Distribution of virulence genes and the molecular epidemiology of Streptococcus pyogenes clinical isolates by emm and multilocus sequence typing methods.

BACKGROUND: Streptococcus pyogenes has a variety of virulence factors and the predominant invasive strains differ according to specific emm types and geographical orientation. Although emm typing is commonly used as the gold standard method for the molecular characterisation, multilocus sequence typing (MLST) has become an important tool for comparing the genetic profiles globally. This study aimed to screen selected virulence genes from invasive and non-invasive clinical samples and to characterise the molecular epidemiology by emm typing and MLST methods. MATERIALS AND METHODS: A total of 42 S. pyogenes isolates from invasive and non-invasive samples collected from two different tertiary hospitals were investigated for the distribution of virulence factors and their molecular epidemiology by emm and multilocus sequence typing methods. Detection of five virulence genes (speA, speB, speJ, ssa and sdaB) was performed using multiplex polymerase chain reaction (PCR) using the standard primers and established protocol. Phylogenetic tree branches were constructed from sequence analysis utilised by neighbour joining method generated from seven housekeeping genes using MEGA X software. RESULTS: Multiplex PCR analysis revealed that sdaB/speF (78.6%) and speB (61.9%) were the predominant virulence genes. Regardless of the type of invasiveness, diverse distribution of emm types/subtypes was noted which comprised of 27 different emm types/subtypes. The predominant emm types/subtypes were emm63 and emm18 with each gene accounted for 11.8% whereas 12% for each gene was noted for emm28, emm97.4 and emm91. The MLST revealed that the main sequence type (ST) in invasive samples was ST402 (17.7%) while ST473 and ST318 (12% for each ST) were the major types in non-invasive samples. Out of 18 virulotypes, Virulotype A (five genes, 55.6%) and Virulotype B (two genes, 27.8%) were the major virulotypes found in this study. Phylogenetic analysis indicated the presence of seven different clusters of S. pyogenes. Interestingly, Cluster VI showed that selected emm/ST types such as emm71/ST318 (n=2), emm70.1/ST318 (n=1), emm44/ST31 (n=1) and emm18/ST442 (n=1) have clustered within a common group (Virulotype A) for both hospitals studied. CONCLUSION: The present study showed that group A streptococcci (GAS) are genetically diverse and possess virulence genes regardless of their invasiveness. Majority of the GAS exhibited no restricted pattern of virulotypes except for a few distinct clusters. Therefore, it can be concluded that virulotyping is partially useful for characterising a heterogeneous population of GAS in hospitals.

The importance of using a right test method in diagnosing leptospirosis.

Leptospirosis is a common febrile illness in Malaysia. The disease is caused by pathogenic bacteria called leptospires that are transmitted directly or indirectly from animals to humans via contaminated water or soil. It is a potentially serious but treatable disease. Its symptoms may mimic those of other unrelated febrile illnesses such as dengue, influenza, meningitis, hepatitis or viral haemorrhagic fevers. The spectrum of the disease is extremely wide, ranging from subclinical infection to a severe syndrome of multiorgan infection with high mortality. The diagnosis requires high suspicion with history of exposure to water or environment possibly contaminated with infected animal urine. This is a case of a 13 year-oldgirl with no known medical illness, and a history of exposure to outdoor activities. However, paired sera for leptospirosis serology was not diagnostic. She then developed septic shock on day 14 of illness. But due to high suspicion of leptospirosis, antibiotic therapy was upgraded to ceftriaxone and samples were sent for further testing which revealed that leptospires were detected in the urine, using molecular technique. She improved after treated as leptospirosis.

The importance of using a right test method in diagnosing leptospirosis

@#Leptospirosis is a common febrile illness in Malaysia. The disease is caused by pathogenic bacteria called leptospires that are transmitted directly or indirectly from animals to humans via contaminated water or soil. It is a potentially serious but treatable disease. Its symptoms may mimic those of other unrelated febrile illnesses such as dengue, influenza, meningitis, hepatitis or viral haemorrhagic fevers. The spectrum of the disease is extremely wide, ranging from subclinical infection to a severe syndrome of multiorgan infection with high mortality. The diagnosis requires high suspicion with history of exposure to water or environment possibly contaminated with infected animal urine. This is a case of a 13 year-oldgirl with no known medical illness, and a history of exposure to outdoor activities. However, paired sera for leptospirosis serology was not diagnostic. She then developed septic shock on day 14 of illness. But due to high suspicion of leptospirosis, antibiotic therapy was upgraded to ceftriaxone and samples were sent for further testing which revealed that leptospires were detected in the urine, using molecular technique. She improved after treated as leptospirosis.

Low Breast Conserving Surgery (BCS) rates in public hospitals in Malaysia: The effect of stage and ethnicity.

INTRODUCTION: Breast-conserving surgery (BCS) with radiation therapy is the procedure of choice for early-stage breast cancer. Survival and locoregional recurrence is non-inferior to mastectomy, with superior cosmetic and psycho-social outcomes. Differing health systems have demonstrated a wide variation in the rate of BCS. Little is known about the rate of BCS and factors influencing its practice in middle resource countries. This study aims to examine the BCS rates in Malaysia and to identify factors influencing its uptake. METHODOLOGY: This is a multi-centre, cross-sectional study involving the University of Malaya Medical Centre (UMMC), Queen Elizabeth II Hospital (QEH), and Tengku Ampuan Rahimah Hospital (TARH). Patients diagnosed with invasive breast cancer from January 2014 to December 2015 were included, excluding stromal cancers and lymphomas. Univariate and multivariate analyses identified factors influencing BCS. RESULTS: A total of 1005 patients were diagnosed with breast cancer in the allocated time frame. Excluding incomplete records and those who did not have surgery, 730 patients were analysed. Overall BCS rate was 32.9%. The BCS rate was highest at QEH (54.1%), followed by UMMC (29.5%), and TARH (17.4%). 16.9% had BCS after neoadjuvant therapy. Factors influencing BCS uptake included age, ethnic group, breast-surgeon led services, AJCC Stage, tumour size, HER-2 expression, and tumour grade. CONCLUSIONS: The rate of BCS in Malaysia is low. A wide variation of rate exists among the studied hospitals. Younger age, earlier AJCC stage, and the presence of a Breast sub-specialist surgeon, would make it more likely that the patient has her breast conserved.

Evaluation of Ge-doped silica fibre TLDs for in vivo dosimetry during intraoperative radiotherapy.

Ge-doped silica fibre (GDSF) thermoluminescence dosimeters (TLD) are non-hygroscopic spatially high-resolution radiation sensors with demonstrated potential for radiotherapy dosimetry applications. The INTRABEAM® system with spherical applicators, one of a number of recent electronic brachytherapy sources designed for intraoperative radiotherapy (IORT), presents a representative challenging dosimetry situation, with a low keV photon beam and a desired rapid dose-rate fall-off close-up to the applicator surface. In this study, using the INTRABEAM® system, investigations were made into the potential application of GDSF TLDs for in vivo IORT dosimetry. The GDSFs were calibrated over the respective dose- and depth-range 1 to 20 Gy and 3 to 45 mm from the x-ray probe. The effect of different sizes of spherical applicator on TL response of the fibres was also investigated. The results show the GDSF TLDs to be applicable for IORT dose assessment, with the important incorporated correction for beam quality effects using different spherical applicator sizes. The total uncertainty in use of this type of GDSF for dosimetry has been found to range between 9.5% to 12.4%. Subsequent in vivo measurement of skin dose for three breast patients undergoing IORT were performed, the measured doses being below the tolerance level for acute radiation toxicity.

Breast-conserving surgery versus mastectomy in young women with breast cancer in Asian settings.

Background: Mastectomy rates among women with early breast cancer in Asia have traditionally been high. This study assessed trends in the surgical management of young women with early-stage breast cancer in Asian settings. Survival in women treated with breast-conserving surgery (BCS; lumpectomy with adjuvant radiotherapy) and those undergoing mastectomy was compared. Methods: Young women (aged less than 50 years) newly diagnosed with stage I or II (T1-2 N0-1 M0) breast cancer in four hospitals in Malaysia, Singapore and Hong Kong in 1990-2012 were included. Overall survival (OS) was compared for patients treated by BCS and those who had a mastectomy. Propensity score analysis was used to account for differences in demographic, tumour and treatment characteristics between the groups. Results: Some 63·5 per cent of 3536 women underwent mastectomy. Over a 15-year period, only a modest increase in rates of BCS was observed. Although BCS was significantly associated with favourable prognostic features, OS was not significantly different for BCS and mastectomy; the 5-year OS rate was 94·9 (95 per cent c.i. 93·5 to 96·3) and 92·9 (91·7 to 94·1) per cent respectively. Inferences remained unchanged following propensity score analysis (hazard ratio for BCS versus mastectomy: 0·81, 95 per cent c.i. 0·64 to 1·03). Conclusion: The prevalence of young women with breast cancer treated by mastectomy remains high in Asian countries. Patients treated with BCS appear to survive as well as those undergoing mastectomy.

Global Disparities in Breast Cancer Genetics Testing, Counselling and Management.

Hereditary breast cancers, mainly due to BRCA1 and BRCA2 mutations, account for only 5-10% of this disease. The threshold for genetic testing is a 10% likelihood of detecting a mutation, as determined by validated models such as BOADICEA and Manchester Scoring System. A 90-95% reduction in breast cancer risk can be achieved with bilateral risk-reducing mastectomy in unaffected BRCA mutation carriers. In patients with BRCA-associated breast cancer, there is a 40% risk of contralateral breast cancer and hence risk-reducing contralateral mastectomy is recommended, which can be performed simultaneously with surgery for unilateral breast cancer. Other options for risk management include surveillance by mammogram and breast magnetic resonance imaging, and chemoprevention with hormonal agents. With the advent of next-generation sequencing and development of multigene panel testing, the cost and time taken for genetic testing have reduced, making it possible for treatment-focused genetic testing. There are also drugs such as the PARP inhibitors that specifically target the BRCA mutation. Risk management multidisciplinary clinics are designed to quantify risk, and offer advice on preventative strategies. However, such services are only possible in high-income settings. In low-resource settings, the prohibitive cost of testing and the lack of genetic counsellors are major barriers to setting up a breast cancer genetics service. Family history is often not well documented because of the stigma associated with cancer. Breast cancer genetics services remain an unmet need in low- and middle-income countries, where the priority is to optimise access to quality treatment.

Machine Learning and Deep Learning Approaches in Breast Cancer Survival Prediction Using Clinical Data.

Breast cancer survival prediction can have an extreme effect on selection of best treatment protocols. Many approaches such as statistical or machine learning models have been employed to predict the survival prospects of patients, but newer algorithms such as deep learning can be tested with the aim of improving the models and prediction accuracy. In this study, we used machine learning and deep learning approaches to predict breast cancer survival in 4,902 patient records from the University of Malaya Medical Centre Breast Cancer Registry. The results indicated that the multilayer perceptron (MLP), random forest (RF) and decision tree (DT) classifiers could predict survivorship, respectively, with 88.2 %, 83.3 % and 82.5 % accuracy in the tested samples. Support vector machine (SVM) came out to be lower with 80.5 %. In this study, tumour size turned out to be the most important feature for breast cancer survivability prediction. Both deep learning and machine learning methods produce desirable prediction accuracy, but other factors such as parameter configurations and data transformations affect the accuracy of the predictive model.

Low Lifetime Risk of Contralateral Breast Cancer in a Middle-Income Asian Country: Evidence to Guide Post-treatment Surveillance.

BACKGROUND: The rate of contralateral risk-reducing mastectomy (CRRM) is increasing in the West with controversial evidence of improved survival in early breast cancer patients. Although uptake of CRRM in Asia appears low, the trends may rise, and there is currently an urgent need to provide evidence for informed decision-making in clinical practice. This study aims to determine the risk of contralateral breast cancer (CBC) and its associated factors in an Asian setting. METHOD: A total of 2937 newly diagnosed patients with stage I and stage II breast cancer in University Malaya Medical Centre between Jan 1993 to Dec 2012 were included in the study. Multinomial logistic regression analysis allowing death to compete with CBC as a study outcome was used; patients with unilateral breast cancer who were alive were taken as reference. A stepwise backward regression analysis including age at diagnosis, ethnicity, family history of breast cancer, TNM stage, hormonal receptor status, HER2 status, chemotherapy, radiotherapy, and hormone therapy was conducted. RESULTS: Fifty women developed CBC, over a median follow-up of 6 years. The 5- and 10-year cumulative risk of contralateral breast cancer was 1.0% (95% CI 0.6-1.4%) and 2.8% (95% CI 2.0-3.6%), respectively. Young age at diagnosis of first cancer, positive family history, and stage I disease were independent predictors of CBC. DISCUSSION: The current study suggests that the risk of CBC is very low in a Southeast Asian setting. Any recommendations or practice of CRRM should be reviewed with caution and patients must be counseled appropriately.

Identification of germline alterations in breast cancer predisposition genes among Malaysian breast cancer patients using panel testing.

Although an association between protein-truncating variants and breast cancer risk has been established for 11 genes, only alterations in BRCA1, BRCA2, TP53 and PALB2 have been reported in Asian populations. Given that the age of onset of breast cancer is lower in Asians, it is estimated that inherited predisposition to breast cancer may be more significant. To determine the potential utility of panel testing, we investigated the prevalence of germline alterations in 11 established and 4 likely breast cancer genes in a cross-sectional hospital-based cohort of 108 moderate to high-risk breast cancer patients using targeted next generation sequencing. Twenty patients (19%) were identified to carry deleterious mutations, of whom 13 (12%) were in the BRCA1 or BRCA2, 6 (6%) were in five other known breast cancer predisposition genes and 1 patient had a mutation in both BRCA2 and BARD1. Our study shows that BRCA1 and BRCA2 account for the majority of genetic predisposition to breast cancer in our cohort of Asian women. Although mutations in other known breast cancer genes are found, the functional significance and breast cancer risk have not yet been determined, thus limiting the clinical utility of panel testing in Asian populations.

Bioengineered riboflavin in nanotechnology.

Riboflavin (RF) is an essential water-soluble vitamin with unique biological and physicochemical properties such as transporterspecific cell internalization, implication in redox reactions, fluorescence and photosensitizing. Due to these features RF attracted researchers in various fields from targeted drug delivery and tissue engineering to optoelectronics and biosensors. In this review we will give a brief reminder of RF chemistry, its optical, photosensitizing properties, RF transporter systems and its role in pathologies. We will point a special attention on the recent findings concerning RF applications in nanotechnologies such as RF functionalized nanoparticles, polymers, biomolecules, carbon nanotubes, hydrogels and implants for tissue engineering.

Multiple ambler class A ESBL genes among Klebsiella pneumoniae isolates in a Malaysian district hospital.

Detailed reports regarding the distribution and activity of extended-spectrum beta-lactamase (ESBL)-producing Klebsiella pneumoniae isolates are currently not widely available in the Malaysian setting. This study was conducted to determine the ESBL genes distribution rate, phenotypic detection, and antimicrobial susceptibility patterns among betalactam resistant Klebsiella pneumoniae isolated from a Malaysian district hospital. K. pneumoniae isolates were collected from a microbiology laboratory at Hospital Pakar Sultanah Fatimah, Malaysia. Following exclusion and inclusion criteria, 141 isolates were selected for this study. K. pneumoniae was identified by phenotypic method, whilst antibiotics' susceptibility patterns were determined by the Kirby-Bauer method, as described in Clinical Laboratory Standard Institute (CLSI) guidelines (Oxoid, UK; Becton-Dickenson, USA). Detection of Ambler Group A ESBL gene (blaSHV, blaTEM, blaCTX-M-1, blaCTX-M-2, blaCTX-M-8, blaCTX-M-9, and blaCTX-M-25) was done using polymerase chain reaction (PCR). ESBL genes were found in 85.8% of K. pneumoniae (121 of 141) isolates. Only blaSHV, blaTEM, blaCTX-M-1, and blaCTX-M-9 were detected among K. pneumoniae isolates with distribution rates of 75.2% (106 of 141), 41.1% (58 of 141), 44% (62 of 141), and 0.7% (1 of 141), respectively. There was no blaCTX-M-2, blaCTX-M-8, or blaCTX-M-25 detected from any isolates in this study. Sequencing of representative amplicons revealed blaSHV as SHV-12, blaTEM as TEM-1, blaCTX-M-1 as CTX-M-15, and blaCTX-M-9 as CTX-M-18. The phenotypic detection rate of ESBL was 71.6% (101 of 141), whilst 9.2% (13 of 141) were positive for carbapenemase. AmpC betalactamase was detected in 22% (31 of 141) of all isolates. Antibiotic resistance was between 44.6% (netilmicin) and 97.2% (cefotaxime). Based on ESBL genes distribution, blaSHV was a predominant gene found in one of Malaysian district hospitals, notwithstanding having blaTEM, blaCTX-M-1, and blaCTX-M-9. Despite carrying multiple ESBL genes, some strains were positive for carbapenemase or AmpC betalactamase, which resulted in high antimicrobial resistance rates.

Multiple ambler class A ESBL genes among Klebsiella pneumoniae isolates in a Malaysian district hospital

Detailed reports regarding the distribution and activity of extended-spectrum beta-lactamase (ESBL)-producing Klebsiella pneumoniae isolates are currently not widely available in the Malaysian setting. This study was conducted to determine the ESBL genes distribution rate, phenotypic detection, and antimicrobial susceptibility patterns among betalactam resistant Klebsiella pneumoniae isolated from a Malaysian district hospital. K. pneumoniae isolates were collected from a microbiology laboratory at Hospital Pakar Sultanah Fatimah, Malaysia. Following exclusion and inclusion criteria, 141 isolates were selected for this study. K. pneumoniae was identified by phenotypic method, whilst antibiotics’ susceptibility patterns were determined by the Kirby-Bauer method, as described in Clinical Laboratory Standard Institute (CLSI) guidelines (Oxoid, UK; Becton-Dickenson, USA). Detection of Ambler Group A ESBL gene (blaSHV, blaTEM, blaCTX-M-1, blaCTX-M-2, blaCTX-M-8, blaCTX-M-9, and blaCTX-M-25) was done using polymerase chain reaction (PCR). ESBL genes were found in 85.8% of K. pneumoniae (121 of 141) isolates. Only blaSHV, blaTEM, blaCTX-M-1, and blaCTX-M-9 were detected among K. pneumoniae isolates with distribution rates of 75.2% (106 of 141), 41.1% (58 of 141), 44% (62 of 141), and 0.7% (1 of 141), respectively. There was no blaCTX-M-2, blaCTX-M-8, or blaCTX-M-25 detected from any isolates in this study. Sequencing of representative amplicons revealed blaSHV as SHV-12, blaTEM as TEM-1, blaCTX-M-1 as CTX-M-15, and blaCTX-M-9 as CTX-M-18. The phenotypic detection rate of ESBL was 71.6% (101 of 141), whilst 9.2% (13 of 141) were positive for carbapenemase. AmpC betalactamase was detected in 22% (31 of 141) of all isolates. Antibiotic resistance was between 44.6% (netilmicin) and 97.2% (cefotaxime). Based on ESBL genes distribution, blaSHV was a predominant gene found in one of Malaysian district hospitals, notwithstanding having blaTEM, blaCTX-M-1, and blaCTX-M-9. Despite carrying multiple ESBL genes, some strains were positive for carbapenemase or AmpC betalactamase, which resulted in high antimicrobial resistance rates.

Breast Cancer Outcomes as Defined by the Estrogen Receptor, Progesterone Receptor, and Human Growth Factor Receptor-2 in a Multi-ethnic Asian Country.

INTRODUCTION: Breast cancer can be divided into four subtypes based on the expressions of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor-2 (HER2). Each subtype has different clinicopathological features and outcomes. OBJECTIVE: To compare the clinicopathological features and survival of ER and/or PR positive HER2 negative (ER+PR+HER2-, ER+PR-HER2- or ER-PR+HER2-), ER and/or PR positive HER2 positive (ER+PR+HER2+, ER+PR-HER2+ or ER-PR+HER2+), ER negative PR negative HER2 positive (ER-PR-HER2+), and ER negative PR negative HER2 negative (ER-PR-HER2-) subtypes. METHODS: 1957 patients with Stage 1-3 breast carcinoma diagnosed between Jan 2005 and Dec 2011 were categorized into the four subtypes. The clinicopathological features between the subtypes were compared using χ (2) test. Kaplan-Meier analysis was performed to estimate 5-year overall survival. Multivariate Cox regression was used to determine the association between subtypes and mortality adjusted for age, ethnicity, stage, pathological features, and treatment. RESULTS: ER-PR-HER2+ and ER-PR-HER2- subtypes were associated with younger age, larger tumors, and higher grade. There was no difference in the 5-year survival of the ER-PR-HER2+ and ER-PR-HER2- subtypes (75.1 and 74.4 %, respectively) and survival was poorer than in the ER and/or PR positive HER2 negative and ER and/or PR positive HER2 positive subtypes (87.1 and 83.1 %, respectively). Only 9.5 % of women with HER2 positive breast cancer had access to trastuzumab. CONCLUSION: In a low resource setting with limited access to trastuzumab, there is no difference in survival between the ER-PR-HER2+ and ER-PR-HER2- subtypes of breast cancer.

Utility of pre-treatment neutrophil-lymphocyte ratio and platelet-lymphocyte ratio as prognostic factors in breast cancer.

BACKGROUND: Peripheral blood-derived inflammation-based scores such as the neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) have recently been proposed as prognostic markers in solid tumours. Although evidence to support these markers as unfavourable prognostic factors is more compelling in gastrointestinal cancers, very little is known of their impact on breast cancer. We investigated the association between the NLR and PLR, and overall survival after breast cancer. METHODS: Data from the University of Malaya Medical Centre Breast Cancer Registry was used. Of 2059 consecutive patients diagnosed from 2000 to 2008, we included 1435 patients with an available pre-treatment differential blood count (∼70%). Patients were stratified into quintiles of the NLR/PLR. Multivariable Cox regression was used to determine the independent prognostic significances of the NLR/PLR. RESULTS: Compared with the first quintile of the NLR, women in quintile 5 were younger, had bigger tumours, nodal involvement, distant metastases and higher tumour grades. Higher NLR quintiles were significantly associated with poorer survival with a 5-year relative survival ratio (RSR) of 76.4% (95% CI: 69.6-82.1%) in quintile 1, 79.4% (95% CI: 74.4-83.7%) in quintile 2, 72.1% (95% CI: 66.3-77.3%) in quintile 3, 65.6% (95% CI: 59.8-70.8%) in quintile 4 and 51.1% (95% CI: 43.3-58.5%) in quintile 5. Following adjustment for demography, tumour characteristics, treatment and the PLR, the adjusted hazard ratio (HR) for quintile 5 vs quintile 1 was 1.50 (95% CI: 1.08-1.63); Ptrend=0.004. Results were unchanged when the NLR was analysed as a dichotomous variable using different cutoff points. Although patients in PLR quintile 5 had lower survival than in quintile 1 (5-year RSR: 53.2% (95% CI: 46.9-59.2%) vs 77.0% (95% CI: 70.9-82.2%)), this association was not significant after multivariable adjustment. However, a PLR >185 was significantly associated with poorer survival; adjusted HR: 1.25 (95% CI: 1.04-1.52). CONCLUSIONS: Both the NLR and PLR are independently associated with an increased risk of mortality in breast cancer. Their added value in the prognostication of breast cancer in clinical practice warrants investigation.

The Will Rogers phenomenon in the staging of breast cancer - does it matter?

INTRODUCTION: Changes in the American Joint Commission on Cancer staging for breast cancer occurred when the 5th Edition was updated to the 6th Edition. OBJECTIVE: To investigate how these changes affected stage and survival. METHODS: 3127 cases of breast cancer were restaged. RESULTS: Late stages increased from 27.7% to 38.1%. The five-year survival improved in Stage 2 (82.9-86.1%) and Stage 3 (50.6-59%). DISCUSSION: Stage shift leads to an erroneous impression that women are presenting with later stages and stage-specific survival is improving. CONCLUSION: Standardizing cancer staging is important when reporting stage and survival in different time periods.

Breast health in developing countries.

Breast cancer is one of the leading cancers world-wide. While the incidence in developing countries is lower than in developed countries, the mortality is much higher. Of the estimated 1 600 000 new cases of breast cancer globally in 2012, 794 000 were in the more developed world compared to 883 000 in the less developed world; however, there were 198 000 deaths in the more developed world compared to 324 000 in the less developed world (data from Globocan 2012, IARC). Survival from breast cancer depends on two main factors--early detection and optimal treatment. In developing countries, women present with late stages of disease. The barriers to early detection are physical, such as geographical isolation, financial as well as psychosocial, including lack of education, belief in traditional medicine and lack of autonomous decision-making in the male-dominated societies that prevail in the developing world. There are virtually no population-based breast cancer screening programs in developing countries. However, before any screening program can be implemented, there must be facilities to treat the cancers that are detected. Inadequate access to optimal treatment of breast cancer remains a problem. Lack of specialist manpower, facilities and anticancer drugs contribute to the suboptimal care that a woman with breast cancer in a low-income country receives. International groups such as the Breast Health Global Initiative were set up to develop economically feasible, clinical practice guidelines for breast cancer management to improve breast health outcomes in countries with limited resources.

Prediction of lymph node involvement in patients with breast tumors measuring 3-5 cm in a middle-income setting: the role of CancerMath.

BACKGROUND: In settings with limited resources, sentinel lymph node biopsy (SNB) is only offered to breast cancer patients with small tumors and a low a priori risk of axillary metastases. OBJECTIVE: We investigated whether CancerMath, a free online prediction tool for axillary lymph node involvement, is able to identify women at low risk of axillary lymph node metastases in Malaysian women with 3-5 cm tumors, with the aim to offer SNB in a targeted, cost-effective way. METHODS: Women with non-metastatic breast cancers, measuring 3-5 cm were identified within the University Malaya Medical Centre (UMMC) breast cancer registry. We compared CancerMath-predicted probabilities of lymph node involvement between women with versus without lymph node metastases. The discriminative performance of CancerMath was tested using receiver operating characteristic (ROC) analysis. RESULTS: Out of 1,017 patients, 520 (51 %) had axillary involvement. Tumors of women with axillary involvement were more often estrogen-receptor positive, progesterone-receptor positive, and human epidermal growth factor receptor (HER)-2 positive. The mean CancerMath score was higher in women with axillary involvement than in those without (53.5 vs. 51.3, p = 0.001). In terms of discrimination, CancerMath performed poorly, with an area under the ROC curve of 0.553 (95 % confidence interval CI 0.518-0.588). Attempts to optimize the CancerMath model by adding ethnicity and HER2 to the model did not improve discriminatory performance. CONCLUSION: For Malaysian women with tumors measuring 3-5 cm, CancerMath is unable to accurately predict lymph node involvement and is therefore not helpful in the identification of women at low risk of node-positive disease who could benefit from SNB.

The effects of co-morbidity in defining major depression subtypes associated with long-term course and severity.

BACKGROUND: Although variation in the long-term course of major depressive disorder (MDD) is not strongly predicted by existing symptom subtype distinctions, recent research suggests that prediction can be improved by using machine learning methods. However, it is not known whether these distinctions can be refined by added information about co-morbid conditions. The current report presents results on this question. METHOD: Data came from 8261 respondents with lifetime DSM-IV MDD in the World Health Organization (WHO) World Mental Health (WMH) Surveys. Outcomes included four retrospectively reported measures of persistence/severity of course (years in episode; years in chronic episodes; hospitalization for MDD; disability due to MDD). Machine learning methods (regression tree analysis; lasso, ridge and elastic net penalized regression) followed by k-means cluster analysis were used to augment previously detected subtypes with information about prior co-morbidity to predict these outcomes. RESULTS: Predicted values were strongly correlated across outcomes. Cluster analysis of predicted values found three clusters with consistently high, intermediate or low values. The high-risk cluster (32.4% of cases) accounted for 56.6-72.9% of high persistence, high chronicity, hospitalization and disability. This high-risk cluster had both higher sensitivity and likelihood ratio positive (LR+; relative proportions of cases in the high-risk cluster versus other clusters having the adverse outcomes) than in a parallel analysis that excluded measures of co-morbidity as predictors. CONCLUSIONS: Although the results using the retrospective data reported here suggest that useful MDD subtyping distinctions can be made with machine learning and clustering across multiple indicators of illness persistence/severity, replication with prospective data is needed to confirm this preliminary conclusion.