High atherogenic index of plasma and cardiovascular risk factors among Ghanaian breast cancer patients

Experiences of family caregivers in dealing with cases of advanced breast cancer: a qualitative study of the sociocultural context in Punjab, Pakistan

BACKGROUND

Patients with advanced breast cancer require consistent help and support from family caregivers. These caregivers often endure financial burdens and psychological stress, with their experiences significantly influenced by sociocultural factors. This study aims to explore the experiences of family caregivers of advanced breast cancer patients in Punjab province, Pakistan.

METHODS

Data was collected through in-depth interviews with fifteen family caregivers of advanced breast cancer patients in three major cities of Punjab, Pakistan. Caregivers, who had been in close contact with the patient for the last two years, were purposively sampled from five major hospitals. The data was analyzed using thematic analysis.

RESULTS

The study revealed that the experiences of family caregivers are deeply rooted in the sociocultural context. Key themes identified include social responsibility and cultural reciprocity norms; limited awareness and mobility options for caregivers; financial responsibility and strain; impacts of beauty myths and shyness on caregiving attitudes and decisions; the stressful and emotional nature of caregiving; treatment perspectives influenced by social groups; challenges in consulting male physicians and associated stigma; the role of religious beliefs in caregiving; and stress management, with religion often being a coping mechanism. These factors can contribute to delayed treatment decisions for patients.

CONCLUSIONS

Family caregivers are crucial in facilitating timely treatment decisions for advanced breast cancer patients in the Pakistani context. To minimize treatment delays and alleviate caregiver stress, addressing sociocultural barriers in care-seeking is essential. A tailored approach, considering sociocultural and religious factors, is imperative for the management and early diagnosis of breast cancer, necessitating appropriate policymaking and implementation.

The association of atherogenic index of plasma with cardiovascular outcomes in patients with coronary artery disease: A systematic review and meta-analysis

BACKGROUND

Atherogenic index of plasma (AIP) represents a novel marker in the current era of cardiovascular diseases. In this meta-analysis, we aimed to evaluate the association of AIP with cardiovascular prognosis in patients with coronary artery disease (CAD).

METHODS

PubMed, Scopus, and Web of Science databases were searched from inception through 2024. The primary outcome was major cardiovascular events (MACE). The secondary outcomes included all-causes death, cardiovascular death, myocardial infarction (MI), stroke, revascularization, and no-reflow phenomenon. AIP was determined by taking the logarithm of the ratio of triglyceride (TG) to high-density lipoprotein cholesterol (HDL-C). The data analysis was represented using the risk ratio (RR) along with a 95% confidence interval (CI).

RESULTS

Sixteen studies with a total number of 20,833 patients met the eligible criteria. The pooled-analysis showed a significant increased risk of MACE in the highest AIP group compared with the lowest AIP group (RR = 1.63; 95% CI, 1.44-1.85; P < 0.001). A similar result was observed when AIP was regarded as a continuous variable (RR = 1.54; 95% CI, 1.30-1.83; P < 0.001). Besides, elevated AIP was associated with increased risk of cardiovascular death (RR = 1.79; 95% CI, 1.09-2.78; P = 0.02), MI (RR = 2.21; 95% CI, 1.55-3.13; P < 0.001), revascularization (RR = 1.62; 95% CI, 1.34-1.97; P < 0.001), no-reflow phenomenon (RR = 3.12 95% CI, 1.09-8.96; P = 0.034), and stent thrombosis (RR = 13.46; 95%CI, 1.39-129.02; P = 0.025). However, AIP was not significantly associated with the risk of all-causes death and stroke among patients with CAD.

CONCLUSIONS

The results of this study demonstrated that increased AIP is an independent prognostic factors in patients with CAD. Further research is warranted to elucidate the potential development of targeted interventions to modify AIP levels and improve patient outcomes.

Determinants of Post-Traumatic Growth and Quality of Life in Ghanaian Breast Cancer Survivors

This study assessed the psychosocial factors associated with post-traumatic growth (PTG) and health-related quality of life (HRQoL) in women breast cancer survivors. Women (N = 128) completed questionnaires on social support, religiosity, hope, optimism, benefit-finding, PTG and HRQoL. Structural equation modeling was used to analyze the data. Results showed that perceived social support, religiosity, hope, optimism, and benefit finding were positively associated with PTG. Religiosity and PTG were positively associated with HRQoL. The results suggest that interventions aimed at increasing religiosity, hope, optimism, and perceived support can help survivors cope better with breast cancer.

Atherogenic index of plasma and coronary artery disease: A systematic review

Various studies suggest that the atherogenic index of plasma (AIP) is associated with the risk of coronary artery disease (CAD) in different clinical scenarios. This review aimed to synthesize evidence of the association between AIP values and CAD. A literature search was carried out on four databases, namely, PubMed, Scopus, Web of Science, and Ovid-Medline. A handsearch was performed on preprint repositories (MedRxiv and Research Square). The effect measurements were expressed as odds ratios (OR) with their corresponding 95% confidence intervals (CI). For the quantitative synthesis, we employed a random-effects model. We analyzed 14 articles (with 40,902 participants) from seven different countries. The quantitative analysis revealed that an increase in one unit of AIP was associated with higher odds of developing CAD (OR 2.11; 95% CI 1.65-2.69; P < 0.001; I ² = 98%). We conducted subgroup analyses of Chinese (OR 1.89; 95% CI 1.40-2.56; P < 0.001) and non-Chinese studies (OR 2.51; 95% CI 1.42-4.42; P < 0.001). The sensitivity analysis by risk of bias continued to demonstrate an association, and the heterogeneity remained unchanged (OR 1.75; 95% CI 1.33-2.31; P < 0.001; I ² = 98%). Higher AIP values were associated with higher odds of developing CAD.

Combining contrast-enhanced ultrasound and blood cell analysis to improve diagnostic accuracy of plasma cell mastitis

Plasma cell mastitis is a benign suppurative disease of the breast, lack of specific clinical manifestations, which is easy to be misdiagnosed and mistreated, often confused with mastitis, breast cancer (BC), and other diseases. Thus, we aimed to establish a combined model of promoting diagnostic accuracy of plasma cell mastitis by contrast-enhanced ultrasound (CEUS) patterns and routine blood cell analysis. Eighty-eight plasma cell mastitis, 91 breast cancer, and 152 other benign breast diseases' patients grouped according to pathological diagnosis underwent CEUS and blood cell analysis examination; 100 healthy female donors were involved. All the plasma cell mastitis and breast cancer patients presented hyperenhancement of CEUS breast lesions compared with others. The majority of plasma cell mastitis (65/88) showed perfusion defect of CEUS patterns with smooth edge (56/65) and multiple lesions (49/65); in contrast, fewer breast cancer patients (30/91) displayed perfusion defect. White blood cell count (WBC), neutrophils, and neutrophils/lymphocytes ratio of blood cell analysis in plasma cell mastitis patients increased significantly compared with other patients (P < 0.0001). Combining perfusion defect of CEUS patterns and WBC yielded an area under the receiver operating characteristic curve of 0.831, higher than single 0.720 and 0.774, respectively. The cut-off value of WBC (7.28 × 10⁹/L) helped remaining 65.2% (15/23) atypical cases to be correctly diagnosed as plasma cell mastitis, not misdiagnosed as breast cancer. In conclusion, CEUS presented a clear perfusion defect pattern of plasma cell mastitis lesion for the first time. A precise WBC by routine blood cell analysis test can assist CEUS examination in the differential diagnosis of plasma cell mastitis and breast cancer. It is a promised combination for laboratory diagnostic of PCM.

Detection of breast cancer of various clinical stages based on serum FT-IR spectroscopy combined with multiple algorithms

BACKGROUND

Breast cancer screening is time consuming, requires expensive equipment, and has demanding requirements for doctors. Hence, a large number of breast cancer patients may miss screening and early treatment, which greatly threatens their health around the world. Infrared spectroscopy may be able to be used as a screening tool for breast cancer detection. Fourier transform infrared (FT-IR) spectroscopy of serum was combined with traditional machine learning algorithms to achieve an auxiliary diagnosis that could quickly and accurately distinguish patients with different stages of breast cancer, including stage 1 disease, from control subjects without breast cancer.

MATERIALS AND METHODS

FT-IR spectroscopy were performed on the serum of 114 non-cancer control subjects, 35 patients with stage I, 43 patients with stage II, and 29 patients with stage III & IV breast cancer. Due to the experimental sample imbalance, we used the oversampling to process the four classes of sample. The oversampling selected Synthetic Minority Oversampling Technique (SMOTE). Subsequently, we used the random discarding method in undersampling to do experiments as well. The average FT-IR spectroscopy results for the four groups showed differences in phospholipids, nucleic acids, lipids, and proteins between non-cancer control subjects and breast cancer patients at different stages. Based on these differences, four classification models were used to classify stage I, II, III & IV breast cancer patients and non-cancer control subjects. First, standard normal variate transformation (SNV) was used to preprocess the original data, and then partial least squares (PLS) was used for feature extraction. Finally, the five models were established including extreme learning machine (ELM), k-nearest neighbor (KNN), genetic algorithms based on support vector machine (GA-SVM), particle swarm optimization-support vector machine (PSO-SVM) and grid search-support vector machine (GS-SVM).

CONCLUSION

In oversampling experiment, the GS-SVM classifier obtained the highest average classification accuracy of 95.45 %; the diagnostic accuracy of non-cancer control subjects was 100 %; breast cancer stage I was 90 %; breast cancer stage II was 84.62 %; and breast cancer stage III & IV was 100 %. In undersampling experiment, the GA-SVM model obtained the highest average classification accuracy of 100 %; the diagnostic accuracy of non-cancer control subjects was 100 %; breast cancer stage I was 100 %; breast cancer stage II was 100 %; and breast cancer stage III & IV was 100 %. The results show that FT-IR spectroscopy combined with powerful classification algorithms has great potential in distinguishing patients with different stages of breast cancer from non-cancer control subjects. In addition, this research provides a reference for future multiclassification studies of cervical cancer, ovarian cancer and other female high-incidence cancers through serum FT-IR spectroscopy.