An empirical study on quality of life and related factors of Pakistani breast cancer survivors

Health-related quality of life in rural cancer survivors compared with their urban counterparts: a systematic review

PURPOSE

We conducted a systematic review to describe health-related quality of life (HRQOL) in rural cancer survivors (RCS), and compare HRQOL between RCS and urban cancer survivors (UCS).

METHOD

We searched Medline, Embase, CINAHL Plus, and PsycINFO for studies with HRQOL in adult cancer survivors living in rural, regional, remote, and urban areas, who had completed definitive primary cancer treatment, without evidence of residual disease. Where available, we used normative and clinically important values to ascribe meaning to HRQOL data.

FINDINGS

Fifteen studies (16 papers) were included. Most were from the US (n = 8) and reported on breast cancer survivors (n = 9). Six HRQOL instruments, collecting data across 16 domains, were used. Three instruments were specific to the survivorship phase. Normative and clinical data were available for 12 studies. Compared with normative populations, RCS had clinically worse physical HRQOL (6/12 studies), better social/family (5/7), and functional (3/6) HRQOL, and there were no differences in emotional or/mental HRQOL (9/12). In six studies with rural-urban comparator groups and normative and clinically important data, RCS and UCS had clinically worse physical (3/6 and 2/6, respectively) and better social/family (3/4 and 2/4 studies, respectively) HRQOL than normative populations. Functional HRQOL was better in RCS (2/4 studies) than UCS and normative populations. In 3/6 studies, there were no clinical differences in emotional or/mental HRQOL between RCS, UCS, and normative populations.

CONCLUSION

Overall, HRQOL is not clearly better or worse in RCS than UCS. Future research should include different tumor types, rural residents, and survivorship-specific HRQOL instruments.

Resilience's impact on quality of life and post-traumatic growth in breast cancer patients during treatment

BACKGROUND

This article aims to examine how psychological resilience influences the interplay between quality of life and post-traumatic growth among breast cancer patients receiving follow-up care and treatment in Türkiye.

METHODS

The study involved 119 female individuals diagnosed with breast cancer who visited the Oncology outpatient clinic at a state hospital in Türkiye from January to September 2023. Data were gathered through the administration of a survey form and the utilization of several assessment tools, including the Adult Life Quality Scale in Cancer Survivors (QLACS), the Brief Resilience Scale (BRS), and the Post-traumatic Growth Inventory (PTGI). Data analysis was carried out using SPSS 25 software.

RESULTS

The participants demonstrated an inverse correlation between Post-Traumatic Growth (PTG) and two QLACS sub-dimensions, namely recurrence and family concern. Conversely, a positive association was identified between PTG and the advantages of dealing with cancer. Furthermore, a statistically significant positive association was established between BRS and all QLACS sub-dimensions, except for family concern and appearance. However, it was determined that psychological resilience did not act as a moderator in the relationship between PTG and QLACS.

CONCLUSION

It is important to enhance psychological resilience in women who have survived cancer at all stages of the cancer journey, including the years after treatment, to have a positive impact on post-traumatic growth and quality of life.

"Just give it to us straight!": a qualitative analysis of midwestern rural lung cancer survivors and caregivers about survivorship care experiences

PURPOSE

We assessed the experiences of rural lung cancer survivors and caregivers to understand and identify barriers to posttreatment survivorship care management.

METHODS

From May 2021 to June 2022, we conducted semi-structured interviews with a purposively sampled cohort. Participants were either posttreatment lung cancer survivors (within 5 years of their last active treatment) or caregivers of a lung cancer survivor. Interviews probed participants regarding survivorship care knowledge, implementation, and navigation. Two analysts inductively coded verbatim transcripts and conducted a thematic analysis.

RESULTS

We interviewed N = 21 participants: lung cancer survivors (76%) and caregivers (24%). Participants self-identified as Non-Hispanic White (100%), were at least 65 years old (77%), identified as male (62%), and previously smoked ≥ 5 packs over the lifetime (71%). The perspectives of survivors and caregivers were similar; thus, we analyzed them together. Themes related to survivorship care included (1) frustrations and uncertainty regarding unexpected barriers, (2) strategies to improve the delivery of posttreatment information, (3) strategies to remain positive and respond to emotional concerns of survivorship care, and (4) the impact of engaging and patient-centered care teams.

CONCLUSION

Given the limited access to lung cancer care resources in rural communities, our findings reveal that following a survivorship care program or plan requires a high level of individual resilience and community/interpersonal networking.

IMPLICATIONS FOR SURVIVORS

This study's findings can be applied to improve practice-based care for rural posttreatment lung cancer survivors and provide an impetus for developing tools to assist patient navigation toward community-based supportive care and care management resources.

Impact of Beta Blockers on Breast Cancer Incidence and Prognosis

Several studies have investigated the link between beta blockers (BB) and breast cancer outcomes but have reported mixed results. Our aim was to investigate the relationship between BB and breast cancer outcomes. Literatures investigating the relationship between BB and breast cancer outcomes were searched through PubMed and Embase. A total 43 articles were included by meta-analysis. We found BB increased breast cancer risk (n = 22, RR: 1.169, 95% CI: 1.063-1.285). We also found BB were associated with a lower overall survival (OS, n = 19, RR: 1.125, 95% CI: 1.078-1.173) and a higher recurrence risk (n = 8, RR: 1.130, 95% CI: 1.040-1.227) for breast cancer. Interestingly, subgroup analyses found only selective BB increased breast cancer risk (n = 5, RR: 1.766, 95% CI: 1.148-2.718) and recurrence risk (n = 2, RR: 1.168 -, 95% CI: 1.026-1.328) while only nonselective BB were associated with a lower OS (n = 4, RR: 1.135, 95% CI: 1.073-1.202) for breast cancer. Moreover, we found BB were associated with a significantly lower OS (n = 3, RR: 2.751, 95% CI: 1.213-6.238) and higher recurrence (n = 2, RR: 1.284, 95% CI: 1.102-1.497) only in luminal breast cancer while with a higher PFS (n = 2, RR: 0.585, 95% CI: 0.343-0.997) in Her2+ breast cancer. No significant differences in terms of CSM (n = 19, RR: 1.009, 95% CI: 0.947-1.077), PFS (n = 4, RR: 0.932, 95% CI: 0.616-1.305), and DFS (n = 2, RR: 0.776, 95% CI: 0.512-1.176) were observed. Our results provide evidence of the relationship between BB and breast cancer incidence and prognosis.

The effects of androgen deprivation on working memory and quality of life in prostate cancer patients: The roles of hypothalamic connectivity

BACKGROUND

Androgen deprivation therapy (ADT) has been associated with adverse effects on the brain. ADT alters testosterone levels via its action on the hypothalamus-pituitary-gonadal axis and may influence hypothalamic functions. Given the wide regional connectivity of the hypothalamus and its role in regulating cognition and behavior, we assessed the effects of ADT on hypothalamic resting state functional connectivity (rsFC) and their cognitive and clinical correlates.

METHODS

In a prospective observational study, 22 men with nonmetastatic prostate cancer receiving ADT and 28 patients not receiving ADT (controls), matched in age, years of education, and Montreal Cognitive Assessment score, participated in N-back task and quality of life (QoL) assessments and brain imaging at baseline and at 6 months. Imaging data were processed with published routines and the results of a group by time flexible factorial analysis were evaluated at a corrected threshold.

RESULTS

ADT and control groups did not differ in N-back performance or QoL across time points. Relative to controls, patients receiving ADT showed significantly higher hypothalamus-right mid-cingulate cortex (MCC) and precentral gyrus (PCG) rsFC during follow-up versus baseline. Further, the changes in MCC and PCG rsFC were correlated positively with the change in QoL score and 0-back correct response rate, respectively, in patients with undergoing ADT.

CONCLUSION

Six-month ADT affects hypothalamic functional connectivity with brain regions critical to cognitive motor and affective functions. Elevated hypothalamic MCC and PCG connectivity likely serve to functionally compensate for the effects of ADT and sustain attention and overall QoL. The longer-term effects of ADT remain to be investigated.

Identifying the Psychometric Properties of the Malay Version of the WHOQOL-BREF among Employees with Obesity Problem

The Malay version of the WHOQOL-BREF was published approximately 15 years ago. Since then, no known research has been conducted to identify the psychometric properties of the scale using confirmatory factor analysis. This study aimed to establish a model by applying a scientific approach to the translation and adaptation method. The back translation technique was used for the translation process. This cross-sectional study involved 282 employees at Universiti Kebangsaan Malaysia. The instrument received satisfactory Cronbach's alpha reliability values. The data were analysed with SEM using AMOS. Results showed that the model produced is parsimonious, with CMIN/df = 0.23, CFI = 0.93, SRMR = 0.08, RMSEA = 0.08 and PCLOSE = 0.07. Adopting the Malay version of the WHOQOL-BREF for future research is highly recommended due to its properties.

A Novel Approach to Modeling and Forecasting Cancer Incidence and Mortality Rates through Web Queries and Automated Forecasting Algorithms: Evidence from Romania

Simple Summary

Cancer remains a global burden, currently causing nearly one in six deaths worldwide. Accurate projections of cancer incidence and mortality are needed for effective and efficient policymaking, accurate resource allocation, and to assess the impact of newly introduced policies and measures. However, the COVID-19 pandemic disrupted public health systems and caused a significant number of cancers to remain undiagnosed, thus affecting the quality of official statistics and their usefulness for health studies. This paper addresses this issue by proposing novel cancer incidence/cancer mortality models based on population web-search habits and historical links with official health variables. The models are empirically estimated using data from one of the most vulnerable European Union (EU) members, Romania, a country that consistently reports lower survival rates than the EU average, and are further used to forecast cancer incidence and mortality rates in the country. Research findings have important policy implications, and the novel framework, owing to its generalizability, can be applied to the same task in other countries. Overall, the results indicate a continuation of the increasing trends in cancer incidence and mortality in Romania and thus underline the urgency to change the status quo in the Romanian public-health system.

Abstract

Cancer remains a leading cause of worldwide mortality and is a growing, multifaceted global burden. As a result, cancer prevention and cancer mortality reduction are counted among the most pressing public health issues of the twenty-first century. In turn, accurate projections of cancer incidence and mortality rates are paramount for robust policymaking, aimed at creating efficient and inclusive public health systems and also for establishing a baseline to assess the impact of newly introduced public health measures. Within the European Union (EU), Romania consistently reports higher mortality from all types of cancer than the EU average, caused by an inefficient and underfinanced public health system and lower economic development that in turn have created the phenomenon of “oncotourism”. This paper aims to develop novel cancer incidence/cancer mortality models based on historical links between incidence and mortality occurrence as reflected in official statistics and population web-search habits. Subsequently, it employs estimates of the web query index to produce forecasts of cancer incidence and mortality rates in Romania. Various statistical and machine-learning models—the autoregressive integrated moving average model (ARIMA), the Exponential Smoothing State Space Model with Box-Cox Transformation, ARMA Errors, Trend, and Seasonal Components (TBATS), and a feed-forward neural network nonlinear autoregression model, or NNAR—are estimated through automated algorithms to assess in-sample fit and out-of-sample forecasting accuracy for web-query volume data. Forecasts are produced with the overperforming model in the out-of-sample context (i.e., NNAR) and fed into the novel incidence/mortality models. Results indicate a continuation of the increasing trends in cancer incidence and mortality in Romania by 2026, with projected levels for the age-standardized total cancer incidence of 313.8 and the age-standardized mortality rate of 233.8 representing an increase of 2%, and, respectively, 3% relative to the 2019 levels. Research findings thus indicate that, under the no-change hypothesis, cancer will remain a significant burden in Romania and highlight the need and urgency to improve the status quo in the Romanian public health system.

Modeling the Ranked Antenatal Care Visits Using Optimized Partial Least Square Regression

The frequency and timing of antenatal care visits are observed to be the significant factors of infant and maternal morbidity and mortality. The present research is conducted to determine the risk factors of reduced antenatal care visits using an optimized partial least square regression model. A data set collected during 2017-2018 by Pakistan Demographic and Health Surveys is used for modeling purposes. The partial least square regression model coupled with rank correlation measures are introduced for improved performance to address ranked response. The proposed models included PLSρ_s, PLSτ_A, PLSτ_B, PLSτ_C, PLS _D, PLSτ_GK, PLS _G, and PLS _U. Three filter-based factor selection methods are executed, and leave-one-out cross-validation by linear discriminant analysis is measured on predicted scores of all models. Finally, the Monte Carlo simulation method with 10 iterations of repeated sampling for optimization of validation performance is applied to select the optimum model. The standard and proposed models are executed over simulated and real data sets for efficiency comparison. The PLSρ_s is found to be the most appropriate proposed method to model the observed ranked data set of antenatal care visits based on validation performance. The optimal model selected 29 influential factors of inadequate use of antenatal care. The important factors of reduced antenatal care visits included women's educational status, wealth index, total children ever born, husband's education level, domestic violence, and history of cesarean section. The findings recommended that partial least square regression algorithms coupled with rank correlation coefficients provide more efficient estimates of ranked data in the presence of multicollinearity.