Taste Alterations Do Not Affect Change in Food Habits and Body Weight in Breast Cancer Patients

Background/Aim: Chemotherapy-induced taste alterations (TAs) affect approximately 53-84% of breast cancer patients with significant consequences on flavor perception, possibly leading to food aversion and changes in daily dietary habits. The aim of this study was to investigate the relationship between TAs and changes in food habits and body weight among early breast cancer (EBC) patients undergoing adjuvant chemotherapy. Patients and Methods: TAs were prospectively evaluated in 182 EBC patients from April 2014 to June 2018. TAs, dietary habits, and body weight were collected by a trained dietician. TAs were classified into different subtypes according to the following basic taste perception: metallic, sweet, bitter, salty, sour, and umami taste. Results: During adjuvant chemotherapy, a significant reduction in the consumption of bread, breadsticks, red meat, fat salami, snacks, added sugar, milk, and alcoholic beverages was observed, regardless of TAs onset. No correlation between these dietary changes and different TAs subtypes was found. Body weight remained stable in most EBC patients (71.4%) and was not influenced by TAs onset and by different TAs subtypes. Conclusion: EBC patients change their dietary habits during adjuvant chemotherapy, mostly following the World Cancer Research Fund recommendations, irrespective of TAs onset and without affecting body weight

Fat Body Mass and Vertebral Fracture Progression in Women With Breast Cancer

Importance Women with early breast cancer (EBC) exposed to aromatase inhibitors (AIs) may experience fragility fractures despite treatment with bone-active drugs. Risk factors for fractures in patients receiving AIs and denosumab have not been explored to date.Objectives To evaluate whether an association exists between dual x-ray absorptiometry (DXA)-measured fat body mass (FBM) and vertebral fracture (VF) progression in postmenopausal women with EBC undergoing adjuvant therapy with AIs in combination with denosumab and to examine whether VF was associated with common risk factors for bone fracture and parameters of body composition other than FBM.Design, Setting, and Participants For this prospective, single-center, cohort study, 237 patients with EBC who were undergoing adjuvant treatment with AIs and denosumab (60 mg every 6 months) were enrolled at the Breast Unit of the ASST Spedali Civili of Brescia from September 2014 to June 2018. Data analysis was conducted in June 2022.Exposure Body composition parameters, bone mineral density, and morphometric VFs were assessed by DXA at study entry and after 18 months of therapy.Main Outcomes and MeasuresVF progression, defined as either new or worsening of preexisting VFs, between the 2 time points.Results Of the 237 patients enrolled (median [range] age, 61 [28-84] years), 17 (4.4%) reported VF progression. Univariable analysis found an association between VF progression and a history of clinical fractures (odds ratio [OR], 3.22; 95% CI, 1.19-8.74; P = .02), Fracture Risk Assessment Tool (FRAX) score for major fractures (OR, 4.42; 95% CI, 1.23-13.79; P = .04), percentage of FBM (OR, 6.04; 95% CI, 1.69-21.63; P = .006), and android fat (OR, 9.58; 95% CI, 1.17-78.21; P = .04) and an inverse association with appendicular lean mass index-FBM ratio (OR, 0.25, 95% CI, 0.08-0.82; P = .02). Multivariable analysis revealed percentage of FBM (OR, 5.41; 95% CI, 1.49-19.59; P = .01) and FRAX score (OR, 3.95; 95% CI, 1.09-14.39; P = .04) as independent variables associated with VF progression.Conclusions and Relevance The findings of this study suggest that baseline FBM is an independent factor for VF progression in patients with EBC treated with adjuvant AIs and denosumab. This observation is new and indicates that diet and exercise may synergize with denosumab in the management of bone health in this patient setting

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Transformation of prostate adenocarcinoma into small-cell neuroendocrine cancer under androgen deprivation therapy: Much is achieved but more information is needed

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Solitary metastasis from occult thyroid cancer mimicking a convexity meningioma

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