e\n \u003cp\u003ePR 14 (37.8)\u003c/p\u003e\n \u003cp\u003eSD 19 (51.4)\u003c/p\u003e\n \u003cp\u003ePD 4 (10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.049204052098407%\" valign=\"top\"\u003e\n \u003cp\u003ePR 10 (41.7)\u003c/p\u003e\n \u003cp\u003eSD 11 (45.8)\u003c/p\u003e\n \u003cp\u003ePD 3 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.049204052098407%\" valign=\"top\"\u003e\n \u003cp\u003ePR 11 (42.3)\u003c/p\u003e\n \u003cp\u003eSD 15 (57.7)\u003c/p\u003e\n \u003cp\u003ePD 0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.798842257597684%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment Failure\u003c/strong\u003e n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.1027496382055%\" valign=\"top\"\u003e\n \u003cp\u003e27 (73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.049204052098407%\" valign=\"top\"\u003e\n \u003cp\u003e14 (58.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.049204052098407%\" valign=\"top\"\u003e\n \u003cp\u003e11 (42.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.24891461649783%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTTF\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.549927641099856%\" valign=\"top\"\u003e\n \u003cp\u003eMedian (days)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.1027496382055%\" valign=\"top\"\u003e\n \u003cp\u003e470.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.049204052098407%\" valign=\"top\"\u003e\n \u003cp\u003e830.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.049204052098407%\" valign=\"top\"\u003e\n \u003cp\u003e866.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.432859399684045%\" valign=\"top\"\u003e\n \u003cp\u003eCox Regression\u003c/p\u003e\n \u003cp\u003eMedian (days)\u003c/p\u003e\n \u003cp\u003eHR (95% CI), p\u003c/p\u003e\n \u003cp\u003eCox Regression\u003c/p\u003e\n \u003cp\u003eMedian (days)\u003c/p\u003e\n \u003cp\u003eHR (95% CI), p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"77.56714060031595%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eNever vs any time (Baseline + Acquired)\u003c/p\u003e\n \u003cp\u003e470.00 vs 830.50\u003c/p\u003e\n \u003cp\u003e0.38 (0.21 to 0.67), p\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003eNo baseline (Never + Acquired) vs Baseline\u003c/p\u003e\n \u003cp\u003e648.00 vs 830.50\u003c/p\u003e\n \u003cp\u003e0.80 (0.43 to 1.48), p\u0026lt;0.481\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.798842257597684%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSubsequent lines\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003emean/median\u003c/p\u003e\n \u003cp\u003estill on treatment n (%)\u003c/p\u003e\n \u003cp\u003e0 lines n (%)\u003c/p\u003e\n \u003cp\u003e1 lines n (%)\u003c/p\u003e\n \u003cp\u003e2 lines n (%)\u003c/p\u003e\n \u003cp\u003e3 lines n (%)\u003c/p\u003e\n \u003cp\u003e4 lines n (%)\u003c/p\u003e\n \u003cp\u003e5 lines n (%)\u003c/p\u003e\n \u003cp\u003e6 lines n (%)\u003c/p\u003e\n \u003cp\u003e7 lines n (%)\u003c/p\u003e\n \u003cp\u003e8 lines n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.1027496382055%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.26/2\u003c/p\u003e\n \u003cp\u003e10 (27.0)\u003c/p\u003e\n \u003cp\u003e5 (13.5)\u003c/p\u003e\n \u003cp\u003e5 (13.5)\u003c/p\u003e\n \u003cp\u003e6 (16.2)\u003c/p\u003e\n \u003cp\u003e6 (16.2)\u003c/p\u003e\n \u003cp\u003e3 (8.1)\u003c/p\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003cp\u003e6 (2.7)\u003c/p\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003cp\u003e8 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.049204052098407%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.36/1\u003c/p\u003e\n \u003cp\u003e10 (41.7)\u003c/p\u003e\n \u003cp\u003e1 (37.5)\u003c/p\u003e\n \u003cp\u003e2 (20.8)\u003c/p\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.049204052098407%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.55/1\u003c/p\u003e\n \u003cp\u003e15 (57.7)\u003c/p\u003e\n \u003cp\u003e1 (3.8)\u003c/p\u003e\n \u003cp\u003e5(19.2)\u003c/p\u003e\n \u003cp\u003e4 (15.4)\u003c/p\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003cp\u003e1 (3.8)\u003c/p\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.798842257597684%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlive\u003c/strong\u003e n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.1027496382055%\" valign=\"top\"\u003e\n \u003cp\u003e24 (64.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.049204052098407%\" valign=\"top\"\u003e\n \u003cp\u003e16 (66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.049204052098407%\" valign=\"top\"\u003e\n \u003cp\u003e19 (73.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.24891461649783%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOS\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.549927641099856%\" valign=\"top\"\u003e\n \u003cp\u003eMedian (days)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.1027496382055%\" valign=\"top\"\u003e\n \u003cp\u003e916.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.049204052098407%\" valign=\"top\"\u003e\n \u003cp\u003e1152.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.049204052098407%\" valign=\"top\"\u003e\n \u003cp\u003e1254.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.26086956521739%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.579710144927535%\" valign=\"top\"\u003e\n \u003cp\u003eCox Regression\u003c/p\u003e\n \u003cp\u003eMedian (days)\u003c/p\u003e\n \u003cp\u003eHR (95% CI) p\u003c/p\u003e\n \u003cp\u003eCox Regression\u003c/p\u003e\n \u003cp\u003eMedian (days)\u003c/p\u003e\n \u003cp\u003eHR (95% CI) p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"71.15942028985508%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eNever vs any time (Baseline + Acquired):\u003c/p\u003e\n \u003cp\u003e929.0 vs 1173.0\u003c/p\u003e\n \u003cp\u003e0.55 (0.26 to 1.18) p\u0026lt;0.127\u003c/p\u003e\n \u003cp\u003eNo baseline (Never + Acquired) vs Baseline:\u003c/p\u003e\n \u003cp\u003e973.0 vs\u0026nbsp;1152.0\u003c/p\u003e\n \u003cp\u003e0.91 (0.40 to 2.07) p\u0026lt;0.826\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eSLD Steatotic Liver Disease, PR partial response, SD stable disease, PD progression disease, TTF time to treatment failure, OS overall survival\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eSLD and toxicity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo\u0026nbsp;statistically\u0026nbsp;significant differences were observed in adverse events between different groups. However, the presence of SLD at anytime and at baseline was quantitatively associated with a higher neutropenia of any grade (Tables 5 and 6).\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"609\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 5\u003c/strong\u003e Toxicity\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.571428571428573%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdverse Event\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"71.42857142857143%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSLD Category\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.41379310344828%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNever\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=37)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.64367816091954%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBaseline\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=24)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.94252873563219%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAcquired\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=26)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.571428571428573%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrade 3/4\u003c/strong\u003e any type n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.15270935960591%\" valign=\"top\"\u003e\n \u003cp\u003e28 (75.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.316912972085387%\" valign=\"top\"\u003e\n \u003cp\u003e19 (79.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958949096880133%\" valign=\"top\"\u003e\n \u003cp\u003e23 (88.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.571428571428573%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNeutropenia\u003c/strong\u003e n (%)\u003c/p\u003e\n \u003cp\u003eGrade 3/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.15270935960591%\" valign=\"top\"\u003e\n \u003cp\u003e29 (78.4)\u003c/p\u003e\n \u003cp\u003e27 (73.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.316912972085387%\" valign=\"top\"\u003e\n \u003cp\u003e23 (95.8)\u003c/p\u003e\n \u003cp\u003e17 (70.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958949096880133%\" valign=\"top\"\u003e\n \u003cp\u003e25 (96.2)\u003c/p\u003e\n \u003cp\u003e22 (84.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.571428571428573%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTransaminitis n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eGrade 1\u003c/p\u003e\n \u003cp\u003eGrade 2\u003c/p\u003e\n \u003cp\u003eGrade 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.15270935960591%\" valign=\"top\"\u003e\n \u003cp\u003e5 (13.5)\u003c/p\u003e\n \u003cp\u003e3 (8.1)\u003c/p\u003e\n \u003cp\u003e1 (2.7)\u003c/p\u003e\n \u003cp\u003e1 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.316912972085387%\" valign=\"top\"\u003e\n \u003cp\u003e4 (16.7)\u003c/p\u003e\n \u003cp\u003e3 (12.5)\u003c/p\u003e\n \u003cp\u003e1 (4.2)\u003c/p\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958949096880133%\" valign=\"top\"\u003e\n \u003cp\u003e5 (19.2)\u003c/p\u003e\n \u003cp\u003e5 (19.2)\u003c/p\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.571428571428573%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDose reductions n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e1 reduction\u003c/p\u003e\n \u003cp\u003e2 reductions\u003c/p\u003e\n \u003cp\u003e3 reductions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.15270935960591%\" valign=\"top\"\u003e\n \u003cp\u003e19 (51.4)\u003c/p\u003e\n \u003cp\u003e8 (21.6)\u003c/p\u003e\n \u003cp\u003e10 (27.0)\u003c/p\u003e\n \u003cp\u003e1 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.316912972085387%\" valign=\"top\"\u003e\n \u003cp\u003e16 (66.7)\u003c/p\u003e\n \u003cp\u003e9 (37.5)\u003c/p\u003e\n \u003cp\u003e4 (16.7)\u003c/p\u003e\n \u003cp\u003e3 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.958949096880133%\" valign=\"top\"\u003e\n \u003cp\u003e17 (65.4)\u003c/p\u003e\n \u003cp\u003e11 (42.3)\u003c/p\u003e\n \u003cp\u003e2 (7.7)\u003c/p\u003e\n \u003cp\u003e4 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eSLD Steatotic Liver Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"614\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 6\u003c/strong\u003e Toxicity and SLD. Logistic regression (binary univariable)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.97068403908795%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDependent variable: SLD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.24755700325733%\" colspan=\"2\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSLD at anytime\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Baseline + acquired)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.781758957654723%\" colspan=\"2\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSLD at baseline\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCovariable: 1 (reference, presence of each variable analyzed)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.97068403908795%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.127035830618894%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR (95%, CI) Univariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.283387622149837%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.498371335504885%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR (95%, CI) Univariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.120521172638437%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.97068403908795%\" valign=\"top\"\u003e\n \u003cp\u003eGrade 3/4 any type (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.127035830618894%\" valign=\"top\"\u003e\n \u003cp\u003e1.69 (0.58 to 4.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.283387622149837%\" valign=\"top\"\u003e\n \u003cp\u003e0.336\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.498371335504885%\" valign=\"top\"\u003e\n \u003cp\u003e0.89 (0.28 to 2.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.120521172638437%\" valign=\"top\"\u003e\n \u003cp\u003e0.851\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.97068403908795%\" valign=\"top\"\u003e\n \u003cp\u003eNeutropenia any grade (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.127035830618894%\" valign=\"top\"\u003e\n \u003cp\u003e6.62 (1.31 to 33.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.283387622149837%\" valign=\"top\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.498371335504885%\" valign=\"top\"\u003e\n \u003cp\u003e3.83 (0.46 to 32.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.120521172638437%\" valign=\"top\"\u003e\n \u003cp\u003e0.215\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.97068403908795%\" valign=\"top\"\u003e\n \u003cp\u003eNeutropenia grade 3/4 (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.127035830618894%\" valign=\"top\"\u003e\n \u003cp\u003e1.31 (0.49 to 3.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.283387622149837%\" valign=\"top\"\u003e\n \u003cp\u003e0.589\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.498371335504885%\" valign=\"top\"\u003e\n \u003cp\u003e0.69 (0.24 to 2.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.120521172638437%\" valign=\"top\"\u003e\n \u003cp\u003e0.500\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.97068403908795%\" valign=\"top\"\u003e\n \u003cp\u003eTransaminitis (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.127035830618894%\" valign=\"top\"\u003e\n \u003cp\u003e1.40 (0.43 to 4.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.283387622149837%\" valign=\"top\"\u003e\n \u003cp\u003e0.575\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.498371335504885%\" valign=\"top\"\u003e\n \u003cp\u003e1.06 (0.30 to 3.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.120521172638437%\" valign=\"top\"\u003e\n \u003cp\u003e0.928\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.97068403908795%\" valign=\"top\"\u003e\n \u003cp\u003eDose reductions (yes vs no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.127035830618894%\" valign=\"top\"\u003e\n \u003cp\u003e1.84 (0.77 to 4.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.283387622149837%\" valign=\"top\"\u003e\n \u003cp\u003e0.170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.498371335504885%\" valign=\"top\"\u003e\n \u003cp\u003e1.50 (0.56 to 4.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.120521172638437%\" valign=\"top\"\u003e\n \u003cp\u003e0.420\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eSLD Steatotic Liver Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eSLD vs HSI model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCohen\u0026apos;s kappa coefficient, used to assess the agreement level of SLD diagnosis between LAI in CT scans and the HSI model, was calculated as 0.253 (p 0.017), indicating fair agreement. The sensitivity was determined to be 76%, while the specificity was 49%.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study represents a comprehensive analysis of SLD presence and its impact in HR\u0026thinsp;+\u0026thinsp;HER2- metastatic breast cancer treated with CDK4/6i in combination with ET. Notably, we found that 27.6% of our patients had SLD at baseline, and 57.5% had SLD at any time during their treatment. This prevalence is almost double the general population, where SLD affects up to 30% of adults and similar in early stages of breast cancer [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Consistent with findings in the general population, the presence of SLD at baseline in our study was quantitatively associated with factors such as age\u0026thinsp;\u0026gt;\u0026thinsp;65, post-menopausal status, and other comorbidities such as DM or smoking.\u003c/p\u003e \u003cp\u003eVisceral obesity has been associated with to worse metastasis-free survival in early stages breast cancer, but conflicting results have emerged regarding prognosis and treatment response in the advanced setting [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. There is limited data regarding to HR\u0026thinsp;+\u0026thinsp;HER2- metastatic breast cancer; however, some studies have explored the association between BMI or body composition and outcomes. Retrospective data have yield conflicting findings related to BMI and ET monotherapy in first line. While studies with fulvestrant have shown both positive and negative associations, data with aromatase inhibitors show no associations [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan additionalcitationids=\"CR45\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. More recently evidence on current standard first line treatment, suggests that overweight patients with metastatic breast cancer may derive greater benefit in progression-free survival (PFS) from the addition of CDK4/6i to ET [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. However, neutral findings have also been reported, such as in the pool analysis of trials MONARCH-2 and 3 with abemaciclib, which found no difference in PFS across different BMI categories [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe above results only assessed associations with BMI. CT scans offer more precise information for assessing body composition, particularly visceral adipose tissue (VAT) and SLD. Studies have shown greater consistency in assessment of VAT with CT scans and associations with treatment response compared to BMI although the data are also retrospective. Studies by Y\u0026uuml;cel, K. B et al [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] and Franzoi et al [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] have demonstrated that a higher VAT index is associated with longer PFS in patients treated with CDK 4/6i. Specifically, Y\u0026uuml;cel reported a PFS of 20.4 vs 9.3 months (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.033) and Franzoi found a PFS of 20.8 vs 10.4 months (HR: 0.40; 95% CI 0.16\u0026ndash;0.99 \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.041). Additionally, Kripa et al [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] observed that a favorable response to therapy correlated with higher VAT value. However, there are conflicting findings regarding the changes in visceral fat during treatment. Franzoi et al. noted no significant changes in body composition throughout the treatment period, whereas Y\u0026uuml;cel, K. B et al observed a statistically significant decrease in VAT at 6 months, suggesting an antiadipogenic effect of CDK4/6i. Our study demonstrated that the presence of SLD at any time was significantly associated with longer TTF. These outcomes were also superior in patients who only had SLD at baseline although the differences were not statistically significant, possibly due to low power. In relation to the evolution of SLD during treatment, our findings indicate that while a significant portion of patients who had SLD before treatment retained it (54.2%), a considerable percentage of those who did not have SLD at baseline acquired it during treatment (41.3%), with a substantial proportion maintaining it until the last follow up (42.3%).\u003c/p\u003e \u003cp\u003eOur findings may suggest survivor treatment bias, wherein disease with more favourable biology and thereby improved outcomes results in prolonged exposure to ET and CDK4/6i which in turn leads to more opportunity to observe SLD (i.e. a form of immortal time bias). Alternatively, it could indicate these groups represent distinct populations with different molecular pathways, resulting in variations in treatment, prognosis, and metabolic dysregulation. Importantly, the median time to develop SLD in the acquired group was 313 days, and the group that never developed it had a treatment duration longer than this, which argues against the survivor treatment bias hypothesis. The alternative hypothesis suggests there could be a different metabolic pathway could enhance sensitivity and prolong the response to CDK4/6i treatment. However, it may also induce adverse metabolic effects, such as increased lipid synthesis, as observed in preclinical models. For instance, emerging research indicates that E2F1 acts as a regulator of metabolism [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], SIRT6 is implicated in MASLD [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e], and RB1 deficiency induces mitochondrial oxidative phosphorylation in breast cancer [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDue to the dual role of this molecular pathway, CDK4/6i are also being tested in diet-induced obesity (DIO) [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. However, our study also shows that a high percentage of patients undergoing treatment maintain or even acquire SLD. This is significant concerning long-term cardiovascular and hepatic risks and the potential conditioning of future treatments in advanced disease, which also can produce metabolic toxicity (e.g. hyperglycemia with phosphatidylinositol 3-kinase (PI3K) inhibitors). Furthermore, CDK4/6i have recently become part of the standard adjuvant treatment in early-stage high-risk patients, exposing more patients with curative intent to potential long-term effects, which is particularly important for individualized decision-making. Reassuringly, data in early stage breast cancer with higher BMI, for example, with palbociclib in PALLAS study, did not show an increase in short-term toxicity such as neutropenia [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Further studies are warranted to establish correlations between metabolic changes and clinical and molecular data to better characterize these pathways and a more comprehensive understanding of the long-term consequences. This could pave the way for a holistic therapeutic approach incorporating physical exercise, dietary modifications, or pharmacological interventions alongside CDK4/6i. If these pathways are shared, such interventions could not only synergistically improve cancer outcomes but also mitigate metabolic consequences, reduce cardiovascular risks, and enhance patients' functional reserves for future lines of therapy.\u003c/p\u003e \u003cp\u003eThere are important limitations in our study in addition to the biases discussed above. First, it is a retrospective single-centre study with patients predominantly receiving palbociclib. Results may not be generalizable to other CDK4/6i. Second, the gold standard to evaluate SLD with imaging is MRI or US, but we used CT scans due to their widespread availability and utilization as the standard response assessment in metastatic breast cancer. Although CT scans may have a limited accuracy in detecting mild steatosis, they exhibit high specificity (nearly 100%) and sensitivity (75\u0026ndash;80%) in diagnosing moderate to severe cases [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. A notable strength of our study is the regular assessment of SLD status during each re-staging CT scan. Finally, the shorter follow-up period may be insufficient to evaluate the impact on OS and subsequent treatment lines adequately. An update on these outcomes with longer follow-up may be warranted.\u003c/p\u003e \u003cp\u003eIn summary, this analysis reveals a high incidence and prevalence of SLD in HR\u0026thinsp;+\u0026thinsp;HER2- metastatic breast cancer undergoing treatment with CDK4/6i with ET. These findings are consistent with previous reports in other breast cancer settings. A positive association was observed between the presence of SLD and longer TTF. This observation may suggest that these patients represent distinct populations with increased sensitivity to treatment with CDK4/6i and better outcomes, although accompanied by adverse metabolic alterations, particularly in lipid synthesis. If substantiated, this hypothesis underscores the potential for a synergistic therapeutic approach integrating CDK4/6i with interventions such as physical exercise, dietary modifications, or pharmacological strategies. Such a comprehensive approach could not only enhance cancer treatment outcomes but also ameliorate harmful metabolic changes, and mitigate associated health risks, including cardiovascular complications.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors would like to acknowledge all the women who participated in this study. The authors are solely responsible for the design of the study, data collection, the analysis or interpretation of the data, the writing of the article, or the decision to submit for publication. This project represents independent research. We extend our gratitude to the Hold\u0026apos;em for Life Oncology Fellowships at the University of Toronto\u0026apos;s Temerty Faculty of Medicine for supporting Dr. Diego Malon as a Clinical Fellow, enabling this work to be carried out.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDiego Malon, MD (Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Software; Writing\u0026mdash;original draft; review \u0026amp; editing; Funding acquisition), Consolacion Molto, MD, PhD (Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Software; review \u0026amp; editing), Shopnil Prasla, MD (Investigation; Methodology; Software; Supervision; review \u0026amp; editing), Danielle Cuthbert, MD (Writing\u0026mdash; review \u0026amp; editing), Neha Pathak, MD (Writing\u0026mdash;review \u0026amp; editing), Yael Berner-Wygoda, MD (Writing\u0026mdash;review \u0026amp; editing), Massimo Di lorio, MD (Writing\u0026mdash;review \u0026amp; editing), Meredith Li, MD (Writing\u0026mdash;review \u0026amp; editing), Jacqueline Savill, NP (Writing\u0026mdash;review \u0026amp; editing), Abhenil Mittal, MD (Writing\u0026mdash;review \u0026amp; editing), Eitan Amir, MD, PhD (Formal analysis; Investigation; Methodology; Resources, Software; Supervision; Writing\u0026mdash; review \u0026amp; \u0026nbsp; editing), Kartik Jhaveri, MD (Investigation; Methodology; Software; Supervision; Writing\u0026mdash;review \u0026amp; editing), Michelle B. Nadler, MD (Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Software; Supervision; Writing\u0026mdash;original draft; review \u0026amp; editing; Funding acquisition). All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDr. Diego Malon was supported as a clinical Fellow by Hold\u0026apos;em for Life Oncology Fellowships at the University of Toronto\u0026rsquo;s Temerty Faculty of Medicine.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data described in the manuscript were stored in a coded data extraction spreadsheet on a password-protected computer, in accordance with the research ethics approval. The study data will be retained for auditing purposes for 10 years after the study\u0026apos;s completion and will be made available upon reasonable request through written proposals to the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDr. Diego Malon reports honoraria/speaking fee from Bristol Meyers Squibb. Dr. Consolacion Molto reports honoraria/speaking fees from AstraZeneca and Merck. Dr. Eitan Amir reports honoraria/consulting or Advisory role fees from Seagen, Gilead, AstraZeneca and Novartis. Dr. Nadler reports speaker honorarium and consulting fees from Novartis and Exact Sciences. All of them outside of the scope of this submitted work. No Conflict of Interest for Shopnil Prasla, Danielle Cuthbert, Neha Pathak, Yael Berner-Wygoda, Massimo Di lorio, Meredith Li, Jacqueline Savill, Abhenil Mittal and Kartik Jhaveri.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study was performed in line with the principles of the Declaration of Helsinki and The University Health Network Research Ethics Board approval was obtained (approval number 22-5856).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDue to the characteristics of the study written informed consent of the participants is not required. A waiver of consent will not adversely affect the rights and welfare of the subjects. This research will not affect clinical care of the individuals.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePiezzo M, Chiodini P, Riemma M, Cocco S, Caputo R, Cianniello D, Di Gioia G, Di Lauro V, Rella FD, Fusco G, Iodice G, Nuzzo F, Pacilio C, Pensabene M, Laurentiis MD (2020) Progression-Free Survival and Overall Survival of CDK 4/6 Inhibitors Plus Endocrine Therapy in Metastatic Breast Cancer: A Systematic Review and Meta-Analysis. International Journal of Molecular Sciences 21(17): 6400. https://doi.org/10.3390/ijms21176400 \u003c/li\u003e\n\u003cli\u003eHortobagyi GN, Stemmer SM, Burris HA, Yap YS, Sonke GS, Hart L, Campone M, Petrakova K, Winer E P, Janni W, Conte P, Cameron DA, Andr\u0026eacute; F, Arteaga CL, Zarate JP, Chakravartty A, Taran T, Le Gac F, Serra P, O\u0026rsquo;Shaughnessy J (2022) Overall Survival with Ribociclib plus Letrozole in Advanced Breast Cancer. 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Oncotarget 8(40): 69025-69037. https://doi.org/10.18632/oncotarget.16982\u003c/li\u003e\n\u003cli\u003ePatel R, Li Z, Zimmerman BS, Fink MY, Wells JD, Zhou X, Ayers K, Redfern A, Newman S, Schadt E, Oh WK, Chen R, Tiersten A (2022) Impact of body mass index on the efficacy of aromatase inhibitors in patients with metastatic breast cancer. Breast Cancer Res Treat 192(2): 313-319. https://doi.org/10.1007/s10549-021-06504-0\u003c/li\u003e\n\u003cli\u003eArtac M, Cağlayan D, Ko\u0026ccedil;ak M, Geredeli C, Tatli A, Goksu SS, Araz M (2022) 235P The impact of body mass index (BMI) on the progression-free survival of CDK4/6 inhibitors in metastatic breast cancer patients (MBC). 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Frontiers in Endocrinology 8:311. https://doi.org/10.3389/fendo.2017.00311\u003c/li\u003e\n\u003cli\u003eKim HS, Xiao C, Wang RH, Lahusen T, Xu X., Vassilopoulos A, Vazquez-Ortiz G, Jeong WI, Park O, Ki SH, Gao B, Deng CX (2010) Hepatic-Specific Disruption of SIRT6 in Mice Results in Fatty Liver Formation Due to Enhanced Glycolysis and Triglyceride Synthesis. Cell Metabolism 12(3): 224-236. https://doi.org/10.1016/j.cmet.2010.06.009\u003c/li\u003e\n\u003cli\u003eZacksenhaus E, Shrestha M, Liu JC, Vorobieva I, Chung PED, Ju Y, Nir U. Jiang Z (2017) Mitochondrial OXPHOS Induced by RB1 Deficiency in Breast Cancer: Implications for Anabolic Metabolism, Stemness, and Metastasis. Trends Cancer 3(11): 768-779. https://doi.org/10.1016/j.trecan.2017.09.002\u003c/li\u003e\n\u003cli\u003eBenot-Dominguez R, Cimini A, Barone D, Giordano A, Pentimalli F (2022) The Emerging Role of Cyclin-Dependent Kinase Inhibitors in Treating Diet-Induced Obesity: New Opportunities for Breast and Ovarian Cancers? Cancers 14(11): 2709. https://doi.org/10.3390/cancers14112709\u003c/li\u003e\n\u003cli\u003ePfeiler G, Hlauschek D, Mayer EL, Deutschmann C, Kacerovsky-Strobl S, Martin M, Meisel JL, Zdenkowski N, Loibl S, Balic M, Park H, Prat A, Isaacs C, Bajetta E, Balko JM, Bellet-Ezquerra M, Bliss J, Burstein H, Cardoso F, Gnant M, et al (2023) Impact of BMI in Patients With Early Hormone Receptor-Positive Breast Cancer Receiving Endocrine Therapy With or Without Palbociclib in the PALLAS Trial. J Clin Oncol 41(33): 5118-5130. https://doi.org/10.1200/jco.23.00126 \u003c/li\u003e\n\u003cli\u003eLee SS, Park SH (2014) Radiologic evaluation of nonalcoholic fatty liver disease. World Journal of Gastroenterology 20(23): 7392-7402. https://doi.org/10.3748/wjg.v20.i23.7392\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"breast-cancer-research-and-treatment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"brea","sideBox":"Learn more about [Breast Cancer Research and Treatment](https://www.springer.com/journal/10549)","snPcode":"10549","submissionUrl":"https://submission.nature.com/new-submission/10549/3","title":"Breast Cancer Research and Treatment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Metastatic breast cancer, CDK 4/6 inhibitors, endocrine therapy, SLD, NAFLD, MASLD, computed tomography","lastPublishedDoi":"10.21203/rs.3.rs-4770215/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4770215/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eIn early-stage breast cancer, steatotic liver disease (SLD) is associated with increased recurrence, cardiovascular events, and non-cancer death. Endocrine therapy (ET) increases the risk of SLD. The impact of cyclin-dependent kinases 4/6 inhibitors (CDK4/6i) on SLD and prognostic association in metastatic breast cancer is unknown. We characterized the incidence, prevalence, risk factors, and treatment outcomes of SLD in metastatic HR+/HER2- breast cancer receiving CDK4/6i.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis single institution, retrospective, cohort study included patients with metastatic HR+/HER2- breast cancer receiving first-line ET and CDK4/6i from January 2018 to June 2022. SLD was defined as a Liver Attenuation Index (LAI)\u0026thinsp;\u0026gt;\u0026thinsp;25 HU on contrast-enhanced CT scans and/or \u0026gt;\u0026thinsp;10 HU on plain CT scans. Univariable binary-logistic regression was used to assess associations with SLD. Time to treatment failure (TTF) and overall survival (OS) were analyzed using Cox proportional hazards modeling.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong 87 patients with a median age of 58 years and 65.5% postmenopausal, 50 (57.5%) had SLD at anytime (24 at baseline, 26 acquired). SLD at baseline was quantitatively but not statistically associated with age\u0026thinsp;\u0026gt;\u0026thinsp;65, post-menopausal status, diabetes, smoking, and HER2-low status. SLD at anytime was statistically significantly associated with longer TTF (median 470 vs 830.5 days, HR\u0026thinsp;=\u0026thinsp;0.38, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). No significant differences in OS or grade 3/4 adverse events were observed between groups.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study demonstrated a high prevalence of SLD in this population, with SLD presence associated with longer TTF. SLD may be an indicator of better outcomes in metastatic HR+/HER2- breast cancer patients treated with CDK4/6i.\u003c/p\u003e","manuscriptTitle":"Steatotic liver disease in metastatic breast cancer treated with endocrine therapy and CDK4/6 inhibitor","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-18 23:22:51","doi":"10.21203/rs.3.rs-4770215/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-24T02:36:04+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-23T19:26:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-19T18:30:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-14T20:33:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"171340131802746559361207416327411502609","date":"2024-08-14T12:30:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"150206786882093391029166965989101189954","date":"2024-08-14T12:19:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"143288225901998583511012817625747755162","date":"2024-08-13T17:52:53+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-13T11:38:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"105528828140027259274287725387024022391","date":"2024-08-13T01:46:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"274221307403707973447294970666546352763","date":"2024-08-12T07:32:08+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-12T07:24:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-20T05:58:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-20T05:57:17+00:00","index":"","fulltext":""},{"type":"submitted","content":"Breast Cancer Research and Treatment","date":"2024-07-19T21:21:51+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"breast-cancer-research-and-treatment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"brea","sideBox":"Learn more about [Breast Cancer Research and Treatment](https://www.springer.com/journal/10549)","snPcode":"10549","submissionUrl":"https://submission.nature.com/new-submission/10549/3","title":"Breast Cancer Research and Treatment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"da142ad5-d810-4e36-ad66-c48ecdffd266","owner":[],"postedDate":"August 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-30T16:05:33+00:00","versionOfRecord":{"articleIdentity":"rs-4770215","link":"https://doi.org/10.1007/s10549-024-07578-2","journal":{"identity":"breast-cancer-research-and-treatment","isVorOnly":false,"title":"Breast Cancer Research and Treatment"},"publishedOn":"2024-12-25 15:57:47","publishedOnDateReadable":"December 25th, 2024"},"versionCreatedAt":"2024-08-18 23:22:51","video":"","vorDoi":"10.1007/s10549-024-07578-2","vorDoiUrl":"https://doi.org/10.1007/s10549-024-07578-2","workflowStages":[]},"version":"v1","identity":"rs-4770215","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4770215","identity":"rs-4770215","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}