A comparison of breast cancer survival across different age groups: a multicentric database study in Penang, Malaysia

Tan, King Fang; Adam, Farzaana; Hussin, Hasmah; Mujar, Noor Mastura Mohd

doi:10.4178/epih.e2021038

Cited by 21 publications

(15 citation statements)

References 20 publications

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“…16 In our 234 BC patients, the average age of diagnosis at 53 years was comparable to other reports from Asian countries including Thailand. The 5-year OS in our patients at 54% was obviously lower than in other reports from countries with comparable economic levels 17,18 which might partly be explained by the fact that nearly half (46%) of our group had locally advanced disease at presentation, 62% of them had lymph node metastasis and 27% had evidence of distant metastasis. Our patients had significantly poorer survival outcomes because of advanced-stage disease.…”

Section: Discussioncontrasting

confidence: 82%

“…In addition, when compared stage-by-stage, overall mortality was similar between our and other Asian studies. 17,19 In a cooperative hospital-based study from Singapore and Malaysia reported in 2011, the size of the primary tumor significantly decrease after the implementation of mammographic screening and the same study showed that only 10% of the patients had distant metastasis at presentation and the figure decreased with time. 20 A nation-wide survey in China in 2011, which had begun a screening program, reported that 18.7% of their BC patients were in stage III, and only 2.4% were in stage IV.…”

Section: Discussionmentioning

confidence: 96%

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Survival Outcomes in Breast Cancer Patients and Associated Factors in a Border Province of Thailand: A Hospital-based Review

Sukpan

Kanokwiroon

Sriplung

et al. 2022

J Health Sci Med Res

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Objective: To evaluate the outcomes of breast cancer (BC) patients in Naradhiwas Rajanagarindra Hospital and factors associated with the outcomes. Material and Methods: A hospital-based retrospective review of patients who were diagnosed with BC in a tertiarylevel hospital in a Thailand border province was performed. Familial histories were obtained by telephone interviews. Results: There were 234 female patients diagnosed with BC during the 6-year study period. The mean age at diagnosis was 52.6 years. At presentation, 46.2% of the patients had locally advanced disease and 26.5% already had distant metastasis. Invasive ductal carcinoma (IDC) was the most common pathological subtype (84.6%) and 4.3% were ductal carcinoma in-situ. The five-year overall survival (OS) was 54% (95% confidence interval (CI) 40.25%-58.15%). On univariate analysis, factors associated with poorer survival were age >50 years, IDC pathology, T stage 3-4, N stage 2-3, distant metastasis, negative estrogen receptors, negative progesterone receptors, or both, positive human epidermal growth factor receptors 2, and Ki67 immunoreactivity >20%. Multivariate analysis showed that advanced T stage (adjusted HR1.97 95% CI 1.15-3.38), N stage (adjusted HR1.95 95% CI 1.05-3.64) and distant metastasis (HR1.86 95% CI 1.27- 2.71). Forty-nine percent of the BC women met the hereditary cancer criteria. Conclusion: The survival outcome of BC in Narathiwat province was poorer than that reported in other parts of the country. Delayed presentation might be an explanation for this disparity and a BC screening program is recommended to improve early detection.

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Section: Discussioncontrasting

confidence: 82%

Section: Discussionmentioning

confidence: 96%

Survival Outcomes in Breast Cancer Patients and Associated Factors in a Border Province of Thailand: A Hospital-based Review

Sukpan

Kanokwiroon

Sriplung

et al. 2022

J Health Sci Med Res

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“…However, PLA2G10 was found to have a weak protective effect on the survival of patients with BC in our analysis. Previous findings indicate that patients with BC who are ≤ 40 years old have worse survival and a higher risk of recurrence than that in patients > 40 years old ( Cathcart-Rake et al, 2021 ; Tan et al, 2021 ). Further, a clinical study showed that the 5-years survival rates of patients with BC in stages I, II, III, IV, and unknown were 100%, 91.9%, 78.8%, 34.2%, and 76.4%, respectively ( Mangone et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

A Metabolic Gene Signature to Predict Breast Cancer Prognosis

Liu

Zhang

2022

Front. Mol. Biosci.

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Background: The existing metabolic gene signatures for predicting breast cancer outcomes only focus on gene expression data without considering clinical characteristics. Therefore, this study aimed to establish a predictive risk model combining metabolic enzyme genes and clinicopathological characteristics to predict the overall survival in patients with breast cancer.Methods: Transcriptomics and corresponding clinical data for patients with breast cancer were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Differentially expressed metabolic genes between tumors and normal tissues were identified in the TCGA dataset (training dataset). A prognostic model was then built using univariate and multifactorial Cox proportional hazards regression analyses in the training dataset. The capability of the predictive model was then assessed using the receiver operating characteristic in both datasets. Pathway enrichment analysis and immune cell infiltration were performed using Kyoto Encyclopedia of Genes and Genomes (KEGG)/Gene Ontology (GO) enrichment and CIBERSORT algorithm, respectively.Results: In breast cancer and normal tissues, 212 metabolic enzyme genes were differentially expressed. The predictive model included four factors: age, stage, and expression of SLC35A2 and PLA2G10. Patients with breast cancer were classified into high- and low-risk groups based on the model; the high-risk group had a significantly poorer overall survival rate than the low-risk group. Furthermore, the two risk groups showed different activation of pathways and alterations in the properties of tumor microenvironment-infiltrating immune cells.Conclusion: We developed a powerful model to predict prognosis in patients with breast cancer by combining the gene expression of metabolic enzymes with clinicopathological characteristics.

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“…A breast cancer survival study in a northern state within peninsular Malaysia showed a remarkably favourable five-year survival rate of 72.9% ( n = 2166) [ 36 ]. Meanwhile, the five-year survival rate found in our study is approximately similar to the previously analysed nationwide study of 61.9% ( n = 17,009); thus, this suggests there are regional differences in cancer prognoses that necessitate the inclusion of centres across different regions within Malaysia.…”

Section: Discussionmentioning

confidence: 99%

Development of Predictive Models for Survival among Women with Breast Cancer in Malaysia

Kadir

Yaacob

Yusof

et al. 2022

IJERPH

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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.

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A comparison of breast cancer survival across different age groups: a multicentric database study in Penang, Malaysia

Abstract: SHORT RUNNING HEAD Breast cancer survival in different age group CONFLICTS OF INTEREST OF ALL LISTED AUTHORSKing Fang Tan: The author has no conflicts of interest to declare for this study.

Cited by 21 publications

References 20 publications

Survival Outcomes in Breast Cancer Patients and Associated Factors in a Border Province of Thailand: A Hospital-based Review

Survival Outcomes in Breast Cancer Patients and Associated Factors in a Border Province of Thailand: A Hospital-based Review

A Metabolic Gene Signature to Predict Breast Cancer Prognosis

Development of Predictive Models for Survival among Women with Breast Cancer in Malaysia

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