Body composition measures as a determinant of Alpelisib related toxicity

Body composition measures as a determinant of Alpelisib related toxicity | 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 Body composition measures as a determinant of Alpelisib related toxicity Eliya Shachar, Ari Raphael, Uriel Katz, Rivka Kessner, Shlomit Strulov Shachar This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3865840/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 07 Apr, 2024 Read the published version in Breast Cancer Research and Treatment → Version 1 posted 7 You are reading this latest preprint version Abstract Background Body composition has emerged as an important prognostic factor in patients treated with cancer. Severe depletion of skeletal muscle, sarcopenia, has been associated with poor performance status and worse oncological outcomes. We studied patients with metastatic breast cancer receiving alpelisib, to determine if sarcopenia and additional body composition measures accounting for muscle and adiposity are associated with toxicity. Methods A retrospective observational analysis was conducted, including 38 women with metastatic breast cancer and a PIK3CA mutation, treated with alpelisib as advanced line of therapy. Sarcopenia was determined by measuring skeletal muscle cross-sectional area at the third lumbar vertebra using computerized tomography. Various body composition metrics were assessed along with drug toxicity, dose reductions, treatment discontinuation, and hospitalizations. Results Sarcopenia was observed in half of the patients (n = 19, 50%), spanning normal weight, overweight, and obese individuals. Among the body composition measures, lower skeletal muscle density (SMD) was associated with an increased risk of treatment-related hyperglycaemia (P = 0.03). Additionally, lower visceral adipose tissue (VAT) was associated with alpelisib-induced rash (P = 0.04) and hospitalizations (P = 0.04). Notably, alpelisib treatment discontinuation was not impacted by alpelisib toxicity. Conclusion Body composition measures, specifically SMD and VAT may provide an opportunity to identify patients at higher risk for severe alpelisib related hyperglycemia, and cutaneous toxicity. These findings suggest the potential use of body composition assessment to predict toxicity, allowing for personalized therapeutic observation and intervention. metastatic breast cancer sarcopenia muscle attenuation skeletal muscle index skeletal muscle gauge toxicity survival alpelisib hyperglycemia adipose tissue Figures Figure 1 Introduction Breast cancer is the most commonly diagnosed malignancy among women in the United States, excluding nonmelanoma of the skin, and the second leading cause of cancer death in women, after lung cancer. 1 Hormone receptor positive (HR+), human epidermal growth factor receptor-2–negative (HER2–) breast cancer subtype, comprises more than 70% of metastatic breast cancers (MBC). 2,3 The 5-year relative survival of patients diagnosed with metastatic disease from 2012–2018 was 29%. 1 First‐line treatment of patients with HR + HER2– MBC, includes endocrine therapy (ET) combined with a cyclin‐dependent kinase 4/6 inhibitor (CDK4/6i). However, acquired resistance to ET presents a great challenge. 4 Fourty-percent of patients with HR + HER2- breast cancer harbor activating mutations in the PIK3CA gene, inducing hyperactivation of the alpha-isoform (p110α) of phosphatidylinositol 3-kinase (PI3K). 5 Alpelisib is an oral small-molecule, α-specific PI3K inhibitor, which selectively inhibits the p110α with greater efficacy than other isoforms. 6 The SOLAR1 phase 3 randomized double-blind trial led to the FDA approval of alpelisib and fulvestrant, demonstrating prolonged progression-free survival (PFS) among patients with PIK3CA -mutated HR + HER2- MBC, who had received previous endocrine therapy. 7,8 The estimated median PFS in the alpelisib plus fulvestrant arm was 11 months compared with 5.7 months in the placebo plus fulvestrant arm (HR, 0.65; 95% CI, 0.50–0.85; P = 0.001). Nevertheless, alpelisib is associated with frequent adverse events of any grade among patients; high rates of adverse reactions were reported among patients in the SOLAR1 trial, including hyperglycemia (63.7%), diarrhea (57.7%), nausea (44.7%), decreased appetite (35.6%), and rash (35.6%). Alpelisib is given at a fixed dose (300 mg daily) regardless of variables such as adiposity, muscle mass, and sarcopenia. Poor body composition metrics (BCM) have been associated with inferior oncological outcomes in breast cancer. 9 BCM have been shown to predict dose-limiting toxicity (DLT) in patients with metastatic renal cell carcinoma (mRCC) receiving sunitinib. 10 Patients who had a lower skeletal muscle index (SMI) and a lower fat-free mass experienced greater DLT. Patients with low measurements of skeletal muscle mass, experienced significantly greater DLT, demonstrating that sarcopenia in patients with mRCC is a significant predictor of DLT among patients treated with sunitinib. Low overall lean body mass (LBM) has been related to toxicity and survival. 11,12 More research is necessary examining the potential use of BCM to predict treatment toxicity and outcomes among various cancer therapies. We investigated the association of BCM, including muscle and adipose tissue, with drug adverse events (AE) among patients treated with alpelisib and PIK3CA mutated HR + HER2- MBC. Methods Participants : This single center retrospective analysis included patients with HR + HER2- MBC harboring a mutation in the PIK3CA gene and treated with alpelisib at Tel Aviv Medical Center (TAMC) between 10.2015–7.2023. Eligible patients were females, 21 years of age and older, Eastern cooperative Oncology Group performance status (ECOG PS) 0–3, 13 with a baseline abdominal CT scan dating no more than 30 days prior to therapy initiation, digital images available for muscle mass assessment, and complete electronic medical records. Patient data was extracted and collected from the institutional electronic database. The study was approved by the TAMC Institutional Review Board (Helsinki ethics approval number 0611-21-TLV(. Toxicity grading measures : Patient demographics and AE were extracted from the electronic medical records. Grading severity was scaled according to the toxicity grades 1–5 of National Cancer Institute Common Toxicity Criteria for adverse events (NCI- CTCAE, Version 4.03). 14 We limited our review of adverse effects based on the commonly reported events in the literature including hyperglycemia, rash, gastrointestinal toxicity (diarrhea, nausea, abdominal pain, stomatitis, vomiting), neurotoxicity, gastrointestinal toxicity (stomatitis, diarrhea, vomiting), dose reductions, treatment delays, hospitalizations due to treatment toxicity, and death. We measured an additional parameter, "Other toxicity", which we defined as a measure of heightened toxicity, including dose reduction, treatment delay, toxicity grade ≥ 3, and hospitalizations. Body Composition Analysis: Measures of body composition were evaluated including body surface area (BSA), and body mass index (BMI). BMI was calculated using the following formula: BMI = weight (kg) / height 2 (m 2 ). 15,16 Obese was classified as patients with a BMI ≥ 30.0 kg/m 2 . BSA was calculated using the Mosteller formula: BSA (m 2 ) = \(\sqrt{\left[\frac{\text{h}\text{e}\text{i}\text{g}\text{h}\text{t} \left(\text{c}\text{m}\right) \text{X} \text{w}\text{e}\text{i}\text{g}\text{h}\text{t} \left(\text{k}\text{g}\right)}{3600}\right]}\) . 17 CT-computed body composition measures Abdominal CT images were acquired from the TAMC Picture Archiving and Communication System (of Philips Algotec, Ra'anana, Israel) and analyses were conducted with the guidance of a radiologist. Axial plane CT images at the level of third lumbar vertebrae (L3) were evaluated. L3 lumbar segments were processed using automated image segmentation software sliceOmatic – CANADA. 18,19 The software recognizes muscle tissue based on density threshold between − 29 and + 150 Housfield units (HU), while using a priori information about the L3 muscle shape to avoid mislabeling parts of the neighboring organs that also have HU values in the − 29 + 150 range. Cross-sectional areas (cm 2 ) of the sum of all L3 regional muscles (psoas, paraspinal, and abdominal wall muscles) were computed for each image, and the average value for the two images was calculated for each patient. The program provides a highly accurate estimation of the cross-sectional lean tissue area and skeletal muscle area. Sarcopenia, a decrease in skeletal muscle index (in women < 38cm 2 /m 2 ), was previously defined in an Asian population using reported cut-off values. 20 These values were chosen as they have been most extensively investigated, while other cutoffs have been reflective of Western populations. 21 For women of the study population, sarcopenia was defined by skeletal muscle index (SMI). SMI was calculated using the following formula: (L3-muscle area-cm 2 )/(patient height-m 2 ). An SMI of < 38 was considered sarcopenic, based on previously derived optimal stratification statistics correlating SMI to increased mortality in a large population of patients with colorectal and lung cancer. Estimation of lean body mass (LBM) was calculated using the formula described by Mourtzakis et al. (LBM (kg) = [(L3 muscle measured by CT (cm 2 ) × 0.3) + 6.06]). 22,23 Mean skeletal muscle density (SMD) was derived by averaging Hounsfield Units (HU) of skeletal muscle at the level of L3 vertebrae. The attenuation measurement of skeletal muscle is used as a non-invasive radiological technique to indirectly assess muscle fat content. The density of skeletal muscle is inversely related to muscle fat content. 24 Since SMI and SMD are each significantly associated with outcome, 25–27 we explored whether combining the two skeletal muscle measures, may provide a stronger correlation with outcome and toxicity. To integrate both SMI and SMD, we evaluated patient skeletal muscle gauge (SMG), which was calculated by multiplying SMI x SMD, as first presented by Weinberg et al . The units for SMG are: (cm^2 tissue * average HU)/(m^2 height) for simplicity we chose to represent them as arbitrary units (AU). 28 Subcutaneous adipose tissue (SAT) area was calculated from extramuscular tissue with density between − 190 and − 30 HU and visceral adipose tissue (VAT) from non-subcutaneous tissue with density between − 150 and − 50 HU. Oncological measures: Furthermore, we also collected additional oncological parameters including patient age at diagnosis with metastatic disease and lines of prior therapies. Time to treatment failure and overall survival were not assessed, as patients received alpelisib at various lines of treatment, potentially obscuring the analysis. Statistical analysis : Data that met the normal distribution assumptions, confirmed by the Kolmogorov–Smirnov test and histogram underwent parametric testing using the two-group t-test and were presented as mean ± standard deviation. For data that did not adhere to a normal distribution, nonparametric tests were employed, specifically the Mann–Whitney U-test, with results reported as median (IQR), or the Fisher's exact test when appropriate. A binary logistic regression model was used to estimate the Odds ratio. A P-value of less than 0.05 was deemed statistically significant. All statistical evaluations were conducted using IBM SPSS version 29.0.1 Results Patient characteristics and body composition Thirty-eight patients diagnosed with HR+ HER2- MBC and a PIK3CA mutation, treated with alpelisib at TAMC between 10.2015-7.2023, met eligibility criteria and were included in the analysis. Patient clinical characteristics, body composition measures and toxicity outcomes are described in Table 1. The median age was 70 years (interquartile range [IQR], 57-78). Approximately half of the women (n=20, 52.6%) were treated with alpelisib up to third line or below, 18 (47.4%) patients received alpelisib as fourth or greater line of treatment, with a median of 3 prior lines of therapy (IQR, 2-4). Patient mean weight was 60.2 kg (standard deviation [SD] ±13.5). Median BMI was 22 kg/m 2 (IQR, 20.3-26.1), and among the study population, 10 (26.3%) patients were obese. Median BSA was 1.58 m 2 (IQR, 1.5-1.7). CT-based body composition indices were available and calculated for all patients. Patient median SMI was 35.8 cm 2 /m 2 (IQR, 31.2-43.4) as demonstrated in Figure 1, and a median SMG of 1142 AU (IQR, 935-1511). Patient median LBM was 34.4 kg (IQR, 31-37.1). The mean SMA was 87.94 cm 2 ±29.6 [SD]), and SMD was 31.96 HU. Half of the patients were sarcopenic, (n=19, 50%). The study population PIK3CA mutations are presented in Supplementary Table 1. Toxicity outcomes Among the study population, almost half of the patients had a dose reduction of alpelisib (16, 42.1%), and 26 patients (68.4%) a dose interruption of therapy (Table 1). A minority were hospitalized resulting from toxicity of the treatment (n=6, 16%). Only 3 (8%) patients did not experience any AE. The majority of patients encountered AE grade ≥2 (n=31, 81.6%) and 15 women (39.5%) suffered from grade ≥3 AE. Body composition as a predictor of increased alpelisib toxicity Among women with grade ≥2 AE, age, treatment line, ECOG PS, sarcopenia (SMI<38, and SMI teritial divisions), SMG, and LBM tertials did not provide additional measures in determining the likelihood of increased drug toxicity (gastrointestinal, haematological, hyperglycaemia, and rash), hospitalizations, dose reductions and interruptions of alpelisib, as demonstrated in Supplementary Table 2. Patients with a lower tertial SMG were likely to have increased risk of Other toxicity, (22.6%, the upper two thirds which were 3.2%, and 6.5%, respectively, P=0.02). When evaluating each toxicity independently, age, ECOG, dose reductions and body composition measures (including BMI, BSA, VAT, SAT , SMA , SMI, SMG), they were not associated with increased toxicity from alpelisib (Table 2). Risk of hyperglycemia was associated with lower mean VAT (40 ± 32.8 [SD] cm 2 vs. 103.3 ± 57.7 [SD] cm 2 , P=0.023), mean SAT (100.8±74.6 [SD] cm 2 vs. 183.4 ± 66.5 [SD] cm 2 , P=0.016), mean SMD (41.6 ± 11.6 [SD] HU vs. 29.6 ± 9.2 [SD] HU, P=0.015), median VAT density, -76.36 HU(IQR, -85.31, -60.27) vs. -91 HU(IQR, -98.79, -81.14, P=0.009), and median SAT density (-83.23 HU (IQR,-97.78, -81.28) vs. -101 HU (IQR, -105.2, -94.12), P=0.021). The risk of hyperglycaemia grade ≥1 was not associated with age, BMI, BSA, height, SMI, SMG, and LBM. Among the body composition measures, mean SMD was associated with grade ≥2 hyperglycemia, (38 ± 9.6 [SD] HU vs. 28.9 ± 9.7 [SD] HU, P=0.024). Median VAT was marginally associated with grade ≥2 hyperglycemia, -79.69 HU (IQR, -92.9, -75.26) vs. -91 HU (IQR, -98.79, -83.14), P=0.05). Rash grade ≥2 was associated with lower median VAT (-88.35 HU (IQR, -94.43, -78.22) vs. -97.8 HU (IQR, -172, -89.85), P=0.043). While grade ≥2 rash, was associated with an increased hospitalization (8% of patients hospitalized with a rash vs. 75.7% of patients who were not hospitalized and without a rash, P=0.042). Among patients with Other toxicity, they had a higher risk of developing grade ≥2 hyperglycaemia (OR=9.58, P=0.01). None of the body composition metrics were found to be significantly associated with an increased likelihood of having hematological, and gastrointestinal toxicity. Among the population of patients with sarcopenia (SMI<38) who were overweight or obese, 8 (23%) women experienced any toxicity grade ≥2, 21% hyperglycemia grade ≥2, 16% had a dose reduction or delay, 21% experienced Other toxicity, while none were hospitalized or experienced rash (grade ≥2). Discussion To our knowledge, this is the first report of the impact of body composition measures on alpelisib toxicity and adherence to therapy. Body composition measures were useful in predicting alpelisib induced hyperglycemia and rash. Other AE were not associated with body metrics. This work demonstrates body composition parameters that may be integrated to identify patients with greater likelihood to develop treatment related toxicities beyond the conventional measures of BMI and BSA, and tailor observation. Among the body composition measures, mean skeletal muscle density (SMD) was predictive of grade ≥2 hyperglycemia, thus women with lower SMD were at increased risk of developing treatment induced hyperglycemia. Additionally, there was a trend seen among women with lower mean visceral adipose tissue (VAT), who were more likely to develop grade ≥2 hyperglycemia. These measures, SMD and VAT may identify a patient population necessitating a more tailored treatment approach and observation, managing glucose control at lower grades and possibly earlier intervention. Women treated with alpelisib who developed a rash grade ≥2, had lower mean visceral adipose tissue, and greater likelihood of hospitalizations. Interestingly half of the study population were deemed sarcopenic, irrespective of BMI. Additionally, we did not find patient BMI, those who were overweight or obese, or age to be risk factors for treatment toxicity. Limitation of this study stem from the study design, a retrospective observational analysis of a small heterogeneous population, which may influence the external validity of the results. Additional, alpelisib was administered as an advanced line of therapy, 47% were treated as fourth or greater line, limiting the analysis of time to treatment failure and overall survival. Given the variability in the correlations between BMI and clinical outcomes in patients with breast cancer, assessment of body composition through distinct body compartments, such as muscle, and fat, separately has evolved as a potentially more informative approach. Our findings suggest that among the toxicities of alpelisib, hyperglycemia and rash were associated with lower SMD and VAT. These results raise the option to identify patients at higher risk for severe side effects, potentially guiding a more personalized approach for these patients. Future prospective studies may determine optimal interventions to mitigate toxicity for this risk group. Table 1. Patient characteristics , body composition measures and toxicity outcomes Variables N= 38 Age, mean ± SD , years 68 (14.6) Age, median (IQR) years 70 (57-77.5) Female, n (%) 38 (100) ECOG n , (%) 0 8 (32) 1 10 (40) 2 5 (20) 3 2 (8) Alpelisib treatment line n, (%) ≤ 3 20 (52.6) ≥4 18 (47.4) Alpelisib mean treatment line 3.8 Alpelisib median treatment line (IQR) 3 (2-4) Weight, mean ± SD, kg 60.2 (13.5) BMI, mean ± SD 23.87 (5.9) BMI median (IQR) , kg/m 2 22 (20.3-26.1) BMI category , n (%) Healthy weight 22 (57.9) Overweight 6 (15.8) Obese 10 (26.3) BSA, mean ± SD 1.63 (0.18) BSA median (IQR) 1.58 (1.5-1.7) SMI, median (IQR), cm 2 /m 2 35.8 (31.2-43.4) SMG, median (IQR), AU 1142 (935-1511) LBM, kg, mean ± SD 32.4428 (8.89) LBM, kg median (IQR) 34.4 (31-37.1) SMA, mean ± SD , cm 2 87.94 (29.6) SMD , HU 31.96 (10.5) Sarcopenic <38 n (%) Yes 19 (5 0 ) Dose reduction Yes 16 (4 2 .1) Dose interruption Yes 26 ( 68 .4) Hospitalizations due to drug, number (%) Yes (%) 6 (16) AE G rade ≥2 AE Yes 31 (81.6) G rade ≥3 AE Yes 15 ( 39 .5) Abbreviations: IQR = interquartile range, SD = standard deviation; Plus–minus values are means ±SD; BMI = body mass index BMI-Healthy <25 kg/m 2 ; overweight 25-30 kg/m 2 ; obese, ≥30 kg/m 2 AE = adverse event, AU = arbitrary units, BSA=body surface area , SMI= skeletal muscle index, Defined as SMI<38cm 2 /m 2 SMD- skeletal muscle density was derived by averaging Hounsfield Units (HU) of skeletal muscle at the L3 vertebrae. SMG- skeletal muscle gauge was calculated by multiplying SMI x SMD; the units for SMG are: (cm^2 tissue * average HU)/(m^2 height) for simplicity we chose to represent them as arbitrary units (AU) LMB- lean body mass (kg) = 0·30 × [skeletal muscle at L3 using CT (cm 2 )] + 6·06] SMA - skeletal muscle area (cm 2 ) Table 2. Body metric parameters predictive of independent toxicities Hyperglycaemia G ≥ 1 P-value Hyperglycaemia G ≥2 P-value Rash G ≥1 P-value Rash G ≥2 P-value Age 0.785 0.105 0.256 0.312 BMI 0.157 0.143 0.170 0.207 BSA 0.400 0.363 0.283 0.058 VAT, cm 2 0.023* 0.082 0.227 0.102 VAT, HU 0.009* 0.051** 0.020* 0.043* SAT, cm 2 0.016* 0.204 0.145 0.164 SAT, HU 0.021* 0.361 0.907 1 SMD, HU 0.015* 0.024* 0.792 0.442 SMA, cm 2 0.085 0.315 0.135 0.161 IMAT, HU 0.125 0.547 0.868 0.680 SMI, cm 2 /m 2 0.125 0.058 0.149 SMG, AU 0.404 0.439 0.823 0.527 Dose reduction 0.340 0.153 0.134 0.133 Hospitalizations 0.564 0.303 0.335 0.042* LBM 0.73 0.165 0.48 0.86 Abbreviations: VAT – visceral adipose tissue , SAT- subcutaneous adipose tissue, IMAT- intramuscular adipose tissue P-value indicates statistical significance in the comparison of mean body metric compositions between groups that possess these characteristics and those that do not. *statistically significant P<0.05 , **marginally significant Abbreviations IQR interquartile range, SD = standard deviation Plus–minus values are means ± SD BMI body mass index Declarations Funding: This work was supported by the Conquer Cancer-Israel Cancer Research Fund Career Development Award 2021CC-ICRFCDA-5807223889 Author Contribution E.S. and S.S. wrote the main manuscript text, data analysis, statistical analysisA.R. data analysisU.K. statistical analysis R.K data extractionAll authors reviewed the manuscript. 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Supplementary Files supplementary15.1.24.docx Cite Share Download PDF Status: Published Journal Publication published 07 Apr, 2024 Read the published version in Breast Cancer Research and Treatment → Version 1 posted Editorial decision: Revision requested 14 Feb, 2024 Reviews received at journal 09 Feb, 2024 Reviewers agreed at journal 24 Jan, 2024 Reviewers invited by journal 23 Jan, 2024 Submission checks completed at journal 16 Jan, 2024 Editor assigned by journal 16 Jan, 2024 First submitted to journal 15 Jan, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-3865840","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":267342188,"identity":"2bc8aaed-3363-4db2-8638-d2b53a41c07e","order_by":0,"name":"Eliya Shachar","email":"","orcid":"","institution":"Tel Aviv Sourasky Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Eliya","middleName":"","lastName":"Shachar","suffix":""},{"id":267342189,"identity":"37a1578f-6bb2-4e10-a51f-e5c11a73f3c0","order_by":1,"name":"Ari Raphael","email":"","orcid":"","institution":"Tel Aviv Sourasky Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Ari","middleName":"","lastName":"Raphael","suffix":""},{"id":267342190,"identity":"8cb314bd-768f-48a8-829e-641ca099f882","order_by":2,"name":"Uriel Katz","email":"","orcid":"","institution":"Tel Aviv University","correspondingAuthor":false,"prefix":"","firstName":"Uriel","middleName":"","lastName":"Katz","suffix":""},{"id":267342191,"identity":"88a4801e-51e8-4d38-91c2-c546bd1ca4e9","order_by":3,"name":"Rivka Kessner","email":"","orcid":"","institution":"Tel Aviv Sourasky Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Rivka","middleName":"","lastName":"Kessner","suffix":""},{"id":267342192,"identity":"f8d13a28-894e-435c-9cad-d720c3ffbc8f","order_by":4,"name":"Shlomit Strulov Shachar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIie3RPQrCMBTA8VccXOpeKPRd4Ym7Hb1GQ8CpQ0fHFsEuHqAFD9Gpc0rWHiDg4scBxM3BwXSRIhjaTST/KYT+yEsKYLP9YFhMUgDSq2nqiPd2lHwnpJyOaONK6BEyEK8j3TEe7xEwET/LLip5hljehJzFS8DVnuBkIHhotouYiFVHDnJWc5i3LRkHA8V2viYR+RyashYwL9bRIKIHkyOJk6oJiLsm6HFhfjHFurssWNVy0oS75EohTAQL3lzjZxBi3pxPrF4GmGfZ+bExDPaZSwL6P2hImI773maz2f6/F39nVC3kohSXAAAAAElFTkSuQmCC","orcid":"","institution":"Tel Aviv Sourasky Medical Center","correspondingAuthor":true,"prefix":"","firstName":"Shlomit","middleName":"Strulov","lastName":"Shachar","suffix":""}],"badges":[],"createdAt":"2024-01-15 08:29:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3865840/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3865840/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10549-024-07315-9","type":"published","date":"2024-04-07T15:01:10+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":49762863,"identity":"6a16fe40-4929-4a39-b970-86f6ef321440","added_by":"auto","created_at":"2024-01-17 16:14:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":193623,"visible":true,"origin":"","legend":"\u003cp\u003eExample of sarcopenia, two patients with metastatic breast cancer , Left, normal SMI (43cm\u003csup\u003e2\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e) non sarcopenic; Right, low SMI (\u0026lt;38 cm\u003csup\u003e2\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e) sarcopenic.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3865840/v1/2f00021dc03e466c2a97159e.png"},{"id":54304104,"identity":"8b6b3de3-7be0-4595-9537-8802a71f4aa5","added_by":"auto","created_at":"2024-04-08 15:14:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":645370,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3865840/v1/a987c5bd-80c8-406b-b5eb-3cbcc67c03cf.pdf"},{"id":49762864,"identity":"fc751fcb-fa9e-466f-9043-49612db494a3","added_by":"auto","created_at":"2024-01-17 16:14:46","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":18462,"visible":true,"origin":"","legend":"","description":"","filename":"supplementary15.1.24.docx","url":"https://assets-eu.researchsquare.com/files/rs-3865840/v1/b439f11863a16f987a20ef4f.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Body composition measures as a determinant of Alpelisib related toxicity","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBreast cancer is the most commonly diagnosed malignancy among women in the United States, excluding nonmelanoma of the skin, and the second leading cause of cancer death in women, after lung cancer.\u003csup\u003e1\u003c/sup\u003e Hormone receptor positive (HR+), human epidermal growth factor receptor-2\u0026ndash;negative (HER2\u0026ndash;) breast cancer subtype, comprises more than 70% of metastatic breast cancers (MBC).\u003csup\u003e2,3\u003c/sup\u003e The 5-year relative survival of patients diagnosed with metastatic disease from 2012\u0026ndash;2018 was 29%.\u003csup\u003e1\u003c/sup\u003e First‐line treatment of patients with HR\u0026thinsp;+\u0026thinsp;HER2\u0026ndash; MBC, includes endocrine therapy (ET) combined with a cyclin‐dependent kinase 4/6 inhibitor (CDK4/6i). However, acquired resistance to ET presents a great challenge.\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFourty-percent of patients with HR\u0026thinsp;+\u0026thinsp;HER2- breast cancer harbor activating mutations in the PIK3CA gene, inducing hyperactivation of the alpha-isoform (p110α) of phosphatidylinositol 3-kinase (PI3K).\u003csup\u003e5\u003c/sup\u003e Alpelisib is an oral small-molecule, α-specific PI3K inhibitor, which selectively inhibits the p110α with greater efficacy than other isoforms.\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe SOLAR1 phase 3 randomized double-blind trial led to the FDA approval of alpelisib and fulvestrant, demonstrating prolonged progression-free survival (PFS) among patients with \u003cem\u003ePIK3CA\u003c/em\u003e-mutated HR\u0026thinsp;+\u0026thinsp;HER2- MBC, who had received previous endocrine therapy.\u003csup\u003e7,8\u003c/sup\u003e The estimated median PFS in the alpelisib plus fulvestrant arm was 11 months compared with 5.7 months in the placebo plus fulvestrant arm (HR, 0.65; 95% CI, 0.50\u0026ndash;0.85; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001). Nevertheless, alpelisib is associated with frequent adverse events of any grade among patients; high rates of adverse reactions were reported among patients in the SOLAR1 trial, including hyperglycemia (63.7%), diarrhea (57.7%), nausea (44.7%), decreased appetite (35.6%), and rash (35.6%). Alpelisib is given at a fixed dose (300 mg daily) regardless of variables such as adiposity, muscle mass, and sarcopenia.\u003c/p\u003e \u003cp\u003ePoor body composition metrics (BCM) have been associated with inferior oncological outcomes in breast cancer.\u003csup\u003e9\u003c/sup\u003e BCM have been shown to predict dose-limiting toxicity (DLT) in patients with metastatic renal cell carcinoma (mRCC) receiving sunitinib.\u003csup\u003e10\u003c/sup\u003e Patients who had a lower skeletal muscle index (SMI) and a lower fat-free mass experienced greater DLT. Patients with low measurements of skeletal muscle mass, experienced significantly greater DLT, demonstrating that sarcopenia in patients with mRCC is a significant predictor of DLT among patients treated with sunitinib. Low overall lean body mass (LBM) has been related to toxicity and survival.\u003csup\u003e11,12\u003c/sup\u003e More research is necessary examining the potential use of BCM to predict treatment toxicity and outcomes among various cancer therapies.\u003c/p\u003e \u003cp\u003eWe investigated the association of BCM, including muscle and adipose tissue, with drug adverse events (AE) among patients treated with alpelisib and PIK3CA mutated HR\u0026thinsp;+\u0026thinsp;HER2- MBC.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003eParticipants\u003c/b\u003e:\u003c/h2\u003e \u003cp\u003eThis single center retrospective analysis included patients with HR\u0026thinsp;+\u0026thinsp;HER2- MBC harboring a mutation in the PIK3CA gene and treated with alpelisib at Tel Aviv Medical Center (TAMC) between 10.2015\u0026ndash;7.2023. Eligible patients were females, 21 years of age and older, Eastern cooperative Oncology Group performance status (ECOG PS) 0\u0026ndash;3,\u003csup\u003e13\u003c/sup\u003e with a baseline abdominal CT scan dating no more than 30 days prior to therapy initiation, digital images available for muscle mass assessment, and complete electronic medical records. Patient data was extracted and collected from the institutional electronic database. The study was approved by the TAMC Institutional Review Board (Helsinki ethics approval number 0611-21-TLV(.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003eToxicity grading measures\u003c/b\u003e:\u003c/h2\u003e \u003cp\u003ePatient demographics and AE were extracted from the electronic medical records. Grading severity was scaled according to the toxicity grades 1\u0026ndash;5 of National Cancer Institute Common Toxicity Criteria for adverse events (NCI- CTCAE, Version 4.03).\u003csup\u003e14\u003c/sup\u003e We limited our review of adverse effects based on the commonly reported events in the literature including hyperglycemia, rash, gastrointestinal toxicity (diarrhea, nausea, abdominal pain, stomatitis, vomiting), neurotoxicity, gastrointestinal toxicity (stomatitis, diarrhea, vomiting), dose reductions, treatment delays, hospitalizations due to treatment toxicity, and death. We measured an additional parameter, \"Other toxicity\", which we defined as a measure of heightened toxicity, including dose reduction, treatment delay, toxicity grade\u0026thinsp;\u0026ge;\u0026thinsp;3, and hospitalizations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eBody Composition Analysis:\u003c/h2\u003e \u003cp\u003eMeasures of body composition were evaluated including body surface area (BSA), and body mass index (BMI). BMI was calculated using the following formula: BMI\u0026thinsp;=\u0026thinsp;weight (kg) / height\u003csup\u003e2\u003c/sup\u003e (m\u003csup\u003e2\u003c/sup\u003e).\u003csup\u003e15,16\u003c/sup\u003e Obese was classified as patients with a BMI\u0026thinsp;\u0026ge;\u0026thinsp;30.0 kg/m\u003csup\u003e2\u003c/sup\u003e. BSA was calculated using the Mosteller formula: BSA (m\u003csup\u003e2\u003c/sup\u003e) = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\sqrt{\\left[\\frac{\\text{h}\\text{e}\\text{i}\\text{g}\\text{h}\\text{t} \\left(\\text{c}\\text{m}\\right) \\text{X} \\text{w}\\text{e}\\text{i}\\text{g}\\text{h}\\text{t} \\left(\\text{k}\\text{g}\\right)}{3600}\\right]}\\)\u003c/span\u003e\u003c/span\u003e.\u003csup\u003e17\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCT-computed body composition measures\u003c/strong\u003e \u003cp\u003eAbdominal CT images were acquired from the TAMC Picture Archiving and Communication System (of Philips Algotec, Ra'anana, Israel) and analyses were conducted with the guidance of a radiologist. Axial plane CT images at the level of third lumbar vertebrae (L3) were evaluated. L3 lumbar segments were processed using automated image segmentation software sliceOmatic \u0026ndash; CANADA.\u003csup\u003e18,19\u003c/sup\u003e The software recognizes muscle tissue based on density threshold between \u0026minus;\u0026thinsp;29 and +\u0026thinsp;150 Housfield units (HU), while using \u003cem\u003ea priori\u003c/em\u003e information about the L3 muscle shape to avoid mislabeling parts of the neighboring organs that also have HU values in the \u0026minus;\u0026thinsp;29\u0026thinsp;+\u0026thinsp;150 range. Cross-sectional areas (cm\u003csup\u003e2\u003c/sup\u003e) of the sum of all L3 regional muscles (psoas, paraspinal, and abdominal wall muscles) were computed for each image, and the average value for the two images was calculated for each patient. The program provides a highly accurate estimation of the cross-sectional lean tissue area and skeletal muscle area.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eSarcopenia, a decrease in skeletal muscle index (in women\u0026thinsp;\u0026lt;\u0026thinsp;38cm\u003csup\u003e2\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e), was previously defined in an Asian population using reported cut-off values.\u003csup\u003e20\u003c/sup\u003e These values were chosen as they have been most extensively investigated, while other cutoffs have been reflective of Western populations.\u003csup\u003e21\u003c/sup\u003e For women of the study population, sarcopenia was defined by skeletal muscle index (SMI). SMI was calculated using the following formula: (L3-muscle area-cm\u003csup\u003e2\u003c/sup\u003e)/(patient height-m\u003csup\u003e2\u003c/sup\u003e). An SMI of \u0026lt;\u0026thinsp;38 was considered sarcopenic, based on previously derived optimal stratification statistics correlating SMI to increased mortality in a large population of patients with colorectal and lung cancer. Estimation of lean body mass (LBM) was calculated using the formula described by Mourtzakis et al. (LBM (kg) = [(L3 muscle measured by CT (cm\u003csup\u003e2\u003c/sup\u003e) \u0026times; 0.3)\u0026thinsp;+\u0026thinsp;6.06]).\u003csup\u003e22,23\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eMean skeletal muscle density (SMD) was derived by averaging Hounsfield Units (HU) of skeletal muscle at the level of L3 vertebrae. The attenuation measurement of skeletal muscle is used as a non-invasive radiological technique to indirectly assess muscle fat content. The density of skeletal muscle is inversely related to muscle fat content.\u003csup\u003e24\u003c/sup\u003e Since SMI and SMD are each significantly associated with outcome,\u003csup\u003e25\u0026ndash;27\u003c/sup\u003e we explored whether combining the two skeletal muscle measures, may provide a stronger correlation with outcome and toxicity. To integrate both SMI and SMD, we evaluated patient skeletal muscle gauge (SMG), which was calculated by multiplying SMI x SMD, as first presented by Weinberg \u003cem\u003eet al\u003c/em\u003e. The units for SMG are: (cm^2 tissue * average HU)/(m^2 height) for simplicity we chose to represent them as arbitrary units (AU).\u003csup\u003e28\u003c/sup\u003e Subcutaneous adipose tissue (SAT) area was calculated from extramuscular tissue with density between \u0026minus;\u0026thinsp;190 and \u0026minus;\u0026thinsp;30 HU and visceral adipose tissue (VAT) from non-subcutaneous tissue with density between \u0026minus;\u0026thinsp;150 and \u0026minus;\u0026thinsp;50 HU.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eOncological measures:\u003c/h2\u003e \u003cp\u003eFurthermore, we also collected additional oncological parameters including patient age at diagnosis with metastatic disease and lines of prior therapies. Time to treatment failure and overall survival were not assessed, as patients received alpelisib at various lines of treatment, potentially obscuring the analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003eStatistical analysis\u003c/b\u003e:\u003c/h2\u003e \u003cp\u003eData that met the normal distribution assumptions, confirmed by the Kolmogorov\u0026ndash;Smirnov test and histogram underwent parametric testing using the two-group t-test and were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. For data that did not adhere to a normal distribution, nonparametric tests were employed, specifically the Mann\u0026ndash;Whitney U-test, with results reported as median (IQR), or the Fisher's exact test when appropriate. A binary logistic regression model was used to estimate the Odds ratio. A P-value of less than 0.05 was deemed statistically significant. All statistical evaluations were conducted using IBM SPSS version 29.0.1\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003ePatient characteristics and body composition\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThirty-eight\u0026nbsp;patients diagnosed with HR+ HER2- MBC and a PIK3CA mutation,\u0026nbsp;treated with alpelisib at TAMC between\u0026nbsp;10.2015-7.2023, met eligibility criteria and were included in the analysis. Patient\u0026nbsp;clinical characteristics,\u0026nbsp;body composition\u0026nbsp;measures and toxicity outcomes\u0026nbsp;are described in Table 1. The median age was\u0026nbsp;70\u0026nbsp;years (interquartile range [IQR], 57-78).\u0026nbsp;Approximately half of the women (n=20, 52.6%) were treated with alpelisib up to third line\u0026nbsp;or below, 18\u0026nbsp;(47.4%) patients received alpelisib as fourth or greater line of treatment, with a median\u0026nbsp;of 3\u0026nbsp;prior lines\u0026nbsp;of therapy (IQR, 2-4). \u0026nbsp;Patient mean weight was 60.2\u0026nbsp;kg\u0026nbsp;(standard deviation\u0026nbsp;[SD]\u0026nbsp;\u0026plusmn;13.5). Median BMI\u0026nbsp;was\u0026nbsp;22\u0026nbsp;kg/m\u003csup\u003e2\u003c/sup\u003e (IQR, 20.3-26.1),\u0026nbsp;and among the study population, 10 (26.3%) patients were obese. Median BSA was 1.58\u0026nbsp;m\u003csup\u003e2\u003c/sup\u003e (IQR, 1.5-1.7).\u003c/p\u003e\n\u003cp\u003eCT-based body composition indices were available and calculated for all patients. Patient median SMI was 35.8\u0026nbsp;cm\u003csup\u003e2\u003c/sup\u003e /m\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e(IQR, 31.2-43.4) as demonstrated in Figure 1, and a median SMG of 1142\u0026nbsp;AU (IQR,\u0026nbsp;935-1511). Patient median\u0026nbsp;LBM was\u0026nbsp;34.4 kg (IQR, 31-37.1).\u0026nbsp;The\u0026nbsp;mean SMA\u0026nbsp;was 87.94\u0026nbsp;cm\u003csup\u003e2\u003c/sup\u003e \u0026plusmn;29.6\u0026nbsp;[SD]), and\u0026nbsp;SMD\u0026nbsp;was 31.96 HU.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHalf of the patients were sarcopenic,\u0026nbsp;(n=19, 50%).\u0026nbsp;The study population PIK3CA mutations are presented in Supplementary Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eToxicity outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong the\u0026nbsp;study population,\u0026nbsp;almost half of the patients had a dose reduction of alpelisib (16, 42.1%), and 26 patients (68.4%) a dose interruption of therapy (Table 1).\u003c/p\u003e\n\u003cp\u003eA minority were hospitalized resulting from toxicity of the treatment (n=6,\u0026nbsp;16%).\u0026nbsp;Only\u0026nbsp;3 (8%)\u0026nbsp;patients did not experience any AE.\u0026nbsp;The majority of patients encountered AE grade \u0026ge;2 (n=31, 81.6%) and 15 women (39.5%) suffered from grade \u0026ge;3 AE.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBody composition as a predictor of increased alpelisib toxicity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong women with grade \u0026ge;2 AE, age, treatment line, ECOG PS, sarcopenia (SMI\u0026lt;38, and SMI teritial divisions), SMG, and LBM tertials\u0026nbsp;did not provide additional measures in determining the likelihood of increased drug toxicity (gastrointestinal, haematological, hyperglycaemia, and rash), hospitalizations, dose reductions and interruptions of alpelisib,\u0026nbsp;as demonstrated in Supplementary Table 2.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePatients with a lower tertial SMG were likely to have increased risk of Other toxicity, (22.6%, the upper two thirds which were 3.2%, and 6.5%, respectively, P=0.02).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhen evaluating each toxicity independently, age, ECOG, dose reductions and body composition measures (including BMI, BSA, VAT, SAT , SMA , SMI, SMG), they\u0026nbsp;were not associated with increased toxicity from alpelisib (Table\u0026nbsp;2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRisk of hyperglycemia was associated with lower mean VAT\u0026nbsp;(40 \u0026plusmn; 32.8\u0026nbsp;[SD]\u0026nbsp; cm\u003csup\u003e2 \u0026nbsp;\u003c/sup\u003evs. 103.3 \u0026plusmn; 57.7\u0026nbsp;[SD]\u0026nbsp;cm\u003csup\u003e2\u003c/sup\u003e, P=0.023), mean SAT (100.8\u0026plusmn;74.6\u0026nbsp;[SD]\u0026nbsp;cm\u003csup\u003e2\u003c/sup\u003e \u0026nbsp;vs. 183.4 \u0026plusmn; 66.5\u0026nbsp;[SD]\u0026nbsp;cm\u003csup\u003e2\u003c/sup\u003e, P=0.016),\u0026nbsp;mean SMD (41.6 \u0026plusmn; 11.6\u0026nbsp;[SD]\u0026nbsp;HU \u0026nbsp;vs. 29.6 \u0026plusmn; 9.2\u0026nbsp;[SD]\u0026nbsp;HU, P=0.015), median VAT density, -76.36 HU(IQR, -85.31, -60.27) vs. -91 HU(IQR, -98.79, -81.14, P=0.009), and median SAT density (-83.23 HU (IQR,-97.78, -81.28) vs. -101 HU (IQR, -105.2, -94.12), \u0026nbsp;P=0.021).\u0026nbsp;The risk of hyperglycaemia grade \u0026ge;1 was not associated with age, BMI, BSA, height, SMI, SMG, and LBM.\u003c/p\u003e\n\u003cp\u003eAmong the body composition measures, mean SMD was associated with grade\u0026nbsp;\u0026ge;2\u0026nbsp;hyperglycemia, (38\u0026nbsp;\u0026plusmn; 9.6\u0026nbsp;[SD]\u0026nbsp;HU vs. 28.9\u0026nbsp;\u0026plusmn; 9.7\u0026nbsp;[SD]\u0026nbsp;HU,\u0026nbsp;P=0.024). Median VAT was marginally associated with grade\u0026nbsp;\u0026ge;2\u0026nbsp;hyperglycemia, -79.69 HU (IQR, -92.9, -75.26) vs. -91 HU (IQR, -98.79, -83.14), P=0.05).\u003c/p\u003e\n\u003cp\u003eRash grade \u0026nbsp;\u0026ge;2 was associated with lower median VAT (-88.35 HU (IQR, -94.43, -78.22) vs. -97.8 HU (IQR, -172, -89.85), P=0.043). While grade \u0026ge;2 rash, was associated with an increased hospitalization (8% of patients hospitalized with a rash vs. 75.7% of patients who were not hospitalized and without a rash, P=0.042).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAmong patients with Other toxicity, they had a higher risk of developing grade\u0026nbsp;\u0026ge;2\u0026nbsp;hyperglycaemia (OR=9.58, P=0.01).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNone of the body composition metrics were found to be significantly associated with an increased likelihood of having hematological,\u0026nbsp;and\u0026nbsp;gastrointestinal toxicity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAmong the population of patients with sarcopenia (SMI\u0026lt;38) who were overweight or obese, 8 (23%) women experienced any toxicity grade \u0026ge;2, 21% hyperglycemia grade \u0026ge;2, 16% had a dose reduction or delay, 21% experienced Other toxicity, while none were hospitalized or experienced rash (grade \u0026ge;2). \u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo our knowledge, this is the first report of the impact of body composition measures on alpelisib toxicity and adherence to therapy. Body composition measures were useful in predicting alpelisib induced hyperglycemia and rash. Other AE were not associated with body metrics. This work demonstrates body composition parameters that may be integrated to identify patients with greater likelihood to develop treatment related toxicities beyond the conventional measures of BMI and BSA, and tailor observation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAmong the body composition measures, mean skeletal muscle density (SMD) was predictive of grade \u0026ge;2 hyperglycemia, thus women with lower SMD were at increased risk of developing treatment induced hyperglycemia. Additionally, there was a trend seen among women with lower mean visceral adipose tissue (VAT), who were more likely to develop grade \u0026ge;2 hyperglycemia.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThese measures, SMD and VAT may identify a patient population necessitating a more tailored treatment approach and observation, managing glucose control at lower grades and possibly earlier intervention.\u003c/p\u003e\n\u003cp\u003eWomen treated with alpelisib who developed a rash grade \u0026ge;2, had lower mean visceral adipose tissue, and greater likelihood of hospitalizations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInterestingly half of the study population were deemed sarcopenic, irrespective of BMI.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAdditionally, we did not find patient BMI, those who were overweight or obese, or age to be risk factors for treatment toxicity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLimitation of this study stem from the study design, a retrospective observational analysis of a small heterogeneous population, which may influence the external validity of the results. Additional, alpelisib was administered as an advanced line of therapy, 47% were treated as fourth or greater line, limiting the analysis of time to treatment failure and overall survival.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGiven the variability in the correlations between BMI and clinical outcomes in patients with breast cancer, assessment of body composition through distinct body compartments, such as \u0026nbsp;muscle, and fat, separately has evolved as a potentially more informative approach.\u003c/p\u003e\n\u003cp\u003eOur findings suggest that among the toxicities of alpelisib, hyperglycemia and rash were associated with lower SMD and VAT. These results raise the option to identify patients at higher risk for severe side effects, potentially guiding a more personalized approach for these patients. Future prospective studies may determine optimal interventions to mitigate toxicity for this risk group.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Patient characteristics\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ebody composition measures\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;and toxicity outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u003cstrong\u003eN=\u003c/strong\u003e\u003cstrong\u003e38\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\u003e\u003cstrong\u003eAge, mean \u0026plusmn; SD\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eyears\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e68\u0026nbsp;(14.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, median (IQR) years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e70 (57-77.5)\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\u003eFemale, n\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e38 (100)\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\u003eECOG n\u003c/strong\u003e\u003cstrong\u003e,\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(%)\u003c/strong\u003e\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\u003e8 (32)\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\u003e10 (40)\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\u003e5 (20)\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\u003e2 (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\u003cstrong\u003eAlpelisib treatment line n, (%)\u003c/strong\u003e\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\u0026le;\u003cspan dir=\"RTL\"\u003e3\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e20 (52.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e18 (47.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlpelisib mean treatment line\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlpelisib median treatment line (IQR)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e3 (2-4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeight, mean \u0026plusmn; SD, kg\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e60.2 (13.5)\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\u003eBMI, mean \u0026plusmn; SD\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e23.87 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI median (IQR)\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e22 (20.3-26.1)\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\u003eBMI category\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003en\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\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\u003eHealthy weight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e22 (57.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eOverweight\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e6 (15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eObese\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e10 (26.3)\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\u003eBSA, mean \u0026plusmn; SD\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e1.63 (0.18)\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\u003eBSA median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e1.58 (1.5-1.7)\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\u003eSMI, median (IQR), cm\u003csup\u003e2\u003c/sup\u003e /m\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e35.8\u003c/span\u003e (31.2-43.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSMG, median (IQR), AU\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e1142 (935-1511)\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\u003eLBM, kg, mean \u0026plusmn; SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e32.4428 (8.89)\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\u003eLBM, kg median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e34.4 (31-37.1)\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\u003eSMA,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003emean\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026plusmn; SD\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ecm\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e87.94 (29.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSMD\u003c/strong\u003e\u003cstrong\u003e, HU\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e31.96 (10.5)\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\u003eSarcopenic \u0026lt;38 n (%)\u003c/strong\u003e\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\u003eYes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e19 (5\u003cspan dir=\"RTL\"\u003e0\u003c/span\u003e)\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\u003eDose reduction\u0026nbsp;\u003c/strong\u003e\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\u003eYes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e16 (4\u003cspan dir=\"RTL\"\u003e2\u003c/span\u003e.1)\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\u003eDose interruption\u0026nbsp;\u003c/strong\u003e\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\u003eYes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e26 (\u003cspan dir=\"RTL\"\u003e68\u003c/span\u003e.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\u003cstrong\u003eHospitalizations due to drug, number (%)\u003c/strong\u003e\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\u003eYes (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e6 (16)\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\u003eAE\u003c/strong\u003e\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\u003cstrong\u003eG\u003c/strong\u003e\u003cstrong\u003erade \u0026ge;2 AE\u0026nbsp;\u003c/strong\u003e\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\u003eYes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e31 (81.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eG\u003c/strong\u003e\u003cstrong\u003erade \u0026ge;3 AE\u0026nbsp;\u003c/strong\u003e\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\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e15 (\u003cspan dir=\"RTL\"\u003e39\u003c/span\u003e.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: IQR = interquartile range, SD = standard deviation; Plus\u0026ndash;minus values are means \u0026plusmn;SD;\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e BMI = body mass index\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBMI-Healthy \u0026lt;25 kg/m\u003csup\u003e2\u003c/sup\u003e; overweight 25-30 kg/m\u003csup\u003e2\u003c/sup\u003e ; obese, \u0026ge;30 kg/m\u003csup\u003e2\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAE = adverse event, AU = arbitrary units,\u0026nbsp;BSA=body surface area , SMI=\u0026nbsp;skeletal muscle index,\u0026nbsp;Defined as SMI\u0026lt;38cm\u003csup\u003e2\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eSMD-\u0026nbsp;skeletal muscle density was derived by averaging Hounsfield Units (HU) of skeletal muscle at the L3 vertebrae.\u003c/p\u003e\n\u003cp\u003eSMG- skeletal muscle gauge was calculated by multiplying SMI x SMD; the units for SMG are: (cm^2 tissue * average HU)/(m^2 height) for simplicity we chose to represent \u0026nbsp;them as arbitrary units (AU)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLMB-\u0026nbsp;lean body mass (kg) = 0\u0026middot;30 \u0026times; [skeletal muscle at L3 using CT (cm\u003csup\u003e2\u003c/sup\u003e)] + 6\u0026middot;06]\u003c/p\u003e\n\u003cp\u003eSMA\u003cspan dir=\"RTL\"\u003e-\u0026nbsp;\u003c/span\u003eskeletal muscle area (cm\u003csup\u003e2\u003c/sup\u003e)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. \u0026nbsp;Body metric parameters predictive of independent toxicities\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.73913043478261%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHyperglycaemia\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eG\u003c/strong\u003e\u003cstrong\u003e\u0026ge;\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHyperglycaemia\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eG\u003c/strong\u003e\u003cstrong\u003e\u0026ge;2\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.347826086956523%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRash\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eG\u003c/strong\u003e\u003cstrong\u003e\u0026ge;1\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.08695652173913%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRash\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eG\u003c/strong\u003e\u003cstrong\u003e\u0026ge;2\u003c/strong\u003e\u003c/p\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=\"21.73913043478261%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.785\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.347826086956523%\" valign=\"top\"\u003e\n \u003cp\u003e0.256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.08695652173913%\" valign=\"top\"\u003e\n \u003cp\u003e0.312\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.73913043478261%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.347826086956523%\" valign=\"top\"\u003e\n \u003cp\u003e0.170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.08695652173913%\" valign=\"top\"\u003e\n \u003cp\u003e0.207\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.73913043478261%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBSA\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.363\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.347826086956523%\" valign=\"top\"\u003e\n \u003cp\u003e0.283\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.08695652173913%\" valign=\"top\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.73913043478261%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVAT, cm\u003csup\u003e2\u003c/sup\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.023*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.347826086956523%\" valign=\"top\"\u003e\n \u003cp\u003e0.227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.08695652173913%\" valign=\"top\"\u003e\n \u003cp\u003e0.102\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.73913043478261%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVAT, \u0026nbsp;HU\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.009*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.051**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.347826086956523%\" valign=\"top\"\u003e\n \u003cp\u003e0.020*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.08695652173913%\" valign=\"top\"\u003e\n \u003cp\u003e0.043*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.73913043478261%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSAT, \u0026nbsp;cm\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.016*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.347826086956523%\" valign=\"top\"\u003e\n \u003cp\u003e0.145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.08695652173913%\" valign=\"top\"\u003e\n \u003cp\u003e0.164\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.73913043478261%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSAT, HU\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.021*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.361\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.347826086956523%\" valign=\"top\"\u003e\n \u003cp\u003e0.907\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.08695652173913%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.73913043478261%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSMD, HU\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.015*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.024*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.347826086956523%\" valign=\"top\"\u003e\n \u003cp\u003e0.792\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.08695652173913%\" valign=\"top\"\u003e\n \u003cp\u003e0.442\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.73913043478261%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSMA, cm\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.315\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.347826086956523%\" valign=\"top\"\u003e\n \u003cp\u003e0.135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.08695652173913%\" valign=\"top\"\u003e\n \u003cp\u003e0.161\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.73913043478261%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIMAT, HU\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.547\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.347826086956523%\" valign=\"top\"\u003e\n \u003cp\u003e0.868\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.08695652173913%\" valign=\"top\"\u003e\n \u003cp\u003e0.680\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.73913043478261%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSMI,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ecm\u003csup\u003e2\u003c/sup\u003e /m\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.347826086956523%\" valign=\"top\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.08695652173913%\" valign=\"top\"\u003e\n \u003cp\u003e0.149\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.73913043478261%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSMG, AU\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.404\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.439\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.347826086956523%\" valign=\"top\"\u003e\n \u003cp\u003e0.823\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.08695652173913%\" valign=\"top\"\u003e\n \u003cp\u003e0.527\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.73913043478261%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDose reduction\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.347826086956523%\" valign=\"top\"\u003e\n \u003cp\u003e0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.08695652173913%\" valign=\"top\"\u003e\n \u003cp\u003e0.133\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.73913043478261%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospitalizations\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.564\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.303\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.347826086956523%\" valign=\"top\"\u003e\n \u003cp\u003e0.335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.08695652173913%\" valign=\"top\"\u003e\n \u003cp\u003e0.042*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.73913043478261%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLBM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91304347826087%\" valign=\"top\"\u003e\n \u003cp\u003e0.165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.347826086956523%\" valign=\"top\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.08695652173913%\" valign=\"top\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;Abbreviations: VAT \u0026ndash; visceral adipose tissue , SAT- subcutaneous adipose tissue, IMAT- intramuscular adipose tissue\u003c/p\u003e\n\u003cp\u003eP-value indicates statistical significance in the comparison of mean body metric compositions between groups that possess these characteristics and those that do not.\u003c/p\u003e\n\u003cp\u003e*statistically significant P\u0026lt;0.05 , **marginally significant\u0026nbsp;\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003einterquartile range, SD\u0026thinsp;=\u0026thinsp;standard deviation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePlus\u0026ndash;minus values are means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e\u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ebody mass index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003e This work was supported by the Conquer Cancer-Israel Cancer Research Fund Career Development Award 2021CC-ICRFCDA-5807223889\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eE.S. and S.S. wrote the main manuscript text, data analysis, statistical analysisA.R. data analysisU.K. statistical analysis R.K data extractionAll authors reviewed the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGiaquinto AN, Sung H, Miller KD et al (2022) Breast Cancer Statistics 2022 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Breast J 24(3):278\u0026ndash;284. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/tbj.12952\u003c/span\u003e\u003cspan address=\"10.1111/tbj.12952\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\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, sarcopenia, muscle attenuation, skeletal muscle index, skeletal muscle gauge, toxicity, survival, alpelisib, hyperglycemia, adipose tissue","lastPublishedDoi":"10.21203/rs.3.rs-3865840/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3865840/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eBody composition has emerged as an important prognostic factor in patients treated with cancer. Severe depletion of skeletal muscle, sarcopenia, has been associated with poor performance status and worse oncological outcomes. We studied patients with metastatic breast cancer receiving alpelisib, to determine if sarcopenia and additional body composition measures accounting for muscle and adiposity are associated with toxicity.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA retrospective observational analysis was conducted, including 38 women with metastatic breast cancer and a PIK3CA mutation, treated with alpelisib as advanced line of therapy. Sarcopenia was determined by measuring skeletal muscle cross-sectional area at the third lumbar vertebra using computerized tomography. Various body composition metrics were assessed along with drug toxicity, dose reductions, treatment discontinuation, and hospitalizations.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eSarcopenia was observed in half of the patients (n\u0026thinsp;=\u0026thinsp;19, 50%), spanning normal weight, overweight, and obese individuals. Among the body composition measures, lower skeletal muscle density (SMD) was associated with an increased risk of treatment-related hyperglycaemia (P\u0026thinsp;=\u0026thinsp;0.03). Additionally, lower visceral adipose tissue (VAT) was associated with alpelisib-induced rash (P\u0026thinsp;=\u0026thinsp;0.04) and hospitalizations (P\u0026thinsp;=\u0026thinsp;0.04). Notably, alpelisib treatment discontinuation was not impacted by alpelisib toxicity.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eBody composition measures, specifically SMD and VAT may provide an opportunity to identify patients at higher risk for severe alpelisib related hyperglycemia, and cutaneous toxicity. These findings suggest the potential use of body composition assessment to predict toxicity, allowing for personalized therapeutic observation and intervention.\u003c/p\u003e","manuscriptTitle":"Body composition measures as a determinant of Alpelisib related toxicity","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-17 16:14:42","doi":"10.21203/rs.3.rs-3865840/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-02-14T18:13:42+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-02-09T18:02:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"3e8be5d1-3e5b-433d-a481-4c5aa37dc601","date":"2024-01-24T08:57:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-01-24T02:41:06+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-01-16T07:40:48+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-01-16T07:40:48+00:00","index":"","fulltext":""},{"type":"submitted","content":"Breast Cancer Research and Treatment","date":"2024-01-15T08:20:46+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":"937e2a2f-b107-4683-98ca-babd603b2d6d","owner":[],"postedDate":"January 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-04-08T15:08:39+00:00","versionOfRecord":{"articleIdentity":"rs-3865840","link":"https://doi.org/10.1007/s10549-024-07315-9","journal":{"identity":"breast-cancer-research-and-treatment","isVorOnly":false,"title":"Breast Cancer Research and Treatment"},"publishedOn":"2024-04-07 15:01:10","publishedOnDateReadable":"April 7th, 2024"},"versionCreatedAt":"2024-01-17 16:14:42","video":"","vorDoi":"10.1007/s10549-024-07315-9","vorDoiUrl":"https://doi.org/10.1007/s10549-024-07315-9","workflowStages":[]},"version":"v1","identity":"rs-3865840","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3865840","identity":"rs-3865840","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}