Does Neoadjuvant Chemotherapy in Clinical T1-T2 N0 Triple-Negative Breast Cancer Increase the Extent of Axillary Surgery?

BACKGROUND: Current management strategies for early-stage triple-negative breast cancer (TNBC) include upfront surgery to determine pathologic stage to guide chemotherapy recommendations, or neoadjuvant chemotherapy (NAC) to de-escalate surgery, elucidate tumor response, and determine the role of adjuvant chemotherapy. However, patients who receive NAC with residual pathological nodal (pN) involvement require axillary lymph node dissection (ALND) as they are Z11/AMAROS ineligible. We aimed to evaluate the impact of NAC compared with upfront surgery on pN status and ALND rates in cT1-2N0 TNBC. METHODS: The National Cancer Database (NCDB) was queried for women with operable cT1-2N0 TNBC from 2014 to 2019. Demographic, clinicopathologic, and treatment data were collected. Multivariable linear regression analysis was performed to assess the odds of pN+ disease and undergoing ALND. RESULTS: Overall, 55,624 women were included: 26.9% (n = 14,942) underwent NAC and 73.1% (n = 40,682) underwent upfront surgery. The NAC cohort was younger (mean age 52.9 vs. 61.3 years; p < 0.001) with more cT2 tumors (71.6% vs. 31.0%; p < 0.001), and had lower ALND rates (4.3% vs. 5.5%; p < 0.001). The upfront surgery cohort was more likely to have one to three pathologically positive nodes (12.1% vs. 6.5%; odds ratio [OR] 2.37, 95% confidence interval (CI) 2.17-2.58; p < 0.001) but there was no difference in the likelihood of ALND (OR 1.1, 95% CI 0.99-1.24; p = 0.08). CONCLUSION: Patients who underwent upfront surgery were more likely to be pN+; however, ALND rates were similar between the two cohorts. Thus, the use of NAC does not result in a higher odds of ALND and the decision for NAC should be individualized and based on modern guidelines and systemic therapy benefits.

Pulmonary vs. extra-pulmonary tuberculosis hospitalizations in the US [1998-2014].

BACKGROUND: Few studies have explored the relative burden and trends in pulmonary (PTB) vs. extra-pulmonary (EPTB) tuberculosis in the United States using a nationally representative sample. METHODS: This study examined trends in hospitalization rates, length-of-stay (LOS), in-hospital mortality and inflation-adjusted charges, for PTB vs. EPTB using the Nationwide/National Inpatient Sample (NIS) from 1998 to 2014. Descriptive and multivariable analyses (linear, negative binomial and logistic) were utilized adjusting for demographics, co-morbidity and hospital characteristics. RESULTS: During the study period there were a survey-adjusted, estimated 258,631 PTB (75.5%), 76,476 EPTB (22.3%) and 7552 concurrent PTB and EPTB (2.2%) discharges. Whites accounted for 27.6% of PTB, 21.9% of EPTB and 17.6% of concurrent discharges; and self-pay or no insurance accounted for 22.2%, 18.4%, and 25.9%, respectively. EPTB was more common among blacks (22.5%), and combined TB more common among Hispanics (24.8%). Mean LOS was 11.4 days, 13.2 days, and 19.5 days; with mean nominal charges of $48,031, $62,255, and $89,364 for PTB, EPTB and combined TB respectively. Inpatient mortality for all three groups was approximately 5.7%. Miliary TB and TB of meninges and central nervous system were positively associated with mortality (odds ratios of 2.44 and 2.11, respectively), as was alcohol abuse (OR 1.21). Trend analyses showed decreased hospitalizations for all TB types, no change in LOS trends, decreased mortality for PTB and ETB and increased charges for PTB and ETB from 1998 to 2014. Increased utilization, higher charges and higher risk of mortality (to some extent) among the EPTB cases warrant improved methods for screening, diagnosis and treatment. CONCLUSION: Though rates of TB hospitalization are declining, EPTB is becoming relatively more common and is more costly compared to pulmonary TB. Screening methods that focus on identification of ETB contrary to current practice guidelines are needed to aid ETB case finding.

Red and Processed Meat and Mortality in a Low Meat Intake Population.

Associations of low-to-moderate consumption of red and processed meat with mortality would add to the evidence of possible adverse effects of these common foods. This study aims to investigate the association of red and processed meat intake with mortality. The Adventist Health Study-2 (AHS-2) is a prospective cohort study of ~96,000 Seventh-day Adventist men and women recruited in the US and Canada between 2002 and 2007. The final analytic sample after exclusions was 72,149. Cox proportional hazards regression was used and hazard ratios (HR) and confidence intervals (CI) were obtained. Diet was assessed by a validated quantitative food frequency questionnaire (FFQ), calibrated using six 24-h dietary recalls. Mortality outcome data were obtained from the National Death Index. During a mean follow-up of 11.8 years, there were 7961 total deaths, of which 2598 were Cardiovascular diseases (CVD) deaths and 1873 were cancer deaths. Unprocessed red meat was associated with risk of all-cause mortality (HR: 1.18; 95% CI: 1.07⁻1.31) and CVD mortality (HR: 1.26; 95% CI: 1.05⁻1.50). Processed meat alone was not significantly associated with risk of mortality. The combined intake of red and processed meat was associated with all-cause mortality (HR: 1.23; 95% CI: 1.11⁻1.36) and CVD mortality (HR: 1.34; 95% CI: 1.12⁻1.60). These findings suggest moderately higher risks of all-cause and CVD mortality associated with red and processed meat in a low meat intake population.

Plasma, Urine, and Adipose Tissue Biomarkers of Dietary Intake Differ Between Vegetarian and Non-Vegetarian Diet Groups in the Adventist Health Study-2.

BACKGROUND: Differences in food composition, nutrient intake, and various health outcomes have been reported for vegetarians and non-vegetarians in the Adventist Health Study-2 (AHS-2) cohort. OBJECTIVE: We sought to determine whether biomarkers of dietary intake also differed between individuals classified as vegetarian (vegan, lacto-ovo-vegetarian, pesco-vegetarian, semi-vegetarian) and non-vegetarians based on patterns of consumption of meat, dairy, and eggs. METHODS: Fasting plasma, overnight urine, and adipose tissue samples were collected from a representative subset of AHS-2 participants classified into 5 diet groups (vegan, lacto-ovo-vegetarian, pesco-vegetarian, semi-vegetarian, non-vegetarian) who also completed food-frequency questionnaires. Diet-related biomarkers including carotenoids, isoflavones, enterolactone, saturated and polyunsaturated fatty acids, and vitamins were analyzed in 840 male and female participants. Multiple linear regression was used to examine the association between diet pattern and biomarker abundance, comparing each of 4 vegetarian dietary groups to non-vegetarians, and adjusted mean values were calculated. Bonferroni correction was applied to control for multiple testing. RESULTS: Vegans had higher plasma total carotenoid concentrations (1.6-fold, P < 0.0001), and higher excretion of urinary isoflavones (6-fold, P < 0.0001) and enterolactone (4.4-fold) compared with non-vegetarians. Vegans had lower relative abundance of saturated fatty acids including myristic, pentadecanoic, palmitic, and stearic acids (P < 0.0001). Vegans had higher linoleic acid (18:2ω-6) relative to non-vegetarians (23.3% compared with 19.1%) (P < 0.0001), and a higher proportion of total ω-3 fatty acids (2.1% compared with 1.6%) (P < 0.0001). Results overall were similar but less robust for lacto-ovo- and pesco-vegetarians. 1-Methylhistidine was 92% lower in vegans, and lower in lacto-ovo- and pesco-vegetarians by 90% and 80%, respectively, relative to non-vegetarians (P < 0.0001). CONCLUSION: AHS-2 participants following vegan, and lacto-ovo- or pesco-vegetarian diet patterns have significant differences in plasma, urine, and adipose tissue biomarkers associated with dietary intakes compared with those who consume a non-vegetarian diet. These findings provide some validation for the prior classification of dietary groups within the AHS-2 cohort.

Meal Frequency and Timing Are Associated with Changes in Body Mass Index in Adventist Health Study 2.

Background: Scientific evidence for the optimal number, timing, and size of meals is lacking.Objective: We investigated the relation between meal frequency and timing and changes in body mass index (BMI) in the Adventist Health Study 2 (AHS-2), a relatively healthy North American cohort.Methods: The analysis used data from 50,660 adult members aged ≥30 y of Seventh-day Adventist churches in the United States and Canada (mean ± SD follow-up: 7.42 ± 1.23 y). The number of meals per day, length of overnight fast, consumption of breakfast, and timing of the largest meal were exposure variables. The primary outcome was change in BMI per year. Linear regression analyses (stratified on baseline BMI) were adjusted for important demographic and lifestyle factors.Results: Subjects who ate 1 or 2 meals/d had a reduction in BMI per year (in kg · m-2 · y-1) (-0.035; 95% CI: -0.065, -0.004 and -0.029; 95% CI: -0.041, -0.017, respectively) compared with those who ate 3 meals/d. On the other hand, eating >3 meals/d (snacking) was associated with a relative increase in BMI (P < 0.001). Correspondingly, the BMI of subjects who had a long overnight fast (≥18 h) decreased compared with those who had a medium overnight fast (12-17 h) (P < 0.001). Breakfast eaters (-0.029; 95% CI: -0.047, -0.012; P < 0.001) experienced a decreased BMI compared with breakfast skippers. Relative to subjects who ate their largest meal at dinner, those who consumed breakfast as the largest meal experienced a significant decrease in BMI (-0.038; 95% CI: -0.048, -0.028), and those who consumed a big lunch experienced a smaller but still significant decrease in BMI than did those who ate their largest meal at dinner.Conclusions: Our results suggest that in relatively healthy adults, eating less frequently, no snacking, consuming breakfast, and eating the largest meal in the morning may be effective methods for preventing long-term weight gain. Eating breakfast and lunch 5-6 h apart and making the overnight fast last 18-19 h may be a useful practical strategy.

[Frequency and timing of meals and changes in body mass index: Analysis of the data from the Adventist Health Study-2]. / Frekvence a nacasování jídel a zmeny v body mass indexu: analýza dat z Adventist Health Study-2.

GOAL: Our study focuses on examining the relationship between the frequency and timing of meals and changes in BMI in the Adventist Health Study-2 (AHS-2) which represents a relatively healthy population in North America. METHODOLOGY: A longitudinal analysis was undertaken using data from 48 673 individuals monitored over an average period of 7.43 ± 1.24 years. The number of meals per day, length of nighttime fasting, eating breakfast and timing of the largest meal of the day (breakfast 5-11 a.m., lunch noon-4 p.m. or supper/dinner 5-11 p.m.) were used as independent variables. The primary output was the change in body mass index (BMI) once in a year. Linear regression analyses were adjusted for all important demographic factors and lifestyle factors. RESULTS: Consumption of 1 and 2 meals a day was associated with decrease in BMI (-0.04; 95% CI -0.06 to -0.03 and -0.02; 95% CI -0.03 to -0,01 kg.m-2 per year, respectively). On the other hand, consumption of 3 or more meals a day was associated with increase in BMI, in a linear relation (p < 0.001). BMI of those who skipped breakfast increased (0.029; 95% CI 0.021-0.037 kg.m-2 per year; p = 0.002) as compared to no BMI change in those who had breakfast (-0.0002; 95% CI -0.005 to + 0.004 kg.m-2 per year). Those, whose largest meal of the day was breakfast, recorded no significant change in BMI (-0.002 95% CI -0.008 to +0.004 kg.m-2 per year). On the contrary, the largest supper was associated with the greatest increase in BMI (0.034; 95% CI 0.029-0.040 kg.m-2 per year). CONCLUSION: Our results indicate that eating less frequently, consuming breakfast and having the largest meal in the morning hours may be effective measures to prevent weight gain.Key words: body mass index (BMI) - frequency and timing of meals - body mass regulation - breakfast.