AI Article Synopsis

  • Quality of life (QoL) in female breast cancer patients is dynamic and can change over time, influenced by various factors, yet current literature on predicting QoL is limited.
  • The proposed meta-analysis will systematically review studies assessing QoL through commonly used questionnaires for women who have undergone mastectomy or breast-conserving surgery, focusing on mental status, physical functioning, and social interactions.
  • The research will extract key information about participants (like age and surgery type) to analyze trends in QoL scores and identify predictors that may help stratify patients at risk for significant QoL decline.

Article Abstract

Quality of life (QoL) may change in female patients with breast cancer over time due to its dynamic construct. Recent studies have provided statistics on the diverse predictors of QoL in breast cancer patients. Still, the literature findings on the prognostication of QoL are scarce. With this meta-analysis, we aim to describe the dynamics of overall QoL and its dimensions: mental status, physical functioning, and social interactions. To reach this aim, we will systematically evaluate the peer-reviewed literature on QoL of women who have undergone either mastectomy or breast-conserving surgery. The proposed study will focus on, but not be limited to, the analysis of BIRS, FACT-B, and EORTC QLQ-C30 questionnaires, which are most commonly used in the assessment of the quality of life of cancer patients. Then, we will extract the following outcome measures: The participants' age, time since surgery, type of tumor removal procedure (mastectomy or breast-conserving surgery), breast reconstruction technique, mean value, and standard deviation in a QoL score. A random-effects model will then compute the pooled QoL and construct the trend lines for scores received from each diagnostic tool. The findings will be adjusted according to the reconstruction techniques and tumor removal surgery. Finally, we will model the QoL dynamics with a set of predictors identified in the extracted studies. The study findings may serve as a tool for stratifying female patients with breast cancer by the risk of significant reduction in QoL.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11594042PMC
http://dx.doi.org/10.3390/healthcare12222288DOI Listing

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