Use of NHS PREDICT Tool and Prognostic Factors for Survival in Patients with Breast Cancer

Year 2024, Volume: 26 Issue: 2, 105 - 111, 30.08.2024

Koh Chee Keong , Wan Zainira Wan Zain , Zalına Zaharı , Maya Mazuwın Yahya , Hussain Mohamad

https://doi.org/10.18678/dtfd.1419974

Abstract

Aim: The PREDICT tool is used to estimate survival in breast cancer patients according to the types of treatment given. This study aimed to assess the accuracy of the PREDICT tool and identify the prognostic factors for survival in patients with breast cancer.
Material and Methods: A retrospective study was performed based on data collected from the Hospital Sultanah Nur Zahirah, Terengganu, Malaysia. All female patients diagnosed with stage I to IV breast cancer were identified from the year 2011 to 2017.
Results: Based on data from 355 eligible patients, the predicted and observed 5-year overall survival rates were 75.8% and 75.2%, respectively. The model performed fairly well, with the area under the curve (AUC) of 0.747 (95% confidence interval (CI): 0.69-0.81) in the predicted 5-year overall survival. Among the 585 patients diagnosed with stage I to IV breast cancer, stage at the presentation (stage III hazard ratio (HR): 5.80, 95% CI: 1.69-19.94, p=0.005, stage IV HR: 10.61, 95% CI: 3.09-36.49, p<0.001), without surgical treatment (HR: 2.29, 95% CI: 1.73-3.00, p<0.001), without radiotherapy (HR: 1.92, 95% CI: 1.41-2.62, p<0.001), and without neoadjuvant chemotherapy (HR: 0.63, 95% CI: 0.47-0.86, p=0.003) were associated with death in breast cancer patients.
Conclusion: The PREDICT tool accurately estimated the 5-year overall survival in the study center. It might serve as a useful prognostication tool during consultation. Late stages of the disease, patients without surgical treatment, and patients without radiotherapy were associated with a higher risk of death in breast cancer.

Keywords

breast cancer, 5-year overall survival, PREDICT

Meme Kanserli Hastalarda Hayatta Kalma için NHS PREDICT Aracının Kullanımı ve Prognostik Faktörler

Abstract

Amaç: PREDICT aracı, meme kanseri hastalarında verilen tedavi türlerine göre sağkalımı tahmin etmek için kullanılır. Bu çalışmanın amacı, PREDICT aracının doğruluğunu değerlendirmek ve meme kanserli hastalarda sağkalım için prognostik faktörleri belirlemektir.
Gereç ve Yöntemler: Malezya'nın Terengganu şehrindeki Sultanah Nur Zahirah Hastanesi'nden toplanan verilere dayalı olarak geriye dönük bir çalışma yapıldı. 2011 ve 2017 yılları arasında evre I ila IV meme kanseri tanısı alan tüm kadın hastalar belirlendi.
Bulgular: Uygun 355 hastadan elde edilen verilere dayanarak, öngörülen ve gözlemlenen 5 yıllık genel sağkalım oranları sırasıyla %75,8 ve %75,2 idi. Model, öngörülen 5 yıllık genel sağkalımda 0,747 (%95 GA: 0,69-0,81) eğri altında kalan alan (area under the curve, AUC) ile oldukça iyi performans gösterdi. Evre I ila IV meme kanseri tanısı alan 585 hasta arasında, başvuru anındaki evre (evre III hazard oranı (hazard ratio, HR): 5,80, %95 GA: 1,69-19,94, p=0,005, evre IV HR: 10,61, %95 GA: 3,09-36,49, p<0,001), cerrahi tedavi olmaması (HR: 2,29, %95 GA: 1,73-3,00, p<0,001), radyoterapi olmaması (HR: 1,92, %95 GA: 1,41-2,62, p<0,001) ve neoadjuvan kemoterapi olmaması (HR: 0,63, %95 GA: 0,47-0,86, p=0,003) meme kanseri hastalarında ölümle ilişkiliydi.
Sonuç: PREDICT aracı çalışma merkezindeki 5 yıllık genel sağkalımı doğru bir şekilde tahmin etti. Konsültasyon sırasında yararlı bir prognoz aracı olarak hizmet edebilir. Hastalığın ileri evreleri, cerrahi tedavi uygulanmayan hastalar ve radyoterapi uygulanmayan hastalar meme kanserinde daha yüksek ölüm riskiyle ilişkilidir.

Keywords

PREDICT, meme kanseri, 5 yıllık genel sağkalım

References

• Dahlui M, Ramli S, Bulgiba AM. Breast cancer prevention and control programs in Malaysia. Asian Pac J Cancer Prev. 2011;12(6):1631-4.
• Yip CH, Bhoo Pathy N, Teo SH. A review of breast cancer research in Malaysia. Med J Malaysia. 2014;69(Suppl A):8-22.
• Abdullah NA, Wan Mahiyuddin WR, Muhammad NA, Ali ZM, Ibrahim L, Ibrahim Tamim NS, et al. Survival rate of breast cancer patients in Malaysia: a population-based study. Asian Pac J Cancer Prev. 2013;14(8):4591-4.
• Pathy NB, Yip CH, Taib NA, Hartman M, Saxena N, Iau P, et al. Breast cancer in a multi-ethnic Asian setting: results from the Singapore-Malaysia hospital-based breast cancer registry. Breast. 2011;20(Suppl 2):S75-80.
• Unger-Saldaña K. Challenges to the early diagnosis and treatment of breast cancer in developing countries. World J Clin Oncol. 2014;5(3):465-77.
• Soh JY, Yahya MM, Bachok N, Wan Zain WZ, Wong MP, Zakaria Z, et al. Factors associated with delay in seeking care for breast symptoms. BMC Womens Health. 2022;22(1):316.
• van Maaren MC, van Steenbeek CD, Pharoah PDP, Witteveen A, Sonke GS, Strobbe LJA, et al. Validation of the online prediction tool PREDICT v. 2.0 in the Dutch breast cancer population. Eur J Cancer. 2017;86:364-72.
• Wong HS, Subramaniam S, Alias Z, Taib NA, Ho GF, Ng CH, et al. The predictive accuracy of PREDICT: a personalized decision-making tool for Southeast Asian women with breast cancer. Medicine (Baltimore). 2015;94(8):e593.
• Zaguirre K, Kai M, Kubo M, Yamada M, Kurata K, Kawaji H, et al. Validity of the prognostication tool PREDICT version 2.2 in Japanese breast cancer patients. Cancer Med. 2021;10(5):1605-13.
• Nordin N, Yaacob NM, Abdullah NH, Mohd Hairon S. Survival time and prognostic factors for breast cancer among women in North-East Peninsular Malaysia. Asian Pac J Cancer Prev. 2018;19(2):497-502.
• Polchai N, Sa-Nguanraksa D, Numprasit W, Thumrongtaradol T, O-Charoenrat E, O-Charoenrat P. A comparison between the online prediction models CancerMath and PREDICT as prognostic tools in Thai breast cancer patients. 2020;12:5549-59.
• Agostinetto E, Ameye L, Martel S, Aftimos P, Pondé N, Maurer C, et al. PREDICT underestimates survival of patients with HER2-positive early-stage breast cancer. NPJ Breast Cancer. 2022;8(1):87.
• Li L, Chang B, Jiang X, Fan X, Li Y, Li T, et al. Clinical outcomes comparison of 10 years versus 5 years of adjuvant endocrine therapy in patients with early breast cancer. BMC Cancer. 2018;18(1):977.
• Norsa'adah B, Rampal KG, Rahmah MA, Naing NN, Biswal BM. Diagnosis delay of breast cancer and its associated factors in Malaysian women. BMC Cancer. 2011;11:141.
• Guiu S, Arnould L, Bonnetain F, Dalban C, Favier L, Desmoulins I, et al. Pathological response and survival after neoadjuvant therapy for breast cancer: a 30-year study. Breast. 2013;22(3):301-8.
• Tartter PI, Pace D, Frost M, Bernstein JL. Delay in diagnosis of breast cancer. Ann Surg. 1999;229(1):91-6.
• Richards MA, Smith P, Ramirez AJ, Fentiman IS, Rubens RD. The influence on survival of delay in the presentation and treatment of symptomatic breast cancer. Br J Cancer. 1999;79(5-6):858-64.
• Bello MA, Menezes RF, Silva B, da Silva Rde C, Cavalcanti RS, Moraes TD, et al. Impact of treatment type on overall survival in elderly Brazilian women with breast cancer. Asian Pac J Cancer Prev. 2016;17(10):4769-74.
• Wang W. Radiotherapy in the management of early breast cancer. J Med Radiat Sci. 2013;60(1):40-6.