Prediction of survival probabilities based on models developed by other countries has shown inconsistent findings among Malaysian patients. This study aimed to develop predictive models for survival among women with breast cancer in Malaysia. A retrospective cohort study was conducted involving patients who were diagnosed between 2012 and 2016 in seven breast cancer centres, where their survival status was followed until 31 December 2021. A total of 13 predictors were selected to model five-year survival probabilities by applying Cox proportional hazards (PH), artificial neural networks (ANN), and decision tree (DT) classification analysis. The random-split dataset strategy was used to develop and measure the models’ performance. Among 1006 patients, the majority were Malay, with ductal carcinoma, hormone-sensitive, HER2-negative, at T2-, N1-stage, without metastasis, received surgery and chemotherapy. The estimated five-year survival rate was 60.5% (95% CI: 57.6, 63.6). For Cox PH, the c-index was 0.82 for model derivation and 0.81 for validation. The model was well-calibrated. The Cox PH model outperformed the DT and ANN models in most performance indices, with the Cox PH model having the highest accuracy of 0.841. The accuracies of the DT and ANN models were 0.811 and 0.821, respectively. The Cox PH model is more useful for survival prediction in this study’s setting.
Background: Bladder cancer ranked ninth of principal male cancer in Malaysia. This study aimed to evaluate the clinical characteristics and survival of bladder cancer patients in Malaysia. Methods: A retrospective cohort study was conducted by obtaining records in the Malaysian National Cancer Registry. Patients aged 15 years old and above with diagnosis date between 2007 and 2011 were included. Death was updated until 31 December 2016. Five-year observed survival and median survival time were determined by the life table method and Kaplan–Meier estimate method. Results: Among 1828 cases, the mean (SD) age of diagnosis was 64.9 (12.5) years. The patients were predominantly men (78.7%), Malay ethnicity (49.4%) and transitional cell carcinoma (78.2%). Only 14.8% of patients were at stage I. The overall five-year observed survival and median survival time was 36.9% (95% CI: 34.6, 39.1) and 27.3 months (95% CI: 23.6, 31.0). The highest five-year observed survival recorded at stage I (67.6%, 95% CI: 62.0, 73.3) and markedly worsen at stage II (34.3%, 95% CI: 27.9, 40.8), III (25.7%, 95% CI: 18.7, 32.6) and IV (12.2%, 95% CI: 8.1, 16.3). Conclusions: Survival of bladder cancer patients in Malaysia was lower with advancing stage. The cancer control programme should be enhanced to improve survival.
Women with breast cancer are keen to know their predicted survival. We developed a new prognostic model for women with breast cancer in Malaysia. Using the model, this study aimed to design the user interface and develop the contents of a web-based prognostic tool for the care provider to convey survival estimates. We employed an iterative website development process which includes: (1) an initial development stage informed by reviewing existing tools and deliberation among breast surgeons and epidemiologists, (2) content validation and feedback by medical specialists, and (3) face validation and end-user feedback among medical officers. Several iterative prototypes were produced and improved based on the feedback. The experts (n = 8) highly agreed on the website content and predictors for survival with content validity indices ≥ 0.88. Users (n = 20) scored face validity indices of more than 0.90. They expressed favourable responses. The tool, named Malaysian Breast cancer Survival prognostic Tool (myBeST), is accessible online. The tool estimates an individualised five-year survival prediction probability. Accompanying contents were included to explain the tool’s aim, target user, and development process. The tool could act as an additional tool to provide evidence-based and personalised breast cancer outcomes.
Background: Malaysia has the third highest crude mortality rates of bladder cancer within Southeast Asia. We aimed to identify the prognostic factors for bladder cancer patients in Malaysia. Methods: A retrospective population-based study was conducted among patients diagnosed between 2007 and 2011. Death date until 31 December 2016 was updated. Cox proportional hazard regression analysis was performed to examine clinical variables as prognostic factors of death. Results: Identified prognostic factors of 1828 analyzed patients were age groups, ethnicity, morphology, stage, and surgery. As compared to patients aged 15–44, the adjusted Hazard Ratio for those aged 45–54, 55–64, 65–74, and ≥75 were 1.59, 1.87, 2.46, and 3.47, respectively. Malay and other ethnic groups had 1.22- and 1.40-times the risk of death compared to Chinese. Patients with squamous cell carcinoma were at 1.47-times the hazard of death compared to urothelial carcinoma patients. Stages II, III and IV patients had 2.20-, 2.98-, and 4.12-times the risk of death as compared to stage I. Patients who did not receive surgery were at 50% increased hazard of death. Conclusion: Early detection and/or surgery, especially for those more than 75 years old, Malay, and squamous cell carcinoma could potentially improve survival. The findings could inform national cancer control programs.
The PREDICT breast cancer is a well-known online calculator to estimate survival probability. We developed a new prognostic model, myBeST, due to the PREDICT tool’s limitations when applied to our patients. This study aims to compare the performance of the two models for women with breast cancer in Malaysia. A total of 532 stage I to III patient records who underwent surgical treatment were analysed. They were diagnosed between 2012 and 2016 in seven centres. We obtained baseline predictors and survival outcomes by reviewing patients’ medical records. We compare PREDICT and myBeST tools’ discriminant performance using receiver-operating characteristic (ROC) analysis. The five-year observed survival was 80.3% (95% CI: 77.0, 83.7). For this cohort, the median five-year survival probabilities estimated by PREDICT and myBeST were 85.8% and 82.6%, respectively. The area under the ROC curve for five-year survival by myBeST was 0.78 (95% CI: 0.73, 0.82) and for PREDICT was 0.75 (95% CI: 0.70, 0.80). Both tools show good performance, with myBeST marginally outperforms PREDICT discriminant performance. Thus, the new prognostic model is perhaps more suitable for women with breast cancer in Malaysia.
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