Background and Objectives: Surgical treatment is central to breast cancer management; however, its long-term impact on QoL varies substantially among patients. This study sought to model the dynamic trajectories of postoperative QoL following breast-conserving surgery (BCS), mastectomy with immediate reconstruction (Mx+IR), and mastectomy alone (MA). It also examined how these trajectories varied across different age groups and over time. Materials and Methods: The review and meta-analysis identified 150 peer-reviewed studies reporting QoL outcomes using validated instruments (EORTC QLQ-C30 or BREAST-Q). A total of 123 observations from 45 studies were included for analysis of global QoL. We standardized QoL scores to a 0–100 scale and harmonized postoperative assessments across six time intervals, extending to more than 73 months. Multilevel random-effects models evaluated linear, quadratic, and logarithmic functions. Subgroup analyses and meta-regressions assessed the moderating effects of surgical type and age. Results: BCS showed the steepest QoL gains, followed by Mx+IR, while MA had the lowest scores and slowest recovery. Compared to BCS, MA showed significantly poorer and delayed recovery, and Mx+IR showed a smaller, borderline decrease. All groups displayed modest long-term QoL plateauing. Conclusions: Global QoL after breast cancer surgery follows distinct, time-dependent patterns shaped by surgical approach and age. These findings emphasize the importance of discussing patients’ quality-of-life expectations with them so that survivorship care can be personalized to their needs.

Background: As survival rates among breast cancer (BC) patients continue to rise, Emotional Functioning (EF)—has become increasingly clinically relevant; however, researchers have yet to fully characterize its long-term, dynamic trajectories following surgery. This systematic review and meta-analysis aimed to (1) characterize the longitudinal trajectories of EF after BC surgery and (2) examine the moderating effects of surgical modality and age. Methods: We conducted this systematic review and meta-analysis in accordance with PRISMA 2020 guidelines. We synthesized data from studies published between 2000 and 2024 that assessed EF using the EORTC QLQ-C30 at multiple post-surgical time points. Using multilevel random-effects meta-analytic models, we examined EF trajectories across 116 effect sizes derived from 40 studies, and evaluated time, surgical modality (breast-conserving surgery (BCS), mastectomy (MA), mastectomy with immediate reconstruction (Mx + IR) and age group as moderators. Results: The overall pooled estimate for EF was 73.44 (95% CI: 70.29–76.58, p < 0.001). Time since surgery significantly influenced EF: scores were lowest during the initial 6 months (66.82, 95% CI: 59.75–73.89), peaked at 7–15 months (77.86, 95% CI: 74.51–81.22) and 31–54 months (77.52, 95% CI: 70.44–84.59), and showed lower values at 16–30 months (72.58, 95% CI: 61.45–83.72) and 55–72 months (69.81, 95% CI: 64.08–75.54). Surgical modality significantly shaped these trajectories (p = 0.013). The overall pooled estimate for EF was 73.44 (95% CI: 70.29–76.58, p < 0.001). Time since surgery significantly influenced EF: scores were lowest during the initial 6 months (66.82, 95% CI: 59.75–73.89), peaked at 7–15 months (77.86, 95% CI: 74.51–81.22) and 31–54 months (77.52, 95% CI: 70.44–84.59), and showed lower values at 16–30 months (72.58, 95% CI: 61.45–83.72) and 55–72 months (69.81, 95% CI: 64.08–75.54). Surgical modality significantly shaped these trajectories (p = 0.013). The BCS group showed a significant inverted-U trajectory in EF scores, with a positive linear slope (β = 1.22, SE = 0.50, p = 0.046) and a small negative quadratic term (β = −0.02, SE = 0.01, p = 0.046), indicating initial improvement followed by decline. A similar pattern was observed for MA, where the linear term (β = 1.19, SE = 0.51, p = 0.054) and quadratic curvature (β = −0.02, SE = 0.01, p = 0.054) suggested an early rise with subsequent decline. In contrast, Mx + IR displayed a high intercept (β = 71.46, SE = 4.46, p < 0.001) but no significant trajectory over time (p = 0.582), indicating stability. The 45–60 year group demonstrated a significant inverted-U trajectory in EF scores, with a positive linear coefficient (β = 0.87, SE = 0.38, p = 0.067) and a negative quadratic coefficient (β = −0.01, SE = 0.01, p = 0.067), suggesting an early rise in emotional functioning followed by a subsequent decline. Participants <45 years also showed a significant inverted-U pattern, starting from a moderately high baseline (β = 67.56, SE = 4.26, p < 0.001) with a positive linear slope (β = 0.82, SE = 0.34, p = 0.051) and a negative quadratic curvature (β = −0.01, SE = 0.01, p = 0.051). In contrast, the >60 year group reported the highest baseline scores (β = 75.60, SE = 5.18, p < 0.001) with no significant trajectory, indicating overall stability. These findings confirm that EF follows a significant inverted-U trajectory (p < 0.001) and is influenced by time, surgical modality, and age.

Background: 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. Objectives: With this meta-analysis, we aim to describe the dynamics of overall QoL and its dimensions: mental status, physical functioning, and social interactions. Methods: 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. Conclusions: The study findings may serve as a tool for stratifying female patients with breast cancer by the risk of significant reduction in QoL.