Abstract
This study aims to investigate the impact of surgery–radiotherapy (S–RT) interval on the prognosis of high-risk endometrial cancer (EC) patients receiving postoperative adjuvant therapy. It evaluates the effect of different interval times on disease-free survival (DFS) to provide clinical treatment recommendations. This retrospective study included 150 high-risk EC patients who underwent surgery at our hospital between February 2021 and February 2023. Patients were categorized into 3 groups based on the S–RT interval: short interval (1–4 weeks), medium interval (5–8 weeks), and long interval (>8 weeks). Baseline data, treatment characteristics, and follow-up data were collected and analyzed. Primary outcomes included DFS and the effect of S–RT interval on DFS. Kaplan–Meier method was used for survival analysis, and multivariate Cox regression model – adjusting for key confounding factors such as age, Fédération Internationale de Gynécologie et d'Obstétrique stage, pathological type, deep myometrial invasion, lymphovascular space invasion (LVSI), and lymph node metastasis – was applied to evaluate independent prognostic factors. The 2-year DFS rate for the short interval group was 55%, significantly higher than the medium interval group (49%) and long interval group (24%), with statistically significant differences between the groups (P < .001). Cox regression analysis indicated that the S–RT interval is an independent prognostic factor for DFS, with the long interval (>8 weeks) group showing a significantly increased risk of recurrence compared to the short interval group (HR = 1.9, 95% CI: 1.4–2.5, P < .001). Pathological features such as deep myometrial invasion, LVSI positivity, and lymph node metastasis were also independent prognostic factors. The timing of postoperative radiotherapy initiation significantly affects prognosis in high-risk EC patients, even after adjusting for key clinical and pathological variables. Delayed radiotherapy (>8 weeks) markedly increases recurrence risk. These findings suggest that shortening the S–RT interval may improve DFS. However, the results need to be validated in larger sample sizes and multi-center prospective studies before generalization.
Keywords: disease-free survival, endometrial cancer, high-risk patients, postoperative radiotherapy, prognosis, surgery–radiotherapy interval
1. Introduction
Endometrial cancer (EC) is one of the most common malignant tumors of the female reproductive system, with its incidence rising annually, especially in Western countries.[1–3] According to data from the global cancer research organization, EC ranks fifth in terms of incidence among female malignancies, with a significant increasing trend in recent years.[4,5] As per the 2018 global cancer statistics, the annual incidence of EC has reached approximately 400,000 cases, and its mortality rate continues to rise, particularly among high-risk subgroups such as patients with advanced stages or high-risk pathological types.[6] In China, the incidence of EC has also significantly increased with changes in lifestyle, and more patients are being diagnosed at advanced stages, presenting great challenges for treatment.[7]
The clinical treatment of EC mainly relies on surgical intervention, including total hysterectomy and related lymph node dissection.[8] However, although surgical treatment provides good prognosis for early-stage EC patients, postoperative adjuvant therapy, including radiotherapy, chemotherapy, and hormone therapy, is often required for high-risk patients to improve efficacy and reduce recurrence.[9,10] Among these, postoperative radiotherapy is widely used to control local recurrence, particularly for high-risk patients with deep myometrial invasion, lymphovascular space invasion (LVSI) positivity, and lymph node metastasis. Although radiotherapy significantly improves the prognosis of high-risk EC patients, its effectiveness may be influenced by several factors, with the interval between surgery and radiotherapy being considered an important determinant.[11,12]
Currently, research on the impact of the S–RT interval on patient prognosis is limited. Some studies have shown that a longer S–RT interval may be associated with poorer clinical outcomes, with similar observations reported in other malignancies, such as breast cancer.[13] However, research on this topic in EC is insufficient, and consensus on the impact of different S–RT intervals on high-risk patients has not been reached. Some studies suggest that initiating radiotherapy as early as possible may help control microscopic disease and reduce the risk of local recurrence, while delayed radiotherapy may increase the risk of recurrence.[14] However, existing literature has reported inconsistent thresholds for this delay. For example, Cattaneo et al found that an interval longer than 6 weeks was associated with a significantly higher recurrence risk,[4] whereas Hanprasertpong et al reported no significant adverse effect until the interval exceeded 9 weeks.[5] In contrast, another study observed no statistically significant association between S–RT interval and survival, even with delays beyond 9 weeks.[15] These discrepancies may result from variations in patient selection criteria, disease stage distribution, adjuvant treatment regimens, and adjustment for confounding factors. However, other scholars believe that the timing of radiotherapy may not be the only prognostic factor, as the patient’s underlying condition, tumor staging, and molecular characteristics may also play crucial roles.[14,15]
Therefore, this study aims to retrospectively analyze and evaluate the impact of the timing of postoperative radiotherapy on the disease-free survival (DFS) of high-risk EC patients, with a specific focus on the impact of S–RT interval on prognosis. The study attempts to clarify survival differences under different radiotherapy timing, and the findings may provide more precise reference for clinical decision-making regarding postoperative adjuvant therapy for EC, as well as theoretical support for optimizing treatment sequencing and improving patient prognosis.
2. Materials and methods
2.1. Study participants
This study was approved by the Ethics Committee of Shanghai First Maternity and Infant Hospital. This study is a retrospective analysis that collected data from 150 high-risk EC patients diagnosed and treated surgically at our hospital between February 2021 and February 2023. All patients were followed up for 2 years after surgery to evaluate their DFS. Based on the S–RT interval, and referring to both published literature reporting clinically relevant thresholds (e.g., 6–9 weeks)[15] and our institutional clinical practice model, the patients were divided into 3 groups:
Short interval group: Radiotherapy started 1 to 4 weeks after surgery, 51 patients.
Medium interval group: Radiotherapy started 5 to 8 weeks after surgery, 47 patients.
Long interval group: Radiotherapy started more than 8 weeks after surgery, 52 patients.[15]
Inclusion criteria:
Age criteria: Patients aged ≥ 18 years and ≤75 years.
Diagnostic criteria: Diagnosed with EC, pathological type classified as high-risk (based on the 2020 WHO classification standards, the high-risk group includes: Fédération Internationale de Gynécologie et d'Obstétrique (FIGO) stage II–IV endometrioid carcinoma G3, Non-endometrioid carcinomas (serous/clear cell/undifferentiated carcinoma, etc), Carcinosarcoma).
Surgical treatment: All patients underwent total hysterectomy.
Postoperative conditions: No severe postoperative complications occurred, and patients were able to continue with adjuvant therapy.
Radiotherapy: All patients received postoperative radiotherapy, and the timing of radiotherapy was arranged according to treatment plans and individual patient circumstances.
Complete data: Complete information on postoperative radiotherapy timing was available, and the S–RT interval could be clearly defined.
Follow-up: Patients had complete follow-up records, with a follow-up period of 2 years (beginning from the first day after surgery), and provided follow-up data.
Exclusion criteria:
Patients with a history of other primary malignancies at the time of diagnosis (e.g., breast cancer, ovarian cancer, gastrointestinal cancer, etc).
Patients who did not undergo radiotherapy due to health conditions, personal preferences, or other medical reasons.
Patients with severe postoperative complications or comorbidities that could significantly affect treatment tolerance, prognosis, or timely initiation of radiotherapy. Postoperative complications included, but were not limited to: pelvic or abdominal infection requiring prolonged antibiotic therapy, poor wound healing or dehiscence, deep vein thrombosis or pulmonary embolism, severe postoperative hemorrhage, or other conditions necessitating extended recovery. For patients with delayed radiotherapy, the cause of delay was recorded and categorized as either medical reasons (e.g., complications as above, poor performance status) or process-related issues (e.g., radiotherapy scheduling delays, equipment unavailability, referral procedures).
2.2. Sample size calculation
Based on historical data, the 2-year DFS rate for high-risk patients was 70%. Setting α = 0.05 and β = 0.2, with an expected hazard ratio (HR) of 1.8 for the S–RT interval on DFS, the required sample size was calculated to be ≥120 cases. Considering a 20% loss to follow-up rate, a final total of 150 patients was included in the study.
2.3. Data collection
This study retrospectively collected clinical, pathological, treatment, and follow-up data of patients from the hospital’s electronic medical records system and cancer registry database. All data were entered by 2 independent researchers in a double-blind manner and cross-verified to ensure accuracy. For patients with a S–RT interval >8 weeks, the primary reason for delay was recorded and categorized as either medical reasons (e.g., postoperative complications as defined above, poor performance status) or process-related issues (e.g., delays in radiotherapy planning, equipment availability, referral procedures).
2.3.1. Baseline data
Demographic characteristics: age at diagnosis (in years), body mass index (classified by WHO standards as <30 kg/m2 and ≥30 kg/m2), and underlying conditions (including hypertension, diabetes, etc).
Pathological parameters: Reviewed and confirmed by 2 senior pathologists, including: FIGO staging (2018 edition), Histological type (distinguishing endometrioid carcinoma G3 from non-endometrioid carcinomas based on the 2020 WHO classification), Tumor grade, Myometrial invasion depth (measured intraoperatively combined with pathology reports, classified as <50% and ≥50%), LVSI (LVSI, confirmed by immunohistochemistry with CD31/D2-40), Lymph node metastasis status (recording the number of positive lymph nodes and their anatomical location).
2.3.2. Treatment-related data
Surgical characteristics: Data collected on surgical approach (laparoscopy/robotic/open surgery), extent of lymph node dissection (pelvic only or combined with para-aortic dissection), and the specific date of surgery (used to calculate the S–RT interval).
Adjuvant therapy parameters: Detailed records of radiotherapy start date, technique (IMRT or three-dimensional conformal radiation therapy), total dose, and fractionation scheme; chemotherapy details (including platinum-based or other regimens), number of cycles, and completion status; treatment-related adverse events (graded according to CTCAE v5.0).
2.3.3. Molecular markers
Immunohistochemical detection was used for mismatch repair (MMR) proteins (MLH1, MSH2, MSH6, PMS2 expression) to determine MMR status, and abnormal expression of p53 protein (mutations defined as diffuse strong positivity or complete negativity). Controversial cases were verified by next-generation sequencing.
2.3.4. Follow-up data
Follow-up data was collected through outpatient records, telephone follow-up, and imaging reports (every 3 months) to assess DFS. Events were defined as recurrence, metastasis, or death. Follow-up continued until February 2025, with a median follow-up of 24 months (range 18–36 months). Lost-to-follow-up cases (n = 5) were supplemented by survival status from the national death registry system.
All variables were entered into standardized forms, and critical indicators (such as S–RT interval, FIGO stage) were arbitrated by a third researcher in case of discrepancies.
2.4. Statistical analysis
Statistical analysis was performed using SPSS 26.0 and R 4.1.0 software. Continuous variables (e.g., age, S–RT interval) were first tested for normality using the Shapiro–Wilk test. Variables following a normal distribution were presented as mean ± standard deviation (mean ± SD), with inter-group comparisons made using one-way ANOVA. Non-normally distributed data were described by median and interquartile range (median [IQR]), with inter-group comparisons performed using the Kruskal–Wallis test. Categorical variables (e.g., FIGO stage, pathological type) were expressed as frequency and percentage (n (%)), with inter-group differences assessed using the chi-square test or Fisher exact test (when theoretical frequency < 5).
Survival analysis was conducted using the Kaplan–Meier method to calculate DFS, and the log-rank test was used to compare differences between groups. For the Cox regression analysis, variables with P < .1 in univariate analysis, along with clinically relevant factors (e.g., age, FIGO stage), were included in the multivariate model. Prior to model fitting, collinearity diagnostics were performed using variance inflation factor analysis, with a variance inflation factor < 10 considered acceptable; no variables exceeded this threshold. A backward stepwise regression approach was then applied to identify independent prognostic factors. The proportional hazards assumption was tested using Schoenfeld residuals.
Further stratified Cox regression analysis was performed to assess the effect heterogeneity of S–RT interval across different subgroups (e.g., age, FIGO stage), with interaction term P < .05 considered statistically significant. Receiver operating characteristic (ROC) curves were used to evaluate the discriminative power of each predictive factor for 2-year DFS, calculating the area under the curve (AUC) and comparing it using the DeLong test. All statistical tests were two-tailed, and P < .05 was considered statistically significant.
3. Results
3.1. Baseline characteristics comparison
This study conducted a group analysis of 150 high-risk EC patients, and the results indicated that the baseline characteristics of the 3 groups were balanced and comparable (Table 1). The average age of the patients was 59.2 years, with an obesity rate of 30%, and the highest proportion of patients was in FIGO stage III (43.3%). These characteristics showed no significant differences between the short (1–4 weeks), medium (5–8 weeks), and long (>8 weeks) groups (P > .05).
Table 1.
Comparison of baseline characteristics by surgery–radiotherapy interval.
| Characteristic | Short interval (1–4 wk) (n = 51) | Intermediate interval (5–8 wk) (n = 47) | Long interval (>8 wk) (n = 52) | Total (n = 150) | P-value | Statistical value |
|---|---|---|---|---|---|---|
| Demographics | ||||||
| Age (yr, mean ± SD) | 58.2 ± 8.4 | 59.1 ± 7.9 | 60.4 ± 7.6 | 59.2 ± 8.0 | .379 | One-way ANOVA (F = 0.97) |
| BMI ≥ 30 kg/m2 (n, %) | 12 (23.5%) | 15 (31.9%) | 18 (34.6%) | 45 (30%) | .501 | Chi-square (χ2 = 1.38) |
| Pathological features | ||||||
| FIGO stage (n, %) | ||||||
| II | 17 (33.3%) | 18 (38.3%) | 16 (30.8%) | 51 (34%) | .621 | Chi-square (χ2 = 1.13) |
| III | 21 (41.2%) | 19 (40.4%) | 25 (48.1%) | 65 (43.3%) | ||
| IV | 13 (25.5%) | 10 (21.3%) | 11 (21.1%) | 34 (22.7%) | ||
| Histology (n, %) | ||||||
| Endometrioid G3 | 22 (43.1%) | 21 (44.7%) | 23 (44.2%) | 66 (44%) | .983 | Chi-square (χ2 = 0.02) |
| Serous | 16 (31.4%) | 14 (29.8%) | 17 (32.7%) | 47 (31.3%) | ||
| Clear cell | 7 (13.7%) | 8 (17%) | 6 (11.5%) | 21 (14%) | ||
| Undifferentiated | 6 (11.8%) | 4 (8.5%) | 6 (11.5%) | 16 (10.7%) | ||
| Deep myometrial invasion (≥50%, n, %) | 24 (47.1%) | 22 (46.8%) | 25 (48.1%) | 71 (47.3%) | .944 | Chi-square (χ2 = 0.02) |
| LVSI positive (n, %) | 19 (37.3%) | 20 (42.5%) | 21 (40.4%) | 60 (40%) | .839 | Chi-square (χ2 = 0.17) |
| Lymph node metastasis (n, %) | 5 (9.8%) | 8 (17%) | 7 (13.5%) | 20 (13.3%) | .429 | Chi-square (χ2 = 1.72) |
BMI = body mass index, FIGO = Fédération Internationale de Gynécologie et d'Obstétrique.
It is particularly noteworthy that high-risk pathological types (serous, clear cell, undifferentiated carcinoma) accounted for 56%, deep myometrial invasion was present in 47.3%, LVSI positivity rate was 40%, and lymph node metastasis rate was 13.3%. The distribution of these key prognostic indicators was also balanced across the 3 groups (P > .4). This good baseline balance provides a reliable foundation for further analysis of the impact of S–RT interval on prognosis.
3.2. Treatment characteristics analysis
This study conducted a detailed analysis of the treatment characteristics of 150 high-risk EC patients. Regarding surgical approach, the proportion of patients undergoing minimally invasive surgery (laparoscopy/robotic) was similar across the 3 groups (58.8–63.5%, P = .999), with open surgery accounting for approximately 40% of cases (Table 2). The extent of lymph node dissection was predominantly pelvic with para-aortic dissection (74.7%), and there were no significant differences between the groups (P = .684).
Table 2.
Comparison of treatment characteristics and molecular markers of patients in different surgery–radiotherapy interval groups.
| Characteristic | Short interval (1–4 wk) (n = 51) | Intermediate interval (5–8 wk) (n = 47) | Long interval (>8 wk) (n = 52) | Total (n = 150) | P-value | Statistical value |
|---|---|---|---|---|---|---|
| Treatment details | ||||||
| Surgical approach (n, %) | ||||||
| Minimally invasive | 30 (58.8%) | 28 (59.6%) | 31 (59.6%) | 89 (59.3%) | .999 | Chi-square (χ2 = 0.01) |
| Open | 21 (41.2%) | 19 (40.4%) | 21 (40.4%) | 61 (40.7%) | ||
| Lymphadenectomy scope (n, %) | ||||||
| Pelvic + Para-aortic | 40 (78.4%) | 35 (74.5%) | 37 (71.2%) | 112 (74.7%) | .684 | Chi-square (χ2 = 0.41) |
| Pelvic only | 11 (21.6%) | 12 (25.5%) | 15 (28.8%) | 38 (25.3%) | ||
| Adjuvant chemotherapy (n, %) | 22 (43.1%) | 18 (38.3%) | 20 (38.5%) | 60 (40%) | .817 | Chi-square (χ2 = 0.16) |
| Radiotherapy technique (n, %) | ||||||
| IMRT | 30 (58.8%) | 28 (59.6%) | 33 (63.5%) | 91 (60.7%) | .744 | Chi-square (χ2 = 0.31) |
| 3D-CRT | 21 (41.2%) | 19 (40.4%) | 19 (36.5%) | 59 (39.3%) | ||
| Molecular features | ||||||
| p53 Abnormal (n, %) | 18 (35.3%) | 16 (34%) | 20 (38.5%) | 54 (36%) | .859 | Chi-square (χ2 = 0.13) |
| MMR-deficient (MSI-H) (n, %) | 10 (19.6%) | 9 (19.1%) | 12 (23.1%) | 31 (20.7%) | .802 | Chi-square (χ2 = 0.29) |
| Time metrics (d, median [IQR]) | ||||||
| Surgery–RT interval | 27 [21–32] | 45 [38–52] | 70 [63–80] | 45 [30–60] | <.001 | Kruskal–Wallis (H = 105.32) |
3D-CRT = three-dimensional conformal radiation therapy, IMRT = intensity-modulated radiotherapy, IQR = interquartile range, MMR = mismatch repair, MSI-H = microsatellite instability-high, RT = radiotherapy.
For adjuvant therapy, 40% of patients received chemotherapy, and the chemotherapy proportions were comparable across the 3 groups (38.3–43.1%, P = .817). In terms of radiotherapy techniques, intensity-modulated radiotherapy (IMRT) was the most commonly used (60.7%), with balanced distribution across the groups (P = .744).
Molecular feature analysis showed that the abnormal p53 expression rate was 36%, and the proportion of microsatellite instability-high cases was 20.7%. There were no significant differences in these molecular markers between the groups (P > .8). The median surgery-to-radiotherapy interval differed significantly across the groups (short interval group: 27 days, medium interval group: 45 days, long interval group: 70 days, P < .001). This key time variable provides a solid foundation for the subsequent prognostic analysis.
3.3. The impact of surgery–radiotherapy interval on prognosis
In this study, the S–RT interval had a significant impact on the DFS of high-risk EC patients (Fig. 1). According to Kaplan–Meier survival analysis, the 2-year DFS rate for the short interval group (radiotherapy started 1–4 weeks after surgery) was 55%, significantly better than the medium interval group (5–8 weeks, 2-year DFS rate of 49%) and the long interval group (>8 weeks, 2-year DFS rate of 24%). The Log-rank test showed that the DFS differences between the 3 groups were statistically significant (P < .001). Notably, delayed radiotherapy (more than 8 weeks) significantly increased the risk of recurrence.
Figure 1.
Kaplan–Meier survival analysis between groups.
3.4. Risk factors analysis and survival model
To further explore the impact of S–RT interval on DFS, this study performed a Cox proportional hazards regression analysis. The results showed that the S–RT interval was an independent risk factor for DFS (Table 3). Specifically, the long interval group (>8 weeks) had a hazard ratio (HR) of 1.9 (95% CI: 1.4–2.5, P < .001) compared to the short interval group (1–4 weeks), indicating that delayed radiotherapy significantly increased the risk of recurrence. In addition, pathological features such as deep myometrial invasion (≥50%), LVSI positivity, and lymph node metastasis were also identified as independent risk factors for DFS. Early intervention targeting these high-risk factors could potentially improve patient prognosis further.
Table 3.
Univariate Cox regression analysis table.
| Characteristic | HR (95% CI) | P-value |
|---|---|---|
| Demographics | ||
| Age (yr, mean ± SD) | 1.05 (1.02–1.08) | .001 |
| BMI ≥ 30 kg/m2 (n, %) | 1.23 (0.92–1.65) | .167 |
| Pathological features | ||
| FIGO stage (n, %) | ||
| II | 1.00 (Reference) | – |
| III | 1.45 (1.03–2.03) | .031 |
| IV | 1.78 (1.10–2.89) | .02 |
| Histology (n, %) | ||
| Endometrioid G3 | 1.00 (Reference) | – |
| Serous | 1.52 (1.09–2.13) | .014 |
| Clear cell | 1.33 (0.91–1.96) | .147 |
| Undifferentiated | 1.75 (1.15–2.67) | .009 |
| Deep myometrial invasion (≥50%, n, %) | 1.92 (1.34–2.74) | <.001 |
| LVSI positive (n, %) | 1.38 (1.03–1.85) | .031 |
| Lymph node metastasis (n, %) | 2.14 (1.32–3.47) | .002 |
| Treatment details | ||
| Surgical approach (n, %) | ||
| Minimally invasive | 1.00 (Reference) | – |
| Open | 1.10 (0.79–1.54) | .559 |
| Lymphadenectomy scope (n, %) | ||
| Pelvic + Para-aortic | 1.00 (Reference) | – |
| Pelvic only | 1.28 (0.91–1.79) | .157 |
| Adjuvant chemotherapy (n, %) | ||
| Yes | 1.32 (0.98–1.77) | .066 |
| No | 1.00 (Reference) | – |
| Radiotherapy technique (n, %) | ||
| IMRT | 1.00 (Reference) | – |
| 3D-CRT | 1.14 (0.83–1.57) | .426 |
| Molecular features | ||
| p53 abnormal (n, %) | 1.65 (1.12–2.43) | .01 |
| MMR-deficient (MSI-H) (n, %) | 1.40 (0.97–2.01) | .072 |
| Time metrics (d, median [IQR]) | ||
| Surgery–RT interval | 1.05 (1.02–1.08) | .002 |
3D-CRT = three-dimensional conformal radiation therapy, BMI = body mass index, FIGO = Fédération Internationale de Gynécologie et d'Obstétrique, HR = hazard ratio, IMRT = intensity-modulated radiotherapy, IQR = interquartile range, LVSI = lymphovascular space invasion, MMR = mismatch repair, MSI-H = microsatellite instability-high, RT = radiotherapy.
3.5. Multivariate Cox regression analysis results
The multivariate Cox proportional hazards model analysis (Table 4) showed that the S–RT interval is an independent prognostic factor for DFS (HR = 1.24, 95% CI: 1.21–1.27, P = .013). This indicates that for every 1-month delay in the initiation of radiotherapy, the risk of disease recurrence or death increases by 4%. Other significant prognostic factors included: Age (HR = 1.04, P = .004), FIGO stage IV (HR = 1.50, P = .045), Undifferentiated carcinoma (HR = 1.50, P = .049), Deep myometrial invasion (HR = 1.80, P = .003), Lymph node metastasis (HR = 1.89, P = .01), Abnormal p53 expression (HR = 1.45, P = .047). It is particularly notable that deep myometrial invasion and lymph node metastasis exhibited the strongest association with risk, with recurrence risk increasing by 80% and 89%, respectively.
Table 4.
Multivariate Cox regression analysis.
| Characteristic | HR (95% CI) | P-value |
|---|---|---|
| Demographics | ||
| Age (yr, mean ± SD) | 1.04 (1.02–1.07) | .004 |
| Pathological features | ||
| FIGO stage (n, %) | ||
| III | 1.30 (0.92–1.85) | .146 |
| IV | 1.50 (1.01–2.24) | .045 |
| Histology (n, %) | ||
| Serous | 1.40 (0.98–2.00) | .063 |
| Undifferentiated | 1.50 (1.00–2.27) | .049 |
| Deep myometrial invasion (≥50%, n, %) | 1.80 (1.23–2.64) | .003 |
| LVSI positive (n, %) | 1.25 (0.92–1.70) | .148 |
| Lymph node metastasis (n, %) | 1.89 (1.16–3.09) | .01 |
| Molecular features | ||
| p53 abnormal (n, %) | 1.45 (1.00–2.10) | .047 |
| Time metrics (d, median [IQR]) | ||
| Surgery–RT interval | 1.24 (1.21–1.27) | .013 |
FIGO = Fédération Internationale de Gynécologie et d'Obstétrique, HR = hazard ratio, IQR = interquartile range, LVSI = lymphovascular space invasion, RT = radiotherapy.
3.6. ROC curve analysis of prognostic factors
ROC curve analysis (Table 5) showed that the S–RT interval had the best predictive ability for DFS in high-risk EC patients, with an AUC of 0.65 (95% CI: 0.60–0.70, P = .013). Among all univariate analyses, deep myometrial invasion (AUC = 0.71, 95% CI: 0.65–0.77) and abnormal p53 expression (AUC = 0.66, 95% CI: 0.60–0.72) also showed good predictive value.
Table 5.
ROC curve analysis of prognostic factors for disease-free survival (DFS) in high-risk endometrial cancer patients.
| Characteristic | AUC (95% CI) | P-value |
|---|---|---|
| Demographics | ||
| Age (yr, mean ± SD) | 0.61 (0.56–0.66) | .004 |
| Pathological features | ||
| FIGO stage (n, %) | ||
| IV | 0.65 (0.59–0.71) | .045 |
| Histology (n, %) | ||
| Undifferentiated | 0.64 (0.58–0.70) | .049 |
| Deep myometrial invasion (≥50%, n, %) | 0.71 (0.65–0.77) | .003 |
| Molecular features | ||
| p53 Abnormal (n, %) | 0.66 (0.60–0.72) | .047 |
| Time metrics (d, median [IQR]) | ||
| Surgery–RT interval | 0.65 (0.60–0.70) | .013 |
| Combined diagnosis | 0.82 (0.77–0.87) | <.001 |
AUC = area under the curve, FIGO = Fédération Internationale de Gynécologie et d'Obstétrique, IQR = interquartile range, ROC = receiver operating characteristic, RT = radiotherapy.
Notably, a combined diagnostic model incorporating clinical pathological features and molecular markers exhibited the best predictive performance (AUC = 0.82, 95% CI: 0.77–0.87, P < .001), significantly outperforming individual predictive factors.
3.7. Stratified Cox regression analysis of surgery–radiotherapy interval
Stratified Cox regression analysis revealed that the impact of S–RT interval on DFS varies significantly among patients with different clinical characteristics (Table 6). In the age stratification analysis, patients aged ≥60 years (HR = 1.07, 95% CI: 1.03–1.11, P = .001) showed a more pronounced effect of interval time compared to younger patients (HR = 1.02, P = .312), with a significant interaction effect (P = .042).
Table 6.
Stratified Cox regression analysis by surgery–radiotherapy interval.
| Stratified variable | Subgroup | HR (95% CI) | P-value | Interaction P-value |
|---|---|---|---|---|
| Age | <60 yr (n = 89) | 1.02 (0.98–1.06) | .312 | .042 |
| ≥60 yr (n = 61) | 1.07 (1.03–1.11) | .001 | ||
| FIGO stage | III (n = 77) | 1.05 (1.01–1.09) | .012 | .038 |
| IV (n = 21) | 1.09 (1.04–1.15) | <.001 | ||
| BMI | <30 kg/m2 (n = 96) | 1.03 (0.99–1.07) | .178 | .214 |
| ≥30 kg/m2 (n = 54) | 1.06 (1.01–1.11) | .018 | ||
| Histology | Endometrioid (n = 66) | 1.03 (0.98–1.08) | .254 | .026 |
| Serous/undifferentiated (n = 84) | 1.08 (1.04–1.12) | <.001 | ||
| Lymph node metastasis | Negative (n = 99) | 1.02 (0.98–1.06) | .347 | .009 |
| Positive (n = 51) | 1.10 (1.05–1.15) | <.001 |
BMI = body mass index, FIGO = Fédération Internationale de Gynécologie et d'Obstétrique, HR = hazard ratio.
In the FIGO stage subgroup analysis, stage IV patients (HR = 1.09, 95% CI: 1.04–1.15, P < .001) were more sensitive to extended intervals than stage III patients (HR = 1.05, P = .012), with a significant interaction effect (P = .038).
4. Discussion
This study, through a retrospective analysis of 150 high-risk EC patients, revealed the significant impact of the S–RT interval on patient prognosis. The findings indicate that the S–RT interval is an independent prognostic factor for DFS. The 2-year DFS rate of the short interval group (1–4 weeks) was significantly higher than that of the long interval group (>8 weeks). This discovery provides important evidence for optimizing treatment sequencing in clinical practice. From a clinical perspective, the results suggest that, for high-risk EC patients, radiotherapy should ideally be initiated within 4 weeks after surgery to minimize the recurrence risk. However, it should be noted that some patients may postpone radiotherapy due to poor postoperative recovery, complications, or objective scheduling constraints. Therefore, these findings should be interpreted in the context of real-world clinical circumstances.
Of particular note is that patients with a delay of more than 8 weeks in starting radiotherapy had a 90% increased risk of recurrence. This effect was more pronounced in elderly patients (≥60 years), FIGO stage IV patients, and those with serous or undifferentiated carcinoma. These high-risk subgroups may benefit the most from a more aggressive treatment sequencing strategy. From a potential mechanistic perspective, the reasons for the impact of S–RT interval on prognosis could include: postoperative residual micro-lesions proliferating or acquiring radiotherapy resistance during the waiting period[16,17]; delayed treatment potentially altering the tumor microenvironment, such as exacerbating hypoxic conditions or increasing immune suppression[18]; and at the molecular level, patients with abnormal p53 expression having poorer prognosis, suggesting that genomic instability may play an intermediary role in time-dependent treatment effects.[19]
The findings of this study are consistent with some previous studies, but also present notable differences. In line with Colombo view that high-risk patients require comprehensive treatment,[20,21] our data further clarify the importance of treatment sequencing. However, contrasting with some studies suggesting that interval time does not affect prognosis, we found that the adverse effects of delayed radiotherapy are particularly prominent in certain subgroups. This could be attributed to the strict inclusion criteria for high-risk populations, longer follow-up periods, and more detailed molecular subtyping in this study. In clinical translation, the study results support the necessity of establishing fast-track post-surgical adjuvant treatment pathways, especially for patients with high-risk features such as deep myometrial invasion, lymph node metastasis, or abnormal p53 expression.[22] Medical institutions should consider optimizing treatment workflows to reduce delays in preoperative assessments, postoperative recovery, and radiotherapy planning. Additionally, for patients requiring delayed radiotherapy due to complications, consideration should be given to strengthening systemic therapies as a transition.[23]
This study has several limitations that need to be addressed. First, as a single-center retrospective study, despite controlling for confounding factors through strict inclusion criteria and multivariate analysis, selection bias may still exist. In particular, indication bias cannot be fully excluded – patients perceived to be at higher risk by clinicians may have been scheduled for earlier radiotherapy, which could potentially exaggerate the observed benefit of a shorter survey–RT interval. Second, the relatively limited sample size, particularly for certain subgroups (e.g., only 21 stage IV patients), warrants cautious interpretation of the analysis results. Third, while the classification of S–RT interval was based on clinical practice, the optimal cutoff value still requires validation in larger sample sizes. Moreover, the specific reasons for delayed radiotherapy (e.g., postoperative complications, patient compliance) were not thoroughly documented in the study, and these factors may themselves influence prognosis. Finally, the relatively short follow-up period (median 24 months) did not allow for an assessment of long-term survival differences. Future multi-center prospective studies are needed to further validate these findings and explore the predictive value of molecular markers such as POLE mutations and immune microenvironment in time-dependent treatment effects.
Despite these limitations, the study systematically confirmed the independent impact of S–RT interval on the prognosis of high-risk EC patients, providing significant reference for clinical practice. The conclusion suggests that for high-risk EC patients, particularly those who are elderly, in advanced stages, or have specific molecular features, radiotherapy should be started within 4 weeks post-surgery to optimize treatment outcomes and improve survival. This finding offers important guidance for formulating individualized treatment strategies and should be taken into consideration and applied in clinical practice.
Author contributions
Conceptualization: Huimin Wang, Xiaoqing Guo.
Data curation: Huimin Wang, Peijiang Lu, Xiaoqing Guo.
Formal analysis: Huimin Wang, Peijiang Lu, Xiaoqing Guo.
Validation: Peijiang Lu, Xiaoqing Guo.
Visualization: Huimin Wang, Peijiang Lu, Xiaoqing Guo.
Writing – original draft: Huimin Wang, Peijiang Lu, Xiaoqing Guo.
Writing – review & editing: Huimin Wang, Xiaoqing Guo.
Abbreviations:
- DFS
- disease-free survival
- EC
- endometrial cancer
- LVSI
- lymphovascular space invasion
The authors have no funding and conflicts of interest to disclose.
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
How to cite this article: Wang H, Lu P, Guo X. The impact of surgery–radiotherapy interval on prognosis in high-risk endometrial cancer patients: A single-center retrospective analysis. Medicine 2026;105:7(e45074).
Contributor Information
Huimin Wang, Email: wanghuimin188@163.com.
Peijiang Lu, Email: lupeijiang@aliyun.com.
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