Implication of body mass index (BMI) on the biological and clinical effects of endocrine therapy plus abemaciclib as neoadjuvant therapy for early breast cancer patients

Reporting on patient's body mass index (BMI) in recent clinical trials for patients with breast cancer: a systematic review

BACKGROUND

The proportion of patients with breast cancer and obesity is increasing. While the therapeutic landscape of breast cancer has been expanding, we lack knowledge about the potential differential efficacy of most drugs according to the body mass index (BMI). Here, we conducted a systematic review on recent clinical drug trials to document the dosing regimen of recent drugs, the reporting of BMI and the possible exclusion of patients according to BMI, other adiposity measurements and/or diabetes (leading comorbidity of obesity). We further explored whether treatment efficacy was evaluated according to BMI.

METHODS

A search of Pubmed and ClinicalTrials.gov was performed to identify phase I-IV trials investigating novel systemic breast cancer treatments. Dosing regimens and exclusion based on BMI, adiposity measurements or diabetes, documentation of BMI and subgroup analyses according to BMI were assessed.

RESULTS

495 trials evaluating 26 different drugs were included. Most of the drugs (21/26, 81%) were given in a fixed dose independent of patient weight. BMI was an exclusion criterion in 3 out of 495 trials. Patients with diabetes, the leading comorbidity of obesity, were excluded in 67/495 trials (13.5%). Distribution of patients according to BMI was mentioned in 8% of the manuscripts, subgroup analysis was performed in 2 trials. No other measures of adiposity/body composition were mentioned in any of the trials. Retrospective analyses on the impact of BMI were performed in 6 trials.

CONCLUSIONS

Patient adiposity is hardly considered as most novel drug treatments are given in a fixed dose. BMI is generally not reported in recent trials and few secondary analyses are performed. Given the prevalence of patients with obesity and the impact obesity can have on pharmacokinetics and cancer biology, more attention should be given by investigators and study sponsors to reporting patient's BMI and evaluating its impact on treatment efficacy and toxicity.

Impact of BMI in Patients With Early Hormone Receptor-Positive Breast Cancer Receiving Endocrine Therapy With or Without Palbociclib in the PALLAS Trial

PURPOSE

BMI affects breast cancer risk and prognosis. In contrast to cytotoxic chemotherapy, CDK4/6 inhibitors are given at a fixed dose, irrespective of BMI or weight. This preplanned analysis of the global randomized PALLAS trial investigates the impact of BMI on the side-effect profile, treatment adherence, and efficacy of palbociclib.

METHODS

Patients were categorized at baseline according to WHO BMI categories. Neutropenia rates were assessed with univariable and multivariable logistic regression. Time to early discontinuation of palbociclib was analyzed with Fine and Gray competing risk models. Unstratified Cox models were used to investigate the association between BMI category and time to invasive disease-free survival (iDFS). 95% CIs were derived.

RESULTS

Of 5,698 patients included in this analysis, 68 (1.2%) were underweight, 2,082 (36.5%) normal weight, 1,818 (31.9%) overweight, and 1,730 (30.4%) obese at baseline. In the palbociclib arm, higher BMI was associated with a significant decrease in neutropenia (unadjusted odds ratio for 1-unit change, 0.93; 95% CI, 0.91 to 0.94; adjusted for age, race ethnicity, region, chemotherapy use, and Eastern Cooperative Oncology Group at baseline, 0.93; 95% CI, 0.92 to 0.95). This translated into a significant decrease in treatment discontinuation rate with higher BMI (adjusted hazard ratio [HR] for 10-unit change, 0.75; 95% CI, 0.67 to 0.83). There was no significant improvement in iDFS with the addition of palbociclib to ET in any weight category (normal weight HR, 0.84; 95% CI, 0.63 to 1.12; overweight HR, 1.10; 95% CI, 0.82 to 1.49; and obese HR, 0.95; 95% CI, 0.69 to 1.30) in this analysis early in follow-up (31 months).

CONCLUSION

This preplanned analysis of the PALLAS trial demonstrates a significant impact of BMI on side effects, dose reductions, early treatment discontinuation, and relative dose intensity. Additional long-term follow-up will further evaluate whether BMI ultimately affects outcome.

Development and validation of a nomogram for predicting deep venous thrombosis in patients with pelvic and acetabular fractures: a retrospective cohort study : Predictive model for pelvic/acetabular fractures

PURPOSE

To construct a novel nomogram model that can predict DVT and avoid unnecessary examination.

METHODS

Patients admitted to the hospital with pelvis/acetabular fractures were included between July 2014 and July 2018. The potential predictors associated with DVT were analyzed using Univariate and multivariable logistic regression analysis. The predictive nomogram was constructed and internally validated.

RESULTS

230 patients were finally enrolled. There were 149 individuals in the non-DVT group and 81 in the DVT group. Following analysis, we obtained the final nomogram model. The risk factors included age (OR, 1.037; 95% CI, 1.013-1.062; P = 0.002), body mass index (BMI) (OR, 1.253; 95% CI, 1.120-1.403; P < 0.001); instant application of anticoagulant after admission (IAA) (OR, 2.734; 95% CI, 0.847-8.829; P = 0.093), hemoglobin (HGB) (OR, 0.970; 95% CI, 0.954-0.986; P < 0.001), D-Dimer(OR, 1.154; 95% CI, 1.016-1.310; P = 0.027) and fibrinogen (FIB) (OR, 1.286; 95% CI, 1.024-1.616; P = 0.002). The apparent C-statistic was 0.811, and the adjusted C-statistic was 0.777 after internal validations, demonstrating good discrimination. Hosmer and Lemeshow's goodness of fit (GOF) test of the predictive model showed a good calibration for the probability of prediction and observation (χ2 = 3.285, P = 0.915; P > 0.05). The decision curve analysis (DCA) and Clinical impact plot (CIC) demonstrated superior clinical use of the nomogram.

CONCLUSIONS

An easy-to-calculate nomogram model for predicting DVT in patients with pelvic-acetabular fractures were developed. It could help clinicians to reduce DVT and avoid unnecessary examinations.

The Challenges of Treating Patients with Breast Cancer and Obesity

Obesity is defined as a body mass index (BMI) of 30 kg/m² or more and is associated with worse outcomes in patients with breast cancer, resulting in an increased incidence of breast cancer, recurrence, and death. The incidence of obesity is increasing, with almost half of all individuals in the United States classified as obese. Patients with obesity present with unique pharmacokinetics and physiology and are at increased risk of developing diabetes mellitus and cardiovascular disease, which leads to specific challenges when treating these patients. The aim of this review is to summarize the impact of obesity on the efficacy and toxicity of systemic therapies used for breast cancer patients, describe the molecular mechanisms through which obesity can affect systemic therapies, outline the existing American Society of Clinical Oncology (ASCO) guidelines for treating patients with cancer and obesity, and highlight additional clinical considerations for treating patients with obesity and breast cancer. We conclude that further research on the biological mechanisms underlying the obesity-breast cancer link may offer new treatment strategies, and clinicals trials that focus on the treatment and outcomes of patients with obesity and all stages of breast cancer are needed to inform future treatment guidelines.

The association between adiposity and anti-proliferative response to neoadjuvant endocrine therapy with letrozole in post-menopausal patients with estrogen receptor positive breast cancer

The impact of adiposity on the efficacy of endocrine treatment in patients with estrogen receptor positive breast cancer is poorly investigated. Here, we retrospectively investigated in a cohort of 56 patients whether body mass index and/or mammary adiposity are associated with anti-proliferative response in the neoadjuvant setting. Anti-proliferative response was defined as high Ki67 at baseline (Ki67_bl) and low Ki67 at surgery (Ki67_srg), using the 14% cut-off. Mammary adipocyte size was assessed on hematoxylin and eosin slides from the surgical samples using digital pathology. A higher proportion of tumors with an anti-proliferative response was observed in patients with obesity (54.5%) as compared to patients with normal weight (9.0%) and patients with overweight (40.0%) (p = 0.031), confirmed by multivariable regression analysis adjusted for baseline Ki67 (OR, obese vs normal weight: 13.76, 95%CI: 1.49–207.63, p = 0.020). Larger adipocyte diameter was identified as predictor of anti-proliferative response (OR per increase in diameter of 5 μm for adipocytes distant from the tumor: 2.24, 95%CI: 1.01–14.32, p = 0.046). This study suggests that anti-proliferative response to neoadjuvant letrozole might be more frequent in patients with increased systemic or mammary adiposity.