Nutrition and Breast Cancer: A Literature Review on Prevention, Treatment and Recurrence
Abstract
:1. Introduction
2. Selection of Studies
3. Dietary Factors in Breast Cancer Incidence and Recurrence
3.1. Fruits and Vegetables
3.2. Red Meat
3.3. Dietary Fat
3.4. Dairy Products
3.5. Carbohydrate and Glycaemic Index
3.6. Alcohol
3.7. Soy Products and Isoflavones
4. Impact of Therapy on Nutritional Status of Women with BC
5. Nutritional Interventions during BC Treatment
5.1. ω-3 Poly Unsaturated Fatty Acids (PUFAs)
5.2. Green Tea
5.3. Antioxidants Vitamins and Minerals
5.4. Intermittent Fasting
6. Nutritional Interventions to Reduce BC Recurrence and Mortality
7. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Study | Results | Reference | |
---|---|---|---|
Fruits, vegetables | Meta-analysis (15 prospective studies) | RR = 0.89 (95% CI, 0.80–0.99, p = 0.67) fruits + vegetables; highest vs. lowest intake RR = 0.92 (95% CI, 0.86–0.98, p = 0.36) fruits; highest vs. lowest intake RR = 0.99 (95% CI, 0.92–1.06, p = 0.26) vegetables; highest vs. lowest intake | [25] |
Prospective study (75,929 women, 38–63 years, 24 years follow-up) | RR = 0.82 (95% CI, 0.71–0.96, p = 0.01), 2 servings/week of total berries RR = 0.69 (95% CI, 0.50–0.95, p = 0.02), 1 serving/week of blueberries RR = 0.59 (95% CI, 0.37–0.93, p = 0.02), 2 servings/week of peaches/nectarines | [26] | |
Prospective study (31,000 women, 36–64 years, 11.25 years follow-up) | HR = 0.70 (95% CI, 0.57–0.86, p = 0.0001) leafy vegetables, highest vs. lowest quintile HR = 0.75 (95% CI, 0.60–0.94, p = 0.01) fruiting vegetables, highest vs lowest quintile no association with fruit | [27] | |
Red meat | Meta-analysis (13 cohort, 3 case-control, 2 clinical trials) | RR = 1.06 (95%CI, 0.99–1.14) unprocessed red meat, highest vs. lowest intake RR = 1.09 (95%CI, 1.03–1.16) processed red meat, highest vs. lowest intake | [28] |
Cohort study (262,195 women, 7 years follow-up) Meta-analysis | HR = 1.21 (95% CI, 1.08–1.35, p = 0.001), >9 g/day processed red meat RR = 1.09 (95% CI 1.03–1.15, p = 0.662), >9 g/day processed red meat in post-menopausal women RR = 0.99 (95% CI 0.88–1.10, p = 0.570), >9 g/day processed red meat in pre-menopausal women | [29] | |
Dietary Fat | Randomized controlled trial (48,835 post-menopausal women, 8.1 years follow-up) | HR = 0.91 (95% CI, 0.83–1.01, NS) intervention group vs. control group | [30] |
Meta-analysis (cohort + case-control studies) | RR = 1.091 (95% CI, 1.001–1.184) cohort PUFA RR = 1.042 (95%CI, 1.013–1.073) case-control total fat RR = 1.22 (95% CI, 1.08–1.38) case-control PUFA | [31] | |
Systematic review (18 studies) | 45–78% increased risk of death with increased intake of trans fats | [32] | |
EPIC study (337,327 women, 11.5 years follow-up) | HR = 1.20 (95% CI, 1.0–1.45, p = 0.05), highest vs. lowest quintile of total fat intake (ER+PR+ BC) HR = 1.2 (95% CI, 1.09–1.52, p = 0.009), highest vs. lowest quintile of saturated fat intake (ER+PR+ BC) HR = 1.29 (95% CI, 1.01–1.64, p = 0.04), highest vs. lowest quintile of saturated fat intake (HER2− BC) | [33] | |
Meta-analysis (6 cohort studies + 3 case-control studies) | RR = 1.29 (95% CI, 1.06–1.56), highest vs. lowest cholesterol intake | [34] | |
Dairy products | Pooled analysis (8 prospective cohort studies) (351,041 women, 15 years follow-up) | NS | [35] |
Meta-analysis (18 prospective cohort studies, n = 1,063,471) | RR = 0.91 (95% CI, 0.80–1.02, p = 0.003), milk consumption RR = 0.85 (95% CI, 0.76–0.95, p = 0.01), highest vs. lowest total dairy food | [36] | |
Meta-analysis (22 cohort + 5 case-control studies) | RR = 0.90 (95% CI, 0.83–0.98, p = 0.111), highest vs. lowest dairy products RR = 0.91 (95% CI, 0.83–0.99, p = 0.991), yogurt consumption RR = 0.85 (95% CI, 0.75–0.96, p = 0.121), low-fat dairy consumption | [37] | |
Carbohydrate, Glycaemic Index | Meta-analysis (19 prospective studies) | RR = 1.04 (95% CI, 1.00–1.07, p = 0.19), 10 units/d for glycemic index RR = 1.01 (95% CI, 0.98–1.04, p = 0.07), 50 units/d for glycemic load RR = 1.00 (95% CI, 0.96–1.05, p = 0.01), 50 g/d for carbohydrate intake | [38] |
Soy products, isoflavones | Meta-analysis (14 case-control + 7 cohort studies) | RR = 0.75 (95% CI, 0.59–0.95, p = 0.023), soyfood intake RR = 0.81 (95% CI, 0.67–0.99), isoflavone intake | [39] |
Meta-analysis (1 cohort + 7 case-control studies) | OR = 0.71 (95% CI, 0.60–0.85, p = 0.023), highest vs. lowest soy intake in Asians OR = 0.88 (95% CI, 0.78–0.98, p = 0.60), moderate vs. lowest soy intake in Asians OR = 1.04 (95% CI, 0.97–1.11, p = 0.42), highest vs. lowest soy isoflavone intake in Western populations | [40] | |
Meta-analysis (18 prospective studies) | RR = 0.89 (95% CI, 0.79–0.99, p = 0.001), highest vs. lowest isoflavone intake (RR = 0.76, 95% CI: 0.65–0.86, p = 0.136 in Asian population; RR = 0.97, 95% CI: 0.87–1.06, p = 0.083 in Western population) | [41] |
Study | Intervention | Results | Reference | |
---|---|---|---|---|
ω-3 PUFAs | Phase II clinical trial (n = 25 breast cancer patients, 31 months follow-up) | 1.8 g DHA/day anthracycline | Improvement of chemo-therapy outcome: median TTP = 6 months (95% CI, 2.8–8.7 months); median OS = 22 months (95% CI, 17–33 months) No severe adverse side effects (grade 3 or 4 toxicity only for neutropenia and alopecia, 80%) | [99] |
Pilot study (n = 38 postmenopausal breast cancer patients) | 4 g/day EPA + DHA for 3 months AI therapy | Inhibition of bone resorption in the fish oil responders vs. placebo (p < 0.05) | [100] | |
Controlled clinical trial (n = 249 postmenopausal breast cancer patients) | 3.3 g/day ω3 PUFA (560 mg EPA + DHA, 40:20 ratio) 24 weeks AI therapy | Reduction of arthralgia (4.36 vs. 5.70, p = 0.02) obese BC patients vs. placebo | [101] | |
Controlled clinical trial (n = 20 breast cancer patients) | EPA (0.19 g/day) + DHA (1.04 g/day) paclitaxel | Reduction of paclitaxel-induced peripheral neuropathy incidence (OR = 0.3; 95% CI, 0.10–0.88, p = 0.029), but not severity (0.95% CI = (−2.06–0.02), p = 0.054) EPA + DHA vs. placebo | [102] | |
Green tea | Prospective cohort study (n = 1160 breast cancer patients, 8 years follow-up) | Regular consumption of green tea | Inverse association between regular green tea consumption (≥3 cups/day) and BC recurrence for stage I/II patients (HR = 0.69; 95% CI, 0.47–1.00, p < 0.05) | [103] |
Prospective cohort study (n = 472 breast cancer patients, 7 years follow-up) | Regular consumption of green tea | Inverse association between regular green tea consumption (≥5 cups/day) and BC recurrence for stage I/II patients (RR = 0.564; 95% CI, 0.350–0.911, p < 0.05) | [104] | |
Prospective cohort study (n = 5042, 9.1 years follow-up) | Regular consumption of green tea | Reduced risk of total mortality (HR = 0.57; 95% CI: 0.34–0.93) and recurrence (HR = 0.54; 95% CI: 0.31–0.96) for the first 60-month post-diagnosis period | [105] | |
Vitamin C | Controlled clinical trial (n = 54 post-menopausal breast cancer patients) | Vitamin C (500 mg) and E (400 mg) +tamoxifen (10 mg twice a day) for 90 days | Decrease of total cholesterol, TG, VLDL (p < 0.001) and LDL (p < 0.01) vs. tamoxifen alone Increase of HDL (p < 0.01) vs. tamoxifen alone | [106] |
Controlled clinical trial (n = 40 breast cancer patients) | Vitamin C (500 mg) and E (400 mg) + 5-fluorouracil (500 mg/m2) + doxorubicin (50 mg/m2) + cyclophosphamide (500 mg/m2) (every 3 weeks for six cycles) | Increase of SOD, CAT, GST, GPx, GSH (p < 0.01) vs. chemotherapy alone Decrease of MDA, DNA damage (p < 0.01) vs. chemotherapy alone | [107] | |
Vitamin E | Prospective cohort study (n = 7 breast cancer patients, 30 days follow-up) | Vitamin E (400 mg) + tamoxifen (20 mg daily) for 30 days | Vitamin E supplement interferes with the therapeutic effects of tamoxifen (increase expression of biomarkers of estrogen-stimulation (ER, PR, p-ERK in breast biopsies) | [108] |
Vitamin D | Prospective cohort study (n = 232 post-menopausal breast cancer patients, 1-year follow-up) | Calcium (1 g) + vitamin D3 (800 IU/d and additional 16,000 IU, every 2 weeks) + AI therapy for 1 year | Reduction of AI-associated lumbar spine bone loss: 1.70% (95% CI, 0.4–3.0%; p = 0.005) (women with 25(OH)D serum levels ≥40 ng/ml vs. women with serum levels <30 ng/ml) | [109] |
Prospective cohort study (n = 60 post-menopausal breast cancer patients, 16 weeks follow-up) | 50,000 IU/week + AI therapy for 12 weeks | Decrease of disability from joint pain (52 vs. 19%; p = 0.026); reduction of fatigue (BFI scores 1.4 vs. 2.9; NS); reduction of menopausal symptoms (MENQOL scores 2.2 vs. 3.2, p = 0.035) (women with 25OHD levels > 66 ng/ml vs. women with levels < 66 ng/ml) | [110] |
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De Cicco, P.; Catani, M.V.; Gasperi, V.; Sibilano, M.; Quaglietta, M.; Savini, I. Nutrition and Breast Cancer: A Literature Review on Prevention, Treatment and Recurrence. Nutrients 2019, 11, 1514. https://doi.org/10.3390/nu11071514
De Cicco P, Catani MV, Gasperi V, Sibilano M, Quaglietta M, Savini I. Nutrition and Breast Cancer: A Literature Review on Prevention, Treatment and Recurrence. Nutrients. 2019; 11(7):1514. https://doi.org/10.3390/nu11071514
Chicago/Turabian StyleDe Cicco, Paola, Maria Valeria Catani, Valeria Gasperi, Matteo Sibilano, Maria Quaglietta, and Isabella Savini. 2019. "Nutrition and Breast Cancer: A Literature Review on Prevention, Treatment and Recurrence" Nutrients 11, no. 7: 1514. https://doi.org/10.3390/nu11071514