Effectiveness and safety of drugs for obesity

Henderson Lewis, Kristina; Sloan, Caroline E; Bessesen, Daniel H; Arterburn, David

doi:10.1136/bmj-2022-072686

Cited by 13 publications

(1 citation statement)

References 174 publications

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“…At the same time, newer anti-obesity drugs can achieve unprecedented double-digit percentages decreases in initial body weight, with more options to choose from in the coming years. The future for pharmacotherapy of obesity has never been so bright [ 8 ].…”

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Diabetes and Cancer: The Perfect Storm and a PRICE to Pay

Gallo

2024

Cancers

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confidence: 99%

Diabetes and Cancer: The Perfect Storm and a PRICE to Pay

Gallo

2024

Cancers

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Obesity and metabolic syndrome in adults with a 22q11.2 microdeletion

Jaspers Faijer-Westerink,

von Scheibler,

van Rossum

et al. 2024

Int J Obes

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Objective Copy number variations (CNVs) may contribute to medical conditions. However, research on the impact of individual CNVs on endocrine disease is limited. This study aimed to provide new data on obesity and metabolic syndrome (MetS) in adults with microdeletion 22q11.2, the pathogenic CNV associated with 22q11.2 deletion syndrome. Methods We examined prevalence rates of obesity and MetS in 103 adults with a typical 22q11.2 deletion (45.2% male, at median age 30.0 (range 17–71) years) and compared these rates with population-based data. Generalized obesity was defined by a body mass index (BMI) ≥ 30 kg/m2, abdominal obesity by a waist circumference (WC) of ≥102 cm in males and ≥88 cm in females, and MetS by standard Joint Interim Statement criteria. General linear models were used to examine the independent associations of age, sex, congenital heart defect, smoking, and antipsychotic use with BMI, WC, and the presence of MetS. Results Prevalence rates of generalized obesity (32.0%), abdominal obesity (51.5%), and MetS (33.0%) were significantly higher compared to a population-based cohort (15.7% (P < 0.0001), 36.1% (P = 0.002), and 15.2% (P < 0.0001), respectively). In antipsychotic naïve subjects, significant correlations were observed between age and BMI (r = 0.54, P < 0.001), and age and WC (r = 0.60, P < 0.001). These correlations were not present in individuals taking antipsychotic medication. The models predicting BMI (F(5, 97) = 3.083, R2 = 0.137, P = 0.01) and WC (F(5, 92) = 5.985, R2 = 0.245, P < 0.001) were significant. Only age was individually predictive of outcomes (P < 0.05 and P < 0.001). The model predicting MetS was also significant (P < 0.001), with higher age being the only factor associated with MetS (OR = 1.07, 95% CI = 1.03–1.12, P < 0.001). Conclusions Generalized and abdominal obesity, as well as MetS, appear to be common in adults with 22q11.2 deletion syndrome, emphasizing the importance of careful monitoring from a young age. These findings contribute to the limited knowledge about the association between pathogenic CNVs, obesity, and MetS.

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An algorithm for the use of anti-obesity medications

Dehghani,

Ali Ahmadi,

Hefner

et al. 2024

Nutr. Diabetes

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Reduced energy diet and increased physical activity form the cornerstone of medical management of obesity. However, longterm adherence to a restricted diet is highly challenging [1]. Antiobesity medications (AOM) help to resist food cravings, reduce hunger, or increase satiety, thereby empowering individuals to adhere to a restricted diet and promote greater weight loss [2]. Therefore, AOM are needed, not as a substitute, but as a supplement to lifestyle modification efforts for weight management. The concept of pharmacological support for obesity treatment is similar to the use of medications for other chronic diseases with a behavioral component, such as diabetes or hypertension. Fortunately, several drug options are now available to treat hypertension or diabetes. And, in case of a suboptimal response of an individual to a drug, a health care provider (HCP) may choose a different drug or a different set of drugs. Similarly, if an individual is a poor responder to a particular AOM, that drug may still help another individual, and a different AOM may be more effective for the person who did not respond initially [3].Often, the drug selection for treatment is based on many criteria, including accompanying comorbidities, prior response to medications, potential adverse events, and drug costs. For example, for diabetes treatment, secretagogues, mimetic, or sensitizers of insulin may be selected depending on the individual's pathophysiology and circumstances. Similarly, AOM are comprised of medications with a range of target pathways, adverse event profiles, routes of administration, costs, and weight loss response [2].However, AOM face additional challenges in recognition of their need for obesity management. While diabetes is widely recognized as a disease that needs aggressive medical attention, obesity may not be viewed by the patients or some HCPs as a serious disease that needs lifelong management, including pharmacotherapy. Furthermore, due to the refractory nature of obesity, resource intense treatment, and limited health insurance coverage, the window of opportunity to treat obesity is limited. Individuals with obesity who are less successful in an initial weight loss attempt are likely to abandon treatment and are less likely to initiate a new weight management attempt [4]. In addition, there are a limited number of Food and Drug Administration (FDA)-approved AOMs for long-term care. Therefore, a careful matching of AOM to an individual's need is needed to maximize the chances of weight loss success. Hence, we propose an algorithm based on the indications of various FDAapproved AOM. First, a very brief description of AOM is merited.

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Effectiveness and safety of drugs for obesity

Cited by 13 publications

References 174 publications

Diabetes and Cancer: The Perfect Storm and a PRICE to Pay

Diabetes and Cancer: The Perfect Storm and a PRICE to Pay

Obesity and metabolic syndrome in adults with a 22q11.2 microdeletion

An algorithm for the use of anti-obesity medications

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