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The subtyping of breast cancer based on features of tumour biology such as hormonal receptor and HER2 status has led to increasingly patient-specific treatment and thus improved outcomes. However, such subgroups may not be sufficiently informed to best predict outcome and/or treatment response. The incorporation of multi-modal data may identify unexpected and actionable subgroups to enhance disease understanding and improve outcomes. This retrospective cross-sectional study used the cancer registry Surveillance, Epidemiology and End Results (SEER), which represents 28% of the U.S. population. We included adult female patients diagnosed with breast cancer in 2010. Latent class analysis (LCA), a data-driven technique, was used to identify clinically homogeneous subgroups (\"endophenotypes\") of breast cancer from receptor status (hormonal receptor and HER2), clinical, and demographic data and each subgroup was explored using Bayesian networks. Included were 44,346 patients, 1257 (3%) of whom had distant organ metastases at diagnosis. Four endophenotypes were identified with LCA: 1) \"Favourable biology\" had entirely local disease with favourable biology, 2) \"HGHR-\" had the highest incidence of HR- receptor status and highest grade but few metastases and relatively good outcomes, 3) \"HR+ bone\" had isolated bone metastases and uniform receptor status (HR+/HER2-), and 4) \"Distant organ spread\" had high metastatic burden and poor survival. Bayesian networks revealed clinically intuitive interactions between patient and disease features. We have identified four distinct subgroups of breast cancer using LCA, including one unexpected group with good outcomes despite having the highest average histologic grade and rate of HR- tumours. Deeper understanding of subgroup characteristics can allow us to 1) identify actionable group properties relating to disease biology and patient features and 2) develop group-specific diagnostics and treatments.

There are limited data on the effects of trastuzumab on the right ventricle (RV). Therefore, we sought to evaluate the temporal changes in right ventricular (RV) structure and function as measured by cardiovascular magnetic resonance (CMR), and their relationship with left ventricular (LV) structure and function in breast cancer patients treated with trastuzumab. Prospective, longitudinal, observational study involving 41 women with HER2+ breast cancer who underwent serial CMR at baseline, 6, 12, and 18 months after initiation of trastuzumab. A single blinded observer measured RV parameters on de-identified CMRs in a random order. Linear mixed models were used to investigate temporal changes in RV parameters. Of the 41 women (age 52 ± 11 years), only one patient experienced trastuzumab-induced cardiotoxicity. Compared to baseline, there were small but significant increases in the RV end-diastolic volume at 6 months (p = 0.002) and RV end-systolic volume at 6 and 12 months (p < 0.001 for both), but not at 18 months (p = 0.82 and 0.13 respectively). RV ejection fraction (RVEF), when compared to baseline (58.3%, 95% CI 57.1–59.5%), showed corresponding decreases at 6 months (53.9%, 95% CI 52.5–55.4%, p < 0.001) and 12 months (55%, 95% CI 53.8–56.2%, p < 0.001) that recovered at 18 months (56.6%, 95% CI 55.1–58.0%, p = 0.08). Although the temporal pattern of changes in LVEF and RVEF were similar, there was no significant correlation between RVEF and LVEF at baseline (r = 0.29, p = 0.07) or between their changes at 6 months (r = 0.24, p = 0.17). In patients receiving trastuzumab without overt cardiotoxicity, there is a subtle but significant deleterious effect on RV structure and function that recover at 18 months, which can be detected by CMR. Furthermore, monitoring of LVEF alone may not be sufficient in detecting early RV injury. These novel findings provide further support for CMR in monitoring early cardiotoxicity. ClinicalTrials.gov Identifier: NCT01022086. Date of registration: November 27, 2009.

Human wellbeing indices can shed light on a society's quality of life. This study ranks human wellbeing by employing objective and subjective indicators of quality of life for hundred districts of Pakistan. Households level data used for the analysis includes 'The Pakistan Social and Living Standards Measurement Survey' for the year 2006–2007. The human wellbeing is examined in four domains: education, health, living conditions and economic situation. Principal component analysis is employed for indexing human wellbeing, rated in five quintiles are generated. The paper demonstrates the importance of education, health and living condition domains in determining the human wellbeing. Objective indicators of education i.e., adult literacy rate, net primary enrolment and gender equality in education are important variables in ranking of districts. Economic status of the households and communities are important variables in subjective perception of wellbeing. The results indicate substantial variation in human wellbeing among districts of Pakistan It may be considered that disparity in objective condition and in subjective perceptions are adequately depicting wellbeing differences. Finally, it is argued that objective indicators and subjective wellbeing measures are needed in unison to understand human quality of life and to make informed policy decisions.

The aim of the paper is to explore the variation in the quality of life by using thirty-five indicators relating to the quality of persons and the quality of conditions to rank districts and tehsils (sub-districts) of the Punjab. The study demonstrates the importance of access to middle and secondary education, access to health facilities and household utilities, etc. The quality of life ranking indicates that districts which have big cities are categorised as 'good' quality of life regions. It is important to note that the majority of the districts and tehsils from northern and central Punjab are doing better in terms of quality of life. However, regions with 'poor' quality of life are identified as the target for special resource allocations.

In recent years, development policy has increasingly been recognised that a household's sense of well-being depends not just on its average income or expenditures, but also on the risks it faces. Hence vulnerability is a more satisfactory measure of welfare. Application of the methodology to data from Pakistan shows that in 2010 households faced on average a 20.7 percent of poverty level while 34.4 percent chance of becoming poor in the future. When decomposing vulnerability into poor and non-poor households, it was figured out that 95 percent poor household are vulnerable and 18 percent non-poor households are vulnerable. The model measuring determinants of vulnerability indicate that households head with no education, large family size, high number of dependents, poverty status, lack of productive assets, agricultural shocks, high cost of shock and rural residence have significantly higher probability of being poor in future. Finally, it can be concluded that policy makers should be aware of social risk management strategies as an integral part of poverty alleviation programme.

The objective of this paper is to investigate the incidence of different types of shocks in rural Pakistan and identify the household characteristics that are associated with this phenomenon. It is observed that one-third of households experience an adverse shock, be it natural/agricultural, economic, social or relating to health. The natural/agricultural shocks have major share in the total burden of shocks while the households' coping mechanism is overwhelmingly informal and largely asset-based. The poorest of the households adopt behaviour-based strategies like reducing food consumption, employ child labour, work more hours etc. Overall, households of with less educated heads, high dependency ratio, large household size, low welfare ratio, farm household, ownership of land and residing in south Punjab or Sindh are more vulnerable to suffer shocks, particularly of income. Vulnerability in terms of a decline in consumption is observed for households who are hit by natural/agricultural or health shocks. For all these reasons, a gradual shift from traditional emergency relief measures towards ex-ante actions to reduce and mitigate hazard impacts should be encouraged along with non-exploitative credit and more effective safety nets.

The vast, sprawling and densely populated province of Punjab, while predominantly agricultural, is marked by considerable regional disparities. An attempt has been made in this paper to see to what extent the differences in the human and social development in its various districts is there. The study exhibits that those regions which are ranked as lagging districts have high disparities in terms of human development and social development with high urban and rural poverty estimates. It is clearly revealed that aggregate national figures mask vast sub regional disparities and speedy development in some regions may not necessarily elevate lagging regions.