COMPARISON OF 18F-FDG PET/CT DATA WİTH TYPE 2 DIABETES AND OBESITY IN BREAST CANCER

Öz

Objective: The aim of the present study was to evaluate the association of obesity and diabetes with 18F-FDG PET/CT SUVmax values and metastasis in breast cancer patients. Material and Methods: The study included 126 breast cancer patients who underwent 18F-FDG PET/CT for staging between 2023 and 2024. Results: There was no significant correlation between the presence of obesity and breast tumour SUVmax value (p=0.427). There was no significant relationship between body mass index and metastatic lymph node SUVmax and distant metastasis SUVmax (p=0.06, p=0.457). There was no significant association between the presence or absence of diabetes and distant metastasis SUVmax or lymph node metastasis SUVmax on 18F-FDG PET/CT (p=0.723, p=0.581). In our study, there was no significant difference in the 18F-FDG PET/CT findings of breast cancer patients with diabetes at the time of diagnosis compared to women without diabetes. In addition, although not statistically significant, we found that the median SUVmax values for lymph node and distant metastases were significantly higher in obese and morbidly obese patients compared to other patients. Therefore, we think that breast cancer patients should be followed up more closely in the follow-up of obese and diabetic patients, taking these conditions into consideration and patients should be advised to lose weight. Conclusion: In conclusion, although we did not find a significant association between body mass indeks and diabetes and breast cancer in our study, we think that this may be due to the small number of patients. We also found that the risk of axillary lymph node metastasis increased as breast tumor SUVmax increased and the cut-off value for breast tumor SUVmax was 5.15. We think that the presence of lymph node metastasis on PET/CT should be reported carefully, taking into account the SUVmax value.

Anahtar Kelimeler

• Breast cancer
• body mass ındex
• diabetes mellitus

Meme Kanserinde Diyabet ve Obezite Varlığı ile F18- FDG PET/BT Verilerinin Karşılaştırması

Öz

Amaç: Bu çalışmadaki amacımız, meme kanseri hastalarında obezite ve diyabetin 18F-FDG PET/BT SUVmax değerleri ve metastaz ile ilişkisini değerlendirmektir. Gereç ve Yöntemler: Çalışmaya 2023 ve 2024 yılları arasında evreleme için 18F-FDG PET/BT çekilen 126 meme kanseri hastası dahil edilmiştir. Bulgular: Obezite varlığı ile meme tümörü SUVmax değeri arasında anlamlı bir korelasyon yoktu (p=0,427). Beden kitle indeksi ile uzak metastaz SUVmax değeri ve metastatik lenf nodu SUVmax değeri arasında anlamlı bir korelasyon yoktu (p=0,06, p=0,457). Diyabet varlığı veya yokluğu ile 18F-FDG PET/BT'de uzak metastaz SUVmax veya metastatik lenf nodu SUVmax değerleri arasında anlamlı bir ilişki bulunmamıştır (p=0,723, p=0,581). Çalışmamızda tanı anında diyabeti olan meme kanserli hastaların 18F-FDG PET/BT bulgularında diyabeti olmayan kadınlara göre anlamlı bir fark bulunmamıştır. Ayrıca, istatistiksel olarak anlamlı olmasa da, lenf nodu ve uzak metastazlar için ortanca SUVmax değerlerinin obez ve morbid obez hastalarda diğer hastalara kıyasla anlamlı derecede yüksek olduğunu tespit ettik. Bu nedenle meme kanseri hastalarının takibinde obez ve diyabetik hastaların bu durumları göz önünde bulundurularak daha yakından takip edilmesi ve hastalara kilo vermelerinin önerilmesi gerektiğini düşünüyoruz. Sonuç: Sonuç olarak, çalışmamızda beden kitle indeksi ve diyabet ile meme kanseri arasında anlamlı bir ilişki bulamamış olsak da, bunun hasta sayısının azlığından olabileceğini düşünüyoruz. Ayrıca, meme tümörü SUVmax değeri arttıkça aksiller lenf nodu metastazı riskinin arttığını ve meme tümörü SUVmax değeri için cut-off değerinin 5,15 olduğunu bulduk. PET/BT'de lenf nodu metastazı varlığının SUVmax değeri dikkate alınarak dikkatli bir şekilde raporlanması gerektiğini düşünüyoruz.

Anahtar Kelimeler

• Meme kanseri
• beden kitle indeksi
• diyabet

Kaynakça

1. Momenimovahed Z, Salehiniya H. Epidemiological characteristics of and risk factors for breast cancer in the world. Breast Cancer. 2019;11:151–164.
2. Sun YS, Zhao Z, Yang ZN, et al. Risk factors and preventions of breast cancer. Int J Biol Sci. 2017;13:1387–1397.
3. Bhaskaran K, Douglas I, Forbes H, dos-Santos-Silva I, Leon DA, Smeeth L. Body-mass index and risk of 22 specific cancers: a population-based cohort study of 5• 24 million UK adults. Lancet, 2014;384(9945),755-765.
4. Kahn CR, Wang G, Lee KY. Altered adipose tissue and adipocyte function in the pathogenesis of metabolic syndrome. J Clin Invest. 2019;129:3990–4000.
5. Qureshi R, Picon-Ruiz M, Aurrekoetxea-Rodriguez I, et al. The major pre-and postmenopausal estrogens play opposing roles in obesity-driven mammary inflammation and breast cancer development. Cell Metab. 2020;31(6),1154-1172.
6. Gavilá J, Lopez-Tarruella S, Saura C, et al. SEOM clinical guidelines in metastatic breast cancer 2015. Clin Transl Oncol. 2015;17,946-955.
7. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2019. CA Cancer J Clin 2019;69(1),7-34.
8. Thomas A, Rhoads A, Suhl J, et al. Incidence and survival by human epidermal growth factor receptor 2 status in young women with stage I-III breast cancer: SEER, 2010-2016. Clin Breast Cancer. 2020;20(4),e410-e422.

9. Larsson SC, Mantzoros CS, Wolk A. Diabetes mellitus and risk of breast cancer: a meta‐analysis. Int J Cancer. 2007;121(4),856-862.
10. Buysschaert M, Sadikot S. Diabetes and cancer: a 2013 synopsis. Diabetes Metab Syndr. 2013;7:247–250.
11. Gallagher EJ, LeRoith D. The proliferating role of insulin and insulin-like growth factors in cancer. Trends Endocrinol Metab. 2010; 21:610–618
12. Novosyadlyy R, Lann DE, Vijayakumar A, et al. Insulin-mediated acceleration of breast cancer development and progression in a nonobese model of type 2 diabetes. Cancer Res. 2010;70:741–751.
13. Nelson ER, Wardell SE, Jasper JS, et al. 27-Hydroxycholesterol links hypercholesterolemia and breast cancer pathophysiology. Science. 2013;342:1094–1098.
14. Gavilá J, Lopez-Tarruella S, Saura C, et al. SEOM clinical guidelines in metastatic breast cancer 2015. Clin Transl Oncol. 2015;17,946-955.
15. Garcia-Saenz JA, Bermejo B, Estevez LG, et al. SEOM clinical guidelines in early-stage breast cancer 2015. Clin Transl Oncol. 2015;17,939-945.
16. Neuhouser ML, Aragaki AK, Prentice RL, et al. Overweight, obesity, and postmenopausal invasive breast cancer risk: a secondary analysis of the women’s health initiative randomized clinical trials. JAMA Oncol. 2015;1(5),611-621.
17. Porter GA, Inglis KM, Wood LA, et al. Effect of obesity on presentation of breast cancer. Ann Surg Oncol. 2006;13,327-332.
18. Neuhouser ML, Aragaki AK, Prentice RL, et al. Overweight, obesity, and postmenopausal invasive breast cancer risk: a secondary analysis of the women’s health initiative randomized clinical trials. JAMA Oncol. 2015;1(5),611-621.
19. Quartuccio N, Ialuna S, Pulizzi S, et al. The Correlation of body mass ındex with risk of recurrence in post-menopausal women with breast cancer undergoing Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography. J Clin Med. 2024;13(6),1575.
20. Leitner BP, Perry RJ. The impact of obesity on tumor glucose uptake in breast and lung cancer. JNCI Cancer Spectr. 2020;4(2),pkaa007.
21. Wahl RL, Jacene H, Kasamon Y, Lodge MA. From RECIST to PERCIST: evolving considerations for PET response criteria in solid tumors. J Nucl Med. 2009;50(Suppl 1),122S-150S.
22. Michels KB, Solomon CG, Hu FB, et al. Type 2 diabetes and subsequent incidence of breast cancer in the Nurses’ Health Study. Diabetes Care. 2003;26(6),1752-1758.
23. Bota M, Autier P, Boyle P. The risk of breast cancer in women with diabetes. Diabetes.2018;67(Suppl 1):180-OR
24. Kım J, Goak YU, Yıng J, et al. The Impact of type 2 diabetes mellitus on the clinical outcome of breast cancer. Diabetes. 2023;72(4):512-520.
25. Jee SH, Ohrr H, Sull JW, et al. Fasting serum glucose level and cancer risk in Korean men and women. JAMA. 2005;293(2),194-202.
26. Lipscombe LL, Goodwin PJ, Zinman B, et al. The impact of diabetes on survival following breast cancer. Breast Cancer Res Treat. 2008;109,389-395.
27. Yoo J, Kim BS, Yoon HJ. Predictive value of primary tumor parameters using 18 F-FDG PET/CT for occult lymph node metastasis in breast cancer with clinically negative axillary lymph node. Ann Nucl Med. 2018;32,642-648.
28. Zhang J, Shi X, Xiao Y. Early SUVmax is the best predictor of axillary lymph node metastasis in stage III breast cancers. Quant Imaging Med Surg .2021;11(5),1680-1691.