Optimal Adjuvant Strategy in Intermediate-Risk Cervical Cancer: A Systematic Review and Meta-Analysis

Optimal Adjuvant Strategy in Intermediate-Risk Cervical Cancer: A Systematic Review and Meta-Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Optimal Adjuvant Strategy in Intermediate-Risk Cervical Cancer: A Systematic Review and Meta-Analysis Akira Yokoi, Hiroko Machida, Mika Okazawa-Sakai, Koji Nishino, and 22 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8559901/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 Apr, 2026 Read the published version in International Journal of Clinical Oncology → Version 1 posted 5 You are reading this latest preprint version Abstract Objective To evaluate the efficacy and safety of adjuvant treatment strategies following radical hysterectomy for intermediate-risk, early-stage cervical cancer using a reconstructed HR meta-analysis. Methods A systematic review and meta-analysis was conducted by the Japan Society of Gynecologic Oncology Cervical Cancer Committee. PubMed/MEDLINE, Cochrane, and Ichushi were searched on July 29, 2025, using “cervical cancer,” “intermediate risk,” and “adjuvant therapy.” Studies comparing adjuvant radiotherapy alone (RT) with no further treatment (NFT), concurrent chemoradiotherapy (CCRT), or systemic chemotherapy (CT) after conventional radical hysterectomy were independently reviewed by two reviewers. Primary outcomes were survival and grade ≥ 3 treatment-related toxicities. Results Of 402 screened articles, 24 studies comprising 9,278 patients were included: RT (n = 4,167), NFT (n = 2,057), CCRT (n = 2,118), and CT (n = 936). The majority of studies enrolled patients with ≥ 2 Sedlis risk factors (median 84.2%, interquartile range 44.7–100%). Compared with NFT, RT significantly improved recurrence-free survival (HR 0.61, P < 0.01) but did not confer a significant overall survival benefit (HR 0.77, P = 0.09). RT also reduced recurrence in patients with a single risk factor (HR 0.55, P < 0.01). RT showed no survival disadvantage compared with CCRT (recurrence-free survival: HR 1.26; overall survival: HR 1.07), and survival outcomes were comparable between RT and CT (recurrence-free survival: HR 0.86; overall survival: HR 1.16), (all P > 0.05). Grade ≥ 3 toxicities were significantly lower with RT than with CCRT (odds ratio 0.25; P < 0.001). Conclusion Adjuvant RT represents an effective and well-tolerated postoperative strategy for intermediate-risk, early-stage cervical cancer. Adjuvant CT may represent a potential alternative option. cervical cancer systematic review intermediate-risk survival complications Figures Figure 1 Figure 2 Figure 3 INTRODUCTION Cervical cancer remains a major global health burden and is one of the most common malignancies among women worldwide [ 1 ]. For patients with early-stage disease, radical hysterectomy with pelvic lymph node assessment remains the cornerstone of primary treatment and yields favorable oncologic outcomes [ 2 ]. Nevertheless, disease recurrence occurs in a subset of patients despite optimal surgical management, highlighting the need for appropriate postoperative risk stratification and adjuvant therapy in selected cases [ 3 ]. Cisplatin-based concurrent chemoradiotherapy (CCRT) is established as the standard adjuvant treatment for patients with high-risk pathological features following radical surgery, supported by randomized controlled trials demonstrating survival benefits [ 4 ]. Postoperative risk stratification in early-stage cervical cancer is primarily based on surgical–pathological factors and classifies patients into high-, intermediate-, and low-risk groups [ 4 , 5 ]. Intermediate-risk disease is defined by combinations of large tumor size, deep stromal invasion, and lymphovascular space invasion (LVSI). This risk category was initially established in Gynecologic Oncology Group (GOG) studies and subsequently evaluated in the randomized GOG-92 trial, which demonstrated that adjuvant external-beam radiotherapy (RT) significantly reduced recurrence compared with observation in node-negative, parametria-negative stage IB disease with two or more Sedlis criteria [ 6 , 7 ]. Despite these findings, the optimal postoperative management for intermediate-risk, early-stage cervical cancer remains controversial, and international guidelines provide inconsistent recommendations [ 5 ]. Although several systematic reviews and meta-analyses have examined this issue, most relied on pooled event rates or dichotomous outcomes, limiting assessment of time-dependent oncologic effects [ 8 , 9 ]. Therefore, this systematic review and meta-analysis incorporated recent trial-era evidence and applied a reconstructed hazard ratio–based approach to evaluate time-to-event outcomes, assessing the efficacy and safety of adjuvant RT alone compared with no further treatment (NFT), systemic chemotherapy (CT), and CCRT following radical hysterectomy. PATIENTS AND METHODS Literature Search and Study Selection The literature search was conducted per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines [ 10 ] using the PubMed/MEDLINE, Cochrane, and Ichushi databases with the keywords “cervical cancer,” “intermediate-risk,” and “adjuvant therapy” on July 29, 2025 (Fig. 1, Supplementary Table S1). Ethical approval was not required for this systematic review and meta-analysis because all data were obtained from previously published peer-reviewed studies. This study was registered in PROSPERO to ensure transparency and methodological rigor (registration number: 1186079). Eligibility Criteria Articles based on comparing postoperative adjuvant RT alone with other postoperative adjuvant therapies, including NFT, CCRT, and CT in women with early-stage cervical cancer, were eligible for inclusion. Articles were stratified by postoperative adjuvant treatment strategies for patients with Stage I or II cervical cancer according to the International Federation of Gynecology and Obstetrics staging system. Patients with early-stage cervical cancer underwent radical hysterectomy with or without bilateral salpingo-oophorectomy and nodal evaluation. Our study included randomized controlled trials, meta-analyses, and case-control series reported in the English literature with adequate data on patient demographics, primary treatment, perioperative complications, survival outcomes, and follow-up. Data Extraction The references of all the selected articles were reviewed, and articles that met the inclusion criteria were assessed. If multiple publications from the same clinical trial were available, the most recent publication was included. Retrospective interventional or observational studies with substantial cases were selected. Non-case-control trials, single-arm studies in any postoperative adjuvant treatment, systematic reviews, reports on high-risk groups (including nodal metastasis, parametrial involvement, and surgical margin positivity), and basic scientific research were excluded. Additionally, studies involving neoadjuvant CT or RT or with unknown treatment information were excluded. Clinical Information and Definitions The following variables were extracted from the selected studies: year of publication, study type, country, details of initial treatment (type of radical hysterectomy, adnexal evaluation, or nodal evaluation) and postoperative adjuvant treatments (NFT, RT, CCRT, and CT), details of pathological information (histological subtypes, including squamous cell carcinoma or non-squamous cell carcinoma,LVSI, deep stromal invasion, and tumor size ≥ 4 cm), details of adjuvant treatment-related complications, and recurrence-free and overall survival. Primary treatment was defined as radical hysterectomy with or without bilateral salpingo-oophorectomy and comprehensive nodal evaluation [ 11 ]. Adjuvant RT comprised postoperative pelvic external beam RT. Adjuvant CCRT was defined as RT combined with platinum-based CCRT. Adjuvant CT was administered as a systemic anticytotoxic agent. The proportion of risk factors (≥ 2 factors), including tumor size, LVSI, and deep stromal invasion, meeting the Sedlis criteria [ 6 ] was calculated from available data. Recurrence-free survival was defined as the time between the primary treatment and the relapse of cervical cancer. Overall survival indicated the period between disease diagnosis and death from any cause or cancer-specific death. Treatment-related complications were defined as critical adverse events if graded as ≥ 3 according to the National Cancer Institute's Common Terminology Criteria for Adverse Events [ 12 ]. Statistical Analysis To synthesize survival data, the HRs and their 95% CIs reported in each study were extracted and pooled after logarithmic transformation. When HRs were not explicitly reported, data were reconstructed from Kaplan–Meier curves using the Tierney method, and a reconstructed HR-based meta-analysis was conducted [ 13 ]. If HR could not be utilized with sufficient power, the number of patients in each treatment arm who experienced an event was compared to estimate the risk ratio (RR) with a 95% confidence interval (CI) for dichotomous variables. RR was also used to assess adverse events. For continuous variables, the final values and standard deviations were calculated to determine differences in mean values. P -values < 0.05 were considered statistically significant. Data Extraction and Management The study protocol was developed in Japanese and conducted as part of a guideline revision project by the Guideline Committee of the Japan Society of Gynecologic Oncology (JSGO). Data were entered into a reference database and extracted independently by three reviewers who were blinded to each other’s assessments (A.Y., H.M., and staff personnel from the Japan Medical Library Association). The quality of the studies was independently assessed by the reviewers (A.Y. and H.M.), and disagreements were resolved through discussion with a third reviewer from the Expert Panel of the JSGO Committee. In cases of missing data or unclear methods, further information was obtained from other published studies on the same trials. For each study, we recorded the detailed methods, study population, sample size, inclusion and exclusion criteria, interventions and comparisons, patient demographics, treatment details, and survival outcomes. Assessment of the Risk of Bias Using the risk of bias in nonrandomized studies as an intervention tool, the risk of bias was independently assessed by two authors for each study (A.Y. and H.M.). The possible biases included selection, preference, detection, attribution, and reporting (Supplementary Table S2). As blinding the participants or physicians to the assigned treatment was infeasible, blinding (performance and detection biases) was only assessed for outcomes. To investigate publication bias, we performed funnel plot analysis (Figs. 2 and 3 ). Assessment of Heterogeneity HR was used as the measure of association across studies, and Mantel–Haenszel random effects models were used to calculate summary estimates. Study heterogeneity was assessed through the visual inspection of forest plots and statistical evaluation using Cochran’s Q test and the I 2 test. Study data were synthesized to obtain the overall estimates of the treatment effects. The Review Manager software (Version 5.3, Copenhagen: The Nordic Cochrane Centre, The Cochrane Collaboration, 2014) was used. The confidence level in the summary data was examined using the Grading of Recommendations Assessment, Development, and Evaluation for Studies of Interventions and Diagnostic Test Accuracy. RESULTS Study selection The literature search initially revealed 402 articles (Fig. 1). Of these, 337 were excluded because they were not case-control studies, did not focus on the target disease or treatment, represented basic research, were duplicates, or were written in languages other than English. After the full-text assessment of the remaining 65 articles, one additional article was identified through reference screening. Twenty-four studies met the eligibility criteria [ 6 ] [ 7 ] [ 14 – 36 ], comprising 2 and 22 prospective and retrospective studies, respectively. The data included outcomes for RT (n = 4,167), NFT (n = 2,057), CCRT (n = 2,118), and CT (n = 932) in 24, 15, 11, and 7 studies, respectively, among patients with intermediate-risk early-stage cervical cancer (Fig. 1). Risk of bias of included studies Except for two prospective randomized controlled trials (RCTs), the included studies exhibited a moderate-to-serious risk of bias (Supplementary Table 1). Publication bias was evaluated using funnel plots (Figs. 2 , 3 ). As expected for cohort studies, several articles [ 14 – 16 ] did not provide sufficient information regarding the assessment of confounding factors or baseline differences between the compared groups. Study characteristics The characteristics of the included studies are summarized in Table 1 . Most of the studies were published in 2010 or later (84.0%) and were Asian reports (68.0%). A total of 9,274 patients were analyzed, including 4,167 (44.9%) who received RT, 2,057 (22.2%) who did not receive adjuvant therapy, 2,118 (22.8%) who had CCRT, and 932 (10.0%) who underwent CT. Across all studies, the proportion of patients with ≥ 2 intermediate-risk factors had a median of 84.2% (interquartile range [IQR], 43.7–100). The prevalence of individual risk factors had a median of 28.6% (IQR, 20.3–32.0) for non-squamous cell carcinoma histology, 59.1% (43.6–71.5) for LVSI, 78.3% (61.3–83.0) for deep stromal invasion, and 38.0% (22.9–58.0) for tumor size ≥ 4 cm. The proportions of patients with ≥ 2 risk factors were similar among treatment comparisons: 76.0% (IQR, 43.5–100) for RT vs. NFT, 100% (57.2–100) for RT vs. CCRT, and 44.3% (0.0–92.3) for RT vs. CT ( P = 0.21). In addition, the follow-up duration was comparable between RT and the other treatment groups, including NFT, CCRT, and CT (median 56.4 vs. 50.9 months, P = 0.78). Table 1 Characteristics of the studies Study population Author, year Study type Country No. RT No. Other Tx Total No. Risk factor ≥ 2* Non-SCC LVSI Present Deep SI Size ≥ 4cm Follow-up(m) RT Other Tx Radiotherapy vs No Further Treatment NFT GOG92. 1999 / 2006 RCT USA 137 140 277 100%** 21.3% 70.4% 75.8% 26.7% 60.0 60.0 Jiaxin F et al. 2025 Retro. China 115 50 219 0% 100% 5.5% 80.8% 13.7% 50.0 55.0 Matsuo K et al. 2024 Retro. Japan 188 481 1,084 92.3% 39.4% 73.8% 60.0% 81.0% 67.2 67.2 Tuscharoenporn T et al. 2023 Retro. Thailand 108 111 219 100%** 28.3% 90.9% 84.0% na 76.1 95.4 Cibula D et al. 2023 Retro. International 418 274 692 76.0% + 29.1% 76.0% na 42.6% 56.4 51.6 Turkmen O et al. 2022 Retro. Turkey 67 67 183 60.1% 23% 57.9% 82.0% 33.9% 48.0 48.0 Zhang J et al. 2022 Retro. China 264 68 976 23.6% 15.7% 9.2% 37.3% 34.4% 49.0 48.0 Nasioudis D et al. 2021 Retro. USA 378 387 765 100%** 31.5% 65.6% na 50.2% 45.0 44.8 Cao L et al. 2021 Retro. China 283 85 861 100%** 0% 46.5% 48.7% 75.2% 64.0 62.0 Nie J et al. 2021 Retro. China 61 71 571 44.3% 15.1% 52.4% 75.7% 22.9% 62.0 62.0 Kim SI et al. 2020 Retro. Korea 53 30 83 100%** 16.8% 60.2% 78.3% 71.1% 40.4 40.4 Akilli H et al. 2020 Retro. Turkey 68 66 134 100%** 17.9% 73.9% 86.3% 33.6 54.0 51.0 Nakamura K et al. 2016 Retro. Japan 19 46 75 33.3% 32.0% 42.7% 61.3% 0% 90.6 78.7 Ryu SY et al. 2011 Retro. Korea 49 34 172 40.7% 24.9% 11.4% 80.0% na 44.6 44.6 Ayhan A et al. 2004 Retro. Turkey 69 147 216 52.3% na 71.8% 73.1% 5.1% 31.2 31.2 Radiotherapy vs Concurrent Chemoradiotherapy CCRT GOG0263. 2025 RCT Korea 158 158 316 100% 16.3% 72.7% 81.6% na 76.5 76.5 Agustí N et al. 2025 Retro. USA 434 434 868 100%** 40.0% 69.1% na 57.1% 64.2 66.0 Matsuo K et al. 2024 Retro. Japan 188 190 1,084 92.3% 39.4% 73.8% 60.0% 81.0% 67.2 67.2 Zhang J et al. 2022 Retro. China 264 118 529 43.5% 28.8% 17.0% 68.8% 63.5% 49.0 49.0 Cao L et al. 2021 Retro. China 283 493 861 100%** 0% 46.5% 48.7% 75.2% 64.0 62.0 Park W et al. 2020 Retro. Korea 243 73 316 70.9% 26.6% 46.2% 88.0% 50.9% 70.0 70.0 Mahmoud O et al. 2016 Retro. USA 429 440 869 100%** 37.0% 32.0% na 58.0% 48.0 48.0 Nakamura K et al. 2016 Retro. Japan 10 14 75 33.3% 32.0% 42.7% 61.3% 0% 90.6 98.0 Song S et al. 2012 Retro. Korea 56 54 110 100% 21.8% 63.6% 93.6% na 75.6 48.0 Ryu SY et al. 2011 Retro. Korea 49 89 172 40.7% 24.9% 11.4% 80.0% na 44.6 44.6 Kim K et al. 2009 Retro. Korea 24 55 79 na 29.1% 49.4% 91.1% 38.0% 54.0 48.0 Radiotherapy vs Chemotherapy CT Jiaxin F et al. 2025 Retro. China 115 50 219 0% 100% 5.5% 80.8% 13.7% 50.0 55.0 Matsuo K et al. 2024 Retro. Japan 188 225 1,084 92.3% 39.4% 73.8% 60.0% 81.0% 67.2 67.2 Taguchi A et al. 2023 Retro. Japan 311 311 960 62% 32.0% 62.9% 57.6% 25.0% 63.0 63.0 Zhang J et al. 2022 Retro. China 264 79 976 23.6% 15.7% 9.2% 37.3% 34.4% 49.0 49.0 Nie J et al. 2021 Retro. China 61 164 571 44.3% 15.1% 52.4% 75.7% 22.9% 62.0 62.0 Li L et al. 2016 Retro. China 68 65 133 0% 8.3% na 24.8% na 36.4 30.8 Lee KB et al. 2008 Retro. Korea 42 38 80 100% 20.0% 48.8% 78.8% na 56.4 40.7 * Risk factors were defined by the Sedlis criteria; non-SCC was reported but not counted. ** The number of risk factors was not specified, though definitions followed the Sedlis criteria. Abbreviations: No., number; RT, radiotherapy; Tx, treatment; SCC. Squamous cell carcinoma; LVSI, lymph vascular invasion; SI, stromal invasion; na, not applicable; (m), month; Retro., retrospective study, AND RCT; randomized controlled trial. Synthesis of results I. Survival, recurrence, and toxicity outcomes: RT versus NFT Our study conducted a meta-analysis of the data from one RCT and 14 retrospective studies between the RT and NFT groups (n = 4,334) (Fig. 2 ). Adjuvant RT was associated with a significantly improved recurrence-free survival compared with that under NFT (HR 0.61, 95%CI 0.44–0.86; P = 0.005). Although the overall survival also tended to favor the RT group, the difference was not statistically significant (HR 0.77, 95%CI 0.56–1.04; P = 0.09) (Figs. 2 and 3 ). Furthermore, among patients with a single risk factor, adjuvant RT significantly reduced recurrence compared with that under NFT (recurrence-free survival: HR 0.55, 95%CI 0.31–0.97; P = 0.04). Recurrence patterns were evaluated based on reported events owing to limited time-dependent data. Local recurrence was less frequent in the RT group than in the NFT group (8.3% vs. 12.2%; RR 0.75, 95%CI 0.56–0.99; P = 0.04), whereas distant recurrence rates were comparable between the groups (6.3% vs. 4.8%; RR 1.04, 95%CI 0.47–2.30; P = 0.93). Grade ≥ 3 adverse events associated with adjuvant treatment were reported in five studies. The incidence of severe adverse events was significantly higher in the RT group than in the NFT group (6.5% vs. 1.9%; RR 5.17, 95%CI 2.70–9.90; P < 0.001). The most common severe adverse events were genitourinary (6.3%), gastrointestinal (3.2%), and hematologic (1.6%) toxicities. II. Survival, recurrence, and toxicity outcomes: RT versus CCRT For the RT and CCRT groups (n = 4,256), our study conducted a meta-analysis of the data from one RCT and 10 retrospective studies (Figs. 2 and 3 ). Recurrence-free survival showed no significant differences between the RT and CCRT groups (HR 1.26, 95%CI 0.92–1.73; P = 0.16). In addition, overall survival did not differ significantly between the groups (HR 1.07, 95%CI 0.84–1.37; P = 0.58). Recurrence patterns were evaluated based on reported events in five studies owing to insufficient time-dependent data. Local recurrence rates were comparable between the RT and CCRT groups (5.4% vs. 2.7%; RR 2.13, 95%CI 0.89–5.07, P = 0.09). In contrast, distant recurrence tended to occur more frequently in the RT group than in the CCRT group (9.5% vs. 6.2%; RR 1.48, 95%CI 1.04–2.10, P = 0.03). Grade ≥ 3 adverse events related to adjuvant treatment were reported in five studies. The incidence of severe adverse events was significantly lower in the RT group than in the CCRT group (11.1% vs. 38.7%; RR 0.28, 95%CI 0.17–0.44, P < 0.001). The most common severe adverse events were hematologic toxicities (RT vs. CCRT: 6.0% vs. 33.6%), followed by gastrointestinal (3.9% vs. 7.4%) and genitourinary (2.0% vs. 3.0%) toxicities. III. Survival, recurrence, and toxicity outcomes: RT versus CT Moreover, our study compared the outcomes between RT and CT groups (n = 1,981). The meta-analysis of data from seven retrospective studies is illustrated in Figs. 2 and 3 . Recurrence-free survival exhibited no significant differences between the RT and CT groups (HR 0.86, 95%CI 0.51–1.46, P = 0.59). In addition, overall survival showed no significant differences between the two groups (HR 1.16, 95%CI 0.76–1.78, P = 0.48). Recurrence patterns were evaluated based on the reported events in only two studies. Local and distant recurrence rates were comparable between the RT and CT groups (Local: 0.9% vs. 3.8%; RR 0.49, 95%CI 0.02–13.13, P = 0.67; Distant: 2.7% vs. 3.8%; RR 0.69, 95%CI 0.16–2.98, P = 0.62). Only one study reported events related to adjuvant treatment. The most common severe adverse event was hematological toxicity in the CT group (RT vs. CT: 27.9% vs. 53.8%), whereas gastrointestinal (4.4% vs. 0%) and genitourinary (5.9% vs. 0%) toxicities were more frequent in the RT group. Discussion Summary of Main Results This systematic review and meta-analysis evaluated adjuvant treatment strategies for patients with intermediate-risk, early-stage cervical cancer following radical hysterectomy and pelvic lymphadenectomy. The results indicate that postoperative RT significantly reduces recurrence compared with NFT, whereas CCRT does not provide additional benefit over RT alone. Notably, RT was associated with reduced recurrence even among patients with a single intermediate-risk factor, underscoring its role as a fundamental adjuvant modality in this setting. Systemic CT demonstrated recurrence outcomes comparable to RT, suggesting a potential alternative approach in selected patients. However, the lack of a clear overall survival benefit across treatment strategies highlights the importance of balancing oncologic efficacy against treatment-related morbidity when selecting adjuvant therapy. Results in the Context of Published Literature A major challenge highlighted in our review is the inconsistent definition of the intermediate-risk category across geographical regions and guideline frameworks [ 37 ]. Although the Sedlis criteria remain acceptable [ 6 ], several contemporary models incorporate different thresholds for tumor size, various grading systems for LVSI, and different methodologies in defining deep stromal invasion. These discrepancies hinder direct comparisons across studies and may contribute to conflicting results regarding the effectiveness of treatment intensification. Therefore, the standardization of definitions, ideally supported by prospective validation, is crucial to optimizing the generalizability of future evidence. Another key finding was that intermediate-risk features did not confer uniform biological or prognostic significance [ 37 ]. Factors such as extensive LVSI and deeply invasive adenocarcinoma were associated with a markedly higher risk of recurrence than tumor size alone [ 37 , 38 ], indicating substantial heterogeneity within the intermediate-risk category. This suggests that the current classification may be overly broad and that refined risk assessment incorporating quantitative deep stromal invasion and structured LVSI scoring may improve patient selection for systemic therapy [ 38 ]. Furthermore, given that histopathological subtype influences postoperative treatment responsiveness [ 39 , 40 ], histology-based subgroup analyses should be incorporated into future studies to facilitate more tailored therapeutic strategies. The evolving landscape of radiation delivery complicates the interpretation of historical data, as many landmark trials predated the widespread use of intensity-modulated radiotherapy (IMRT), which reduces toxicity without compromising local control [ 39 ]]. Accordingly, the efficacy of adjuvant radiotherapy should be interpreted in the context of modern radiotherapy practice. Notably, the NRG Oncology/GOG-263 trial conducted in the IMRT era did not demonstrate survival benefit from the addition of cisplatin-based chemotherapy, suggesting that the incremental value of postoperative CCRT may be limited, particularly in intermediate-risk populations. Systemic treatment options for cervical cancer are rapidly evolving [ 41 ]. Particularly, immune checkpoint inhibitors have transformed the management of recurrent and metastatic disease, and ongoing trials are exploring their use in earlier treatment settings [ 41 ]. In the present study, adjuvant CT for early-stage, intermediate-risk cervical cancer resulted in survival outcomes comparable to postoperative RT, suggesting its feasibility as a postoperative option. This finding may be especially relevant in Japan, where a higher prevalence of underweight young women may increase susceptibility to radiation-related toxicity [ 42 , 43 ]. The ongoing RCT (JGOG1082) is evaluating adjuvant CT as an alternative to RT in high-risk early-stage cervical cancer, with potential implications for intermediate-risk disease. Strengths and Weaknesses The primary strength of this study lies in its consideration of an HR-based meta-analysis rather than a simple pooled analysis of survival data derived from event counts and total sample sizes, as previously reported. To synthesize survival data, the HRs and their 95% CIs reported in each study were extracted and pooled after logarithmic transformation. This approach enabled us to apply an appropriate strategy to synthesize time-to-event outcomes. However, this study has some limitations. First, although this meta-analysis included 24 studies, only two were RCTs, which may limit the methodological rigor and introduce potential bias (Supplemental Table S1). Moreover, despite the widespread use of the Sedlis criteria, specific risk factors varied across studies, which may have affected the results. Second, the limited number of eligible studies precluded stratified analyses according to histological subtype. Third, although all patients underwent radical hysterectomy with lymph node assessment, the extent of surgical radicality could not be consistently determined, and details regarding radiotherapy techniques—including the use of contemporary toxicity-sparing approaches such as intensity-modulated radiotherapy (IMRT)—as well as chemotherapy regimens were insufficiently reported to allow stratified analyses. These methodological and reporting limitations may have influenced the study results. The available evidence is limited by the retrospective design and methodological heterogeneity of most included studies. Ongoing prospective trials, including the CERVANTES study [ 44 ], are expected to clarify whether adjuvant therapy is necessary after high-quality radical hysterectomy with adequate nodal assessment. Conclusions This systematic review and meta-analysis indicate that adjuvant RT is preferable to NFT for patients with intermediate-risk, early-stage cervical cancer. CCRT did not demonstrate clear superiority over RT alone, while systemic CT may represent a potential alternative, although its role remains uncertain. These findings support postoperative RT as the current cornerstone of adjuvant management, and routine de-escalation to observation alone should be avoided in the absence of clearly favorable biological features. Declarations IRB: No ethical approval was required for this systematic review with meta-analysis, as all data had already been published in peer-reviewed journals. No patients were involved in the design, conduct, or interpretation of our study. PROSPERO: Registration number: 1186079 registration date: 7 November 2025 Declaration of competing interest: Tokai University Research Organization (H.M). All other authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding Sources ： None Author contributions: Study concept and design: A.Y., H.M., K.M ; Methodology: A.Y., H.M., S.S. ; Investigation: A.Y., H.M. ; Supervision: All the authors ; Writing – original draft: A.Y., H.M.; Writing – review and editing: All the authors discussed the results and commented on the manuscript. Acknowledgments: This project was assisted by an Expert Panel of the Japan Society of Gynecologic Oncology via the Medical Information Network Distribution Service, which received financial support from the Ministry of Health, Labor and Welfare of Japan as a consignment project. Declaration of generative AI and AI-assisted technologies in the manuscript: None Availability of data, code and other materials : In accordance with the journal’s guidelines, we will provide our data for independent analysis by a selected team by the Editorial Team for the purposes of additional data analysis or for the reproducibility of this study in other centers if such is requested. References Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A et al (2021) Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. 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Gynecol Oncol 162:532–538 Chung HC, Ros W, Delord JP, Perets R, Italiano A, Shapira-Frommer R et al (2019) Efficacy and Safety of Pembrolizumab in Previously Treated Advanced Cervical Cancer: Results From the Phase II KEYNOTE-158 Study. J Clin oncology: official J Am Soc Clin Oncol 37:1470–1478 Takeuchi M, Honda M, Tsuboi A, Minato-Inokawa S, Kurata M, Wu B et al (2022) Weight Trajectory Since Birth, Current Body Composition, Dietary Intake, and Glucose Tolerance in Young Underweight Japanese Women, vol 3. Women's health reports, New Rochelle, NY, pp 215–221 Lee J, Chang CL, Lin JB, Wu MH, Sun FJ, Wu CJ et al (2018) The Effect of Body Mass Index and Weight Change on Late Gastrointestinal Toxicity in Locally Advanced Cervical Cancer Treated With Intensity-modulated Radiotherapy. 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Int J Gynecol cancer: official J Int Gynecol Cancer Soc 32:1327–1331 Cite Share Download PDF Status: Published Journal Publication published 21 Apr, 2026 Read the published version in International Journal of Clinical Oncology → Version 1 posted Editorial decision: Minor revisions 09 Mar, 2026 Reviewers agreed at journal 21 Jan, 2026 Reviewers invited by journal 20 Jan, 2026 First submitted to journal 19 Jan, 2026 Editor assigned by journal 13 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8559901","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":577761947,"identity":"90111c4e-5fb0-4532-a55f-83db018cc44f","order_by":0,"name":"Akira Yokoi","email":"","orcid":"","institution":"Nagoya University: Nagoya Daigaku","correspondingAuthor":false,"prefix":"","firstName":"Akira","middleName":"","lastName":"Yokoi","suffix":""},{"id":577761948,"identity":"00f0dc3f-5485-4736-80f0-9f7fdbeff1ee","order_by":1,"name":"Hiroko 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14:51:57","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1765946,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of the meta-analysis and funnel plot for recurrence-free survival based on adjuvant treatment with early-stage cervical cancer\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8559901/v1/1672dcd7c75274f93c066315.png"},{"id":100900632,"identity":"c4685e0a-34cb-44c0-8a33-74e3a8cdeef7","added_by":"auto","created_at":"2026-01-22 14:51:58","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1525173,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of the meta-analysis and funnel plot for overall survival based on adjuvant treatment with early-stage cervical cancer\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8559901/v1/01ea0e676225c6c96bb9de2b.png"},{"id":107929474,"identity":"6ff7c74b-407a-4d79-8d06-f79fe53e5c92","added_by":"auto","created_at":"2026-04-27 16:15:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3987541,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8559901/v1/5b32c366-6cc6-4a5b-8ac0-b516e6e56313.pdf"}],"financialInterests":"","formattedTitle":"Optimal Adjuvant Strategy in Intermediate-Risk Cervical Cancer: A Systematic Review and Meta-Analysis","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eCervical cancer remains a major global health burden and is one of the most common malignancies among women worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. For patients with early-stage disease, radical hysterectomy with pelvic lymph node assessment remains the cornerstone of primary treatment and yields favorable oncologic outcomes [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Nevertheless, disease recurrence occurs in a subset of patients despite optimal surgical management, highlighting the need for appropriate postoperative risk stratification and adjuvant therapy in selected cases [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Cisplatin-based concurrent chemoradiotherapy (CCRT) is established as the standard adjuvant treatment for patients with high-risk pathological features following radical surgery, supported by randomized controlled trials demonstrating survival benefits [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePostoperative risk stratification in early-stage cervical cancer is primarily based on surgical\u0026ndash;pathological factors and classifies patients into high-, intermediate-, and low-risk groups [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Intermediate-risk disease is defined by combinations of large tumor size, deep stromal invasion, and lymphovascular space invasion (LVSI). This risk category was initially established in Gynecologic Oncology Group (GOG) studies and subsequently evaluated in the randomized GOG-92 trial, which demonstrated that adjuvant external-beam radiotherapy (RT) significantly reduced recurrence compared with observation in node-negative, parametria-negative stage IB disease with two or more Sedlis criteria [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite these findings, the optimal postoperative management for intermediate-risk, early-stage cervical cancer remains controversial, and international guidelines provide inconsistent recommendations [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Although several systematic reviews and meta-analyses have examined this issue, most relied on pooled event rates or dichotomous outcomes, limiting assessment of time-dependent oncologic effects [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Therefore, this systematic review and meta-analysis incorporated recent trial-era evidence and applied a reconstructed hazard ratio\u0026ndash;based approach to evaluate time-to-event outcomes, assessing the efficacy and safety of adjuvant RT alone compared with no further treatment (NFT), systemic chemotherapy (CT), and CCRT following radical hysterectomy.\u003c/p\u003e"},{"header":"PATIENTS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eLiterature Search and Study Selection\u003c/h2\u003e \u003cp\u003eThe literature search was conducted per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] using the PubMed/MEDLINE, Cochrane, and Ichushi databases with the keywords \u0026ldquo;cervical cancer,\u0026rdquo; \u0026ldquo;intermediate-risk,\u0026rdquo; and \u0026ldquo;adjuvant therapy\u0026rdquo; on July 29, 2025 (Fig.\u0026nbsp;1, Supplementary Table S1). Ethical approval was not required for this systematic review and meta-analysis because all data were obtained from previously published peer-reviewed studies. This study was registered in PROSPERO to ensure transparency and methodological rigor (registration number: 1186079).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEligibility Criteria\u003c/h3\u003e\n\u003cp\u003eArticles based on comparing postoperative adjuvant RT alone with other postoperative adjuvant therapies, including NFT, CCRT, and CT in women with early-stage cervical cancer, were eligible for inclusion. Articles were stratified by postoperative adjuvant treatment strategies for patients with Stage I or II cervical cancer according to the International Federation of Gynecology and Obstetrics staging system. Patients with early-stage cervical cancer underwent radical hysterectomy with or without bilateral salpingo-oophorectomy and nodal evaluation. Our study included randomized controlled trials, meta-analyses, and case-control series reported in the English literature with adequate data on patient demographics, primary treatment, perioperative complications, survival outcomes, and follow-up.\u003c/p\u003e\n\u003ch3\u003eData Extraction\u003c/h3\u003e\n\u003cp\u003eThe references of all the selected articles were reviewed, and articles that met the inclusion criteria were assessed. If multiple publications from the same clinical trial were available, the most recent publication was included. Retrospective interventional or observational studies with substantial cases were selected. Non-case-control trials, single-arm studies in any postoperative adjuvant treatment, systematic reviews, reports on high-risk groups (including nodal metastasis, parametrial involvement, and surgical margin positivity), and basic scientific research were excluded. Additionally, studies involving neoadjuvant CT or RT or with unknown treatment information were excluded.\u003c/p\u003e\n\u003ch3\u003eClinical Information and Definitions\u003c/h3\u003e\n\u003cp\u003eThe following variables were extracted from the selected studies: year of publication, study type, country, details of initial treatment (type of radical hysterectomy, adnexal evaluation, or nodal evaluation) and postoperative adjuvant treatments (NFT, RT, CCRT, and CT), details of pathological information (histological subtypes, including squamous cell carcinoma or non-squamous cell carcinoma,LVSI, deep stromal invasion, and tumor size\u0026thinsp;\u0026ge;\u0026thinsp;4 cm), details of adjuvant treatment-related complications, and recurrence-free and overall survival. Primary treatment was defined as radical hysterectomy with or without bilateral salpingo-oophorectomy and comprehensive nodal evaluation [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Adjuvant RT comprised postoperative pelvic external beam RT. Adjuvant CCRT was defined as RT combined with platinum-based CCRT. Adjuvant CT was administered as a systemic anticytotoxic agent. The proportion of risk factors (\u0026ge;\u0026thinsp;2 factors), including tumor size, LVSI, and deep stromal invasion, meeting the Sedlis criteria [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] was calculated from available data. Recurrence-free survival was defined as the time between the primary treatment and the relapse of cervical cancer. Overall survival indicated the period between disease diagnosis and death from any cause or cancer-specific death. Treatment-related complications were defined as critical adverse events if graded as \u0026ge;\u0026thinsp;3 according to the National Cancer Institute's Common Terminology Criteria for Adverse Events [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eTo synthesize survival data, the HRs and their 95% CIs reported in each study were extracted and pooled after logarithmic transformation. When HRs were not explicitly reported, data were reconstructed from Kaplan\u0026ndash;Meier curves using the Tierney method, and a reconstructed HR-based meta-analysis was conducted [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. If HR could not be utilized with sufficient power, the number of patients in each treatment arm who experienced an event was compared to estimate the risk ratio (RR) with a 95% confidence interval (CI) for dichotomous variables. RR was also used to assess adverse events. For continuous variables, the final values and standard deviations were calculated to determine differences in mean values. \u003cem\u003eP\u003c/em\u003e-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData Extraction and Management\u003c/h2\u003e \u003cp\u003e The study protocol was developed in Japanese and conducted as part of a guideline revision project by the Guideline Committee of the Japan Society of Gynecologic Oncology (JSGO). Data were entered into a reference database and extracted independently by three reviewers who were blinded to each other\u0026rsquo;s assessments (A.Y., H.M., and staff personnel from the Japan Medical Library Association). The quality of the studies was independently assessed by the reviewers (A.Y. and H.M.), and disagreements were resolved through discussion with a third reviewer from the Expert Panel of the JSGO Committee. In cases of missing data or unclear methods, further information was obtained from other published studies on the same trials. For each study, we recorded the detailed methods, study population, sample size, inclusion and exclusion criteria, interventions and comparisons, patient demographics, treatment details, and survival outcomes.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAssessment of the Risk of Bias\u003c/h3\u003e\n\u003cp\u003eUsing the risk of bias in nonrandomized studies as an intervention tool, the risk of bias was independently assessed by two authors for each study (A.Y. and H.M.). The possible biases included selection, preference, detection, attribution, and reporting (Supplementary Table S2). As blinding the participants or physicians to the assigned treatment was infeasible, blinding (performance and detection biases) was only assessed for outcomes. To investigate publication bias, we performed funnel plot analysis (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eAssessment of Heterogeneity\u003c/h3\u003e\n\u003cp\u003eHR was used as the measure of association across studies, and Mantel\u0026ndash;Haenszel random effects models were used to calculate summary estimates. Study heterogeneity was assessed through the visual inspection of forest plots and statistical evaluation using Cochran\u0026rsquo;s Q test and the I\u003csup\u003e2\u003c/sup\u003e test. Study data were synthesized to obtain the overall estimates of the treatment effects. The Review Manager software (Version 5.3, Copenhagen: The Nordic Cochrane Centre, The Cochrane Collaboration, 2014) was used. The confidence level in the summary data was examined using the Grading of Recommendations Assessment, Development, and Evaluation for Studies of Interventions and Diagnostic Test Accuracy.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eStudy selection\u003c/h2\u003e \u003cp\u003eThe literature search initially revealed 402 articles (Fig.\u0026nbsp;1). Of these, 337 were excluded because they were not case-control studies, did not focus on the target disease or treatment, represented basic research, were duplicates, or were written in languages other than English. After the full-text assessment of the remaining 65 articles, one additional article was identified through reference screening. Twenty-four studies met the eligibility criteria [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] [\u003cspan additionalcitationids=\"CR15 CR16 CR17 CR18 CR19 CR20 CR21 CR22 CR23 CR24 CR25 CR26 CR27 CR28 CR29 CR30 CR31 CR32 CR33 CR34 CR35\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], comprising 2 and 22 prospective and retrospective studies, respectively. The data included outcomes for RT (n\u0026thinsp;=\u0026thinsp;4,167), NFT (n\u0026thinsp;=\u0026thinsp;2,057), CCRT (n\u0026thinsp;=\u0026thinsp;2,118), and CT (n\u0026thinsp;=\u0026thinsp;932) in 24, 15, 11, and 7 studies, respectively, among patients with intermediate-risk early-stage cervical cancer (Fig.\u0026nbsp;1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eRisk of bias of included studies\u003c/h2\u003e \u003cp\u003eExcept for two prospective randomized controlled trials (RCTs), the included studies exhibited a moderate-to-serious risk of bias (Supplementary Table\u0026nbsp;1). Publication bias was evaluated using funnel plots (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). As expected for cohort studies, several articles [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] did not provide sufficient information regarding the assessment of confounding factors or baseline differences between the compared groups.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eStudy characteristics\u003c/h2\u003e \u003cp\u003eThe characteristics of the included studies are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Most of the studies were published in 2010 or later (84.0%) and were Asian reports (68.0%). A total of 9,274 patients were analyzed, including 4,167 (44.9%) who received RT, 2,057 (22.2%) who did not receive adjuvant therapy, 2,118 (22.8%) who had CCRT, and 932 (10.0%) who underwent CT. Across all studies, the proportion of patients with \u0026ge;\u0026thinsp;2 intermediate-risk factors had a median of 84.2% (interquartile range [IQR], 43.7\u0026ndash;100). The prevalence of individual risk factors had a median of 28.6% (IQR, 20.3\u0026ndash;32.0) for non-squamous cell carcinoma histology, 59.1% (43.6\u0026ndash;71.5) for LVSI, 78.3% (61.3\u0026ndash;83.0) for deep stromal invasion, and 38.0% (22.9\u0026ndash;58.0) for tumor size\u0026thinsp;\u0026ge;\u0026thinsp;4 cm. The proportions of patients with \u0026ge;\u0026thinsp;2 risk factors were similar among treatment comparisons: 76.0% (IQR, 43.5\u0026ndash;100) for RT vs. NFT, 100% (57.2\u0026ndash;100) for RT vs. CCRT, and 44.3% (0.0\u0026ndash;92.3) for RT vs. CT (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.21). In addition, the follow-up duration was comparable between RT and the other treatment groups, including NFT, CCRT, and CT (median 56.4 vs. 50.9 months, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.78).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of the studies\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"10\" nameend=\"c13\" namest=\"c4\"\u003e \u003cp\u003eStudy population\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAuthor, year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStudy type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCountry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003cp\u003eRT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003cp\u003eOther Tx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRisk factor\u0026thinsp;\u0026ge;\u0026thinsp;2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNon-SCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLVSI\u003c/p\u003e \u003cp\u003ePresent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eDeep\u003c/p\u003e \u003cp\u003eSI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eSize\u003c/p\u003e \u003cp\u003e\u0026ge;\u0026thinsp;4cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003eFollow-up(m)\u003c/p\u003e \u003cp\u003eRT Other Tx\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRadiotherapy vs No Further Treatment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNFT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGOG92. 1999 / 2006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100%**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e21.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e70.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e75.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e26.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e60.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e60.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJiaxin F et al. 2025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e80.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e13.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e55.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMatsuo K et al. 2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJapan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e481\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e92.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e39.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e73.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e60.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e81.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e67.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e67.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTuscharoenporn T et al. 2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThailand\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100%**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e28.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e90.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e84.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ena\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e76.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e95.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCibula D et al. 2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInternational\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e418\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e692\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e76.0%\u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e29.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e76.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ena\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e42.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e56.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e51.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTurkmen O et al. 2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTurkey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e60.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e57.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e82.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e33.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e48.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e48.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZhang J et al. 2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e976\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e37.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e34.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e49.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e48.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNasioudis D et al. 2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e378\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100%**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e31.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e65.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ena\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e50.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e45.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e44.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCao L et al. 2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e861\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100%**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e46.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e48.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e75.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e64.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e62.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNie J et al. 2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e44.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e52.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e75.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e22.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e62.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e62.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKim SI et al. 2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKorea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100%**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e60.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e78.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e71.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e40.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e40.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAkilli H et al. 2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTurkey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100%**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e17.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e73.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e86.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e33.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e54.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e51.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNakamura K et al. 2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJapan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e33.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e32.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e42.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e61.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e90.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e78.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRyu SY et al. 2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKorea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e40.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e24.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e80.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ena\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e44.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e44.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAyhan A et al. 2004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTurkey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e52.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ena\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e71.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e73.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e31.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e31.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRadiotherapy vs Concurrent Chemoradiotherapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCCRT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGOG0263. 2025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKorea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e72.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e81.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ena\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e76.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e76.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAgust\u0026iacute; N et al. 2025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e434\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e434\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e868\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100%**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e40.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e69.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ena\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e57.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e64.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e66.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMatsuo K et al. 2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJapan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e92.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e39.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e73.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e60.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e81.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e67.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e67.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZhang J et al. 2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e43.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e28.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e17.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e68.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e63.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e49.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e49.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCao L et al. 2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e493\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e861\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100%**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e46.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e48.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e75.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e64.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e62.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePark W et al. 2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKorea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e70.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e26.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e46.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e88.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e50.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e70.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e70.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMahmoud O et al. 2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100%**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e37.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e32.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ena\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e58.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e48.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e48.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNakamura K et al. 2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJapan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e33.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e32.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e42.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e61.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e90.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e98.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSong S et al. 2012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKorea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e21.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e63.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e93.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ena\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e75.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e48.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRyu SY et al. 2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKorea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e40.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e24.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e80.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ena\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e44.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e44.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKim K et al. 2009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKorea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ena\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e29.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e49.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e91.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e38.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e54.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e48.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRadiotherapy vs Chemotherapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJiaxin F et al. 2025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e80.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e13.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e55.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMatsuo K et al. 2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJapan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e92.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e39.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e73.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e60.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e81.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e67.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e67.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTaguchi A et al. 2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJapan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e62%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e32.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e62.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e57.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e25.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e63.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e63.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZhang J et al. 2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e976\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e37.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e34.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e49.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e49.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNie J et al. 2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e44.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e52.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e75.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e22.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e62.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e62.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLi L et al. 2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ena\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e24.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ena\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e36.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e30.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLee KB et al. 2008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetro.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKorea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e48.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e78.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ena\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e56.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e40.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003e* Risk factors were defined by the Sedlis criteria; non-SCC was reported but not counted.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003e** The number of risk factors was not specified, though definitions followed the Sedlis criteria.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003eAbbreviations: No., number; RT, radiotherapy; Tx, treatment; SCC. Squamous cell carcinoma; LVSI, lymph vascular invasion; SI, stromal invasion; na, not applicable; (m), month; Retro., retrospective study, AND RCT; randomized controlled trial.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eSynthesis of results\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eI. Survival, recurrence, and toxicity outcomes: RT versus NFT\u003c/em\u003e \u003c/p\u003e \u003cp\u003eOur study conducted a meta-analysis of the data from one RCT and 14 retrospective studies between the RT and NFT groups (n\u0026thinsp;=\u0026thinsp;4,334) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Adjuvant RT was associated with a significantly improved recurrence-free survival compared with that under NFT (HR 0.61, 95%CI 0.44\u0026ndash;0.86; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005). Although the overall survival also tended to favor the RT group, the difference was not statistically significant (HR 0.77, 95%CI 0.56\u0026ndash;1.04; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.09) (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Furthermore, among patients with a single risk factor, adjuvant RT significantly reduced recurrence compared with that under NFT (recurrence-free survival: HR 0.55, 95%CI 0.31\u0026ndash;0.97; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04). Recurrence patterns were evaluated based on reported events owing to limited time-dependent data. Local recurrence was less frequent in the RT group than in the NFT group (8.3% vs. 12.2%; RR 0.75, 95%CI 0.56\u0026ndash;0.99; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04), whereas distant recurrence rates were comparable between the groups (6.3% vs. 4.8%; RR 1.04, 95%CI 0.47\u0026ndash;2.30; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.93). Grade\u0026thinsp;\u0026ge;\u0026thinsp;3 adverse events associated with adjuvant treatment were reported in five studies. The incidence of severe adverse events was significantly higher in the RT group than in the NFT group (6.5% vs. 1.9%; RR 5.17, 95%CI 2.70\u0026ndash;9.90; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The most common severe adverse events were genitourinary (6.3%), gastrointestinal (3.2%), and hematologic (1.6%) toxicities.\u003c/p\u003e \u003cp\u003e \u003cem\u003eII. Survival, recurrence, and toxicity outcomes: RT versus CCRT\u003c/em\u003e \u003c/p\u003e \u003cp\u003eFor the RT and CCRT groups (n\u0026thinsp;=\u0026thinsp;4,256), our study conducted a meta-analysis of the data from one RCT and 10 retrospective studies (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Recurrence-free survival showed no significant differences between the RT and CCRT groups (HR 1.26, 95%CI 0.92\u0026ndash;1.73; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.16). In addition, overall survival did not differ significantly between the groups (HR 1.07, 95%CI 0.84\u0026ndash;1.37; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.58). Recurrence patterns were evaluated based on reported events in five studies owing to insufficient time-dependent data. Local recurrence rates were comparable between the RT and CCRT groups (5.4% vs. 2.7%; RR 2.13, 95%CI 0.89\u0026ndash;5.07, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.09). In contrast, distant recurrence tended to occur more frequently in the RT group than in the CCRT group (9.5% vs. 6.2%; RR 1.48, 95%CI 1.04\u0026ndash;2.10, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03). Grade\u0026thinsp;\u0026ge;\u0026thinsp;3 adverse events related to adjuvant treatment were reported in five studies. The incidence of severe adverse events was significantly lower in the RT group than in the CCRT group (11.1% vs. 38.7%; RR 0.28, 95%CI 0.17\u0026ndash;0.44, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The most common severe adverse events were hematologic toxicities (RT vs. CCRT: 6.0% vs. 33.6%), followed by gastrointestinal (3.9% vs. 7.4%) and genitourinary (2.0% vs. 3.0%) toxicities.\u003c/p\u003e \u003cp\u003e \u003cem\u003eIII. Survival, recurrence, and toxicity outcomes: RT versus CT\u003c/em\u003e \u003c/p\u003e \u003cp\u003eMoreover, our study compared the outcomes between RT and CT groups (n\u0026thinsp;=\u0026thinsp;1,981). The meta-analysis of data from seven retrospective studies is illustrated in Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Recurrence-free survival exhibited no significant differences between the RT and CT groups (HR 0.86, 95%CI 0.51\u0026ndash;1.46, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.59). In addition, overall survival showed no significant differences between the two groups (HR 1.16, 95%CI 0.76\u0026ndash;1.78, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.48). Recurrence patterns were evaluated based on the reported events in only two studies. Local and distant recurrence rates were comparable between the RT and CT groups (Local: 0.9% vs. 3.8%; RR 0.49, 95%CI 0.02\u0026ndash;13.13, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.67; Distant: 2.7% vs. 3.8%; RR 0.69, 95%CI 0.16\u0026ndash;2.98, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.62). Only one study reported events related to adjuvant treatment. The most common severe adverse event was hematological toxicity in the CT group (RT vs. CT: 27.9% vs. 53.8%), whereas gastrointestinal (4.4% vs. 0%) and genitourinary (5.9% vs. 0%) toxicities were more frequent in the RT group.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eSummary of Main Results\u003c/h2\u003e \u003cp\u003eThis systematic review and meta-analysis evaluated adjuvant treatment strategies for patients with intermediate-risk, early-stage cervical cancer following radical hysterectomy and pelvic lymphadenectomy. The results indicate that postoperative RT significantly reduces recurrence compared with NFT, whereas CCRT does not provide additional benefit over RT alone. Notably, RT was associated with reduced recurrence even among patients with a single intermediate-risk factor, underscoring its role as a fundamental adjuvant modality in this setting. Systemic CT demonstrated recurrence outcomes comparable to RT, suggesting a potential alternative approach in selected patients. However, the lack of a clear overall survival benefit across treatment strategies highlights the importance of balancing oncologic efficacy against treatment-related morbidity when selecting adjuvant therapy.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eResults in the Context of Published Literature\u003c/h2\u003e \u003cp\u003eA major challenge highlighted in our review is the inconsistent definition of the intermediate-risk category across geographical regions and guideline frameworks [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Although the Sedlis criteria remain acceptable [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], several contemporary models incorporate different thresholds for tumor size, various grading systems for LVSI, and different methodologies in defining deep stromal invasion. These discrepancies hinder direct comparisons across studies and may contribute to conflicting results regarding the effectiveness of treatment intensification. Therefore, the standardization of definitions, ideally supported by prospective validation, is crucial to optimizing the generalizability of future evidence.\u003c/p\u003e \u003cp\u003eAnother key finding was that intermediate-risk features did not confer uniform biological or prognostic significance [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Factors such as extensive LVSI and deeply invasive adenocarcinoma were associated with a markedly higher risk of recurrence than tumor size alone [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], indicating substantial heterogeneity within the intermediate-risk category. This suggests that the current classification may be overly broad and that refined risk assessment incorporating quantitative deep stromal invasion and structured LVSI scoring may improve patient selection for systemic therapy [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Furthermore, given that histopathological subtype influences postoperative treatment responsiveness [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], histology-based subgroup analyses should be incorporated into future studies to facilitate more tailored therapeutic strategies.\u003c/p\u003e \u003cp\u003eThe evolving landscape of radiation delivery complicates the interpretation of historical data, as many landmark trials predated the widespread use of intensity-modulated radiotherapy (IMRT), which reduces toxicity without compromising local control [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]]. Accordingly, the efficacy of adjuvant radiotherapy should be interpreted in the context of modern radiotherapy practice. Notably, the NRG Oncology/GOG-263 trial conducted in the IMRT era did not demonstrate survival benefit from the addition of cisplatin-based chemotherapy, suggesting that the incremental value of postoperative CCRT may be limited, particularly in intermediate-risk populations.\u003c/p\u003e \u003cp\u003eSystemic treatment options for cervical cancer are rapidly evolving [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Particularly, immune checkpoint inhibitors have transformed the management of recurrent and metastatic disease, and ongoing trials are exploring their use in earlier treatment settings [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. In the present study, adjuvant CT for early-stage, intermediate-risk cervical cancer resulted in survival outcomes comparable to postoperative RT, suggesting its feasibility as a postoperative option. This finding may be especially relevant in Japan, where a higher prevalence of underweight young women may increase susceptibility to radiation-related toxicity [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. The ongoing RCT (JGOG1082) is evaluating adjuvant CT as an alternative to RT in high-risk early-stage cervical cancer, with potential implications for intermediate-risk disease.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Weaknesses\u003c/h2\u003e \u003cp\u003eThe primary strength of this study lies in its consideration of an HR-based meta-analysis rather than a simple pooled analysis of survival data derived from event counts and total sample sizes, as previously reported. To synthesize survival data, the HRs and their 95% CIs reported in each study were extracted and pooled after logarithmic transformation. This approach enabled us to apply an appropriate strategy to synthesize time-to-event outcomes. However, this study has some limitations. First, although this meta-analysis included 24 studies, only two were RCTs, which may limit the methodological rigor and introduce potential bias (Supplemental Table S1). Moreover, despite the widespread use of the Sedlis criteria, specific risk factors varied across studies, which may have affected the results. Second, the limited number of eligible studies precluded stratified analyses according to histological subtype. Third, although all patients underwent radical hysterectomy with lymph node assessment, the extent of surgical radicality could not be consistently determined, and details regarding radiotherapy techniques\u0026mdash;including the use of contemporary toxicity-sparing approaches such as intensity-modulated radiotherapy (IMRT)\u0026mdash;as well as chemotherapy regimens were insufficiently reported to allow stratified analyses. These methodological and reporting limitations may have influenced the study results. The available evidence is limited by the retrospective design and methodological heterogeneity of most included studies. Ongoing prospective trials, including the CERVANTES study [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], are expected to clarify whether adjuvant therapy is necessary after high-quality radical hysterectomy with adequate nodal assessment.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis systematic review and meta-analysis indicate that adjuvant RT is preferable to NFT for patients with intermediate-risk, early-stage cervical cancer. CCRT did not demonstrate clear superiority over RT alone, while systemic CT may represent a potential alternative, although its role remains uncertain. These findings support postoperative RT as the current cornerstone of adjuvant management, and routine de-escalation to observation alone should be avoided in the absence of clearly favorable biological features.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eIRB:\u0026nbsp;\u003c/strong\u003eNo ethical approval was required for this systematic review with meta-analysis, as all data had already been published in peer-reviewed journals. No patients were involved in the design, conduct, or interpretation of our study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePROSPERO:\u0026nbsp;\u003c/strong\u003eRegistration number: 1186079\u0026nbsp;\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eregistration date: 7 November 2025\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest:\u0026nbsp;\u003c/strong\u003eTokai University Research Organization (H.M). All other authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Sources\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u0026nbsp;\u003c/strong\u003eStudy concept and design: A.Y., H.M., K.M\u003cstrong\u003e;\u0026nbsp;\u003c/strong\u003eMethodology: A.Y., H.M., S.S.\u003cstrong\u003e;\u0026nbsp;\u003c/strong\u003eInvestigation: A.Y., H.M.\u003cstrong\u003e;\u0026nbsp;\u003c/strong\u003eSupervision: All the authors\u003cstrong\u003e;\u0026nbsp;\u003c/strong\u003eWriting \u0026ndash; original draft: A.Y., H.M.; Writing \u0026ndash; review and editing: All the authors discussed the results and commented on the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e This project was assisted by an Expert Panel of the Japan Society of Gynecologic Oncology via the Medical Information Network Distribution Service, which received financial support from the Ministry of Health, Labor and Welfare of Japan as a consignment project.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of generative AI and AI-assisted technologies in the manuscript:\u0026nbsp;\u003c/strong\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data, code and other materials\u003c/strong\u003e: In accordance with the journal\u0026rsquo;s guidelines, we will provide our data for independent analysis by a selected team by the Editorial Team for the purposes of additional data analysis or for the reproducibility of this study in other centers if such is requested.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A et al (2021) Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. 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Am J otology 21:341\u0026ndash;344\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCibula D, Raspollini MR, Planchamp F, Centeno C, Chargari C, Felix A et al (2023) ESGO/ESTRO/ESP Guidelines for the management of patients with cervical cancer - Update 2023. Int J Gynecol cancer: official J Int Gynecol Cancer Soc 33:649\u0026ndash;666\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSedlis A, Bundy BN, Rotman MZ, Lentz SS, Muderspach LI, Zaino RJ (1999) A randomized trial of pelvic radiation therapy versus no further therapy in selected patients with stage IB carcinoma of the cervix after radical hysterectomy and pelvic lymphadenectomy: A Gynecologic Oncology Group Study. 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Int J Gynecol cancer: official J Int Gynecol Cancer Soc 14:286\u0026ndash;292\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim K, Kang SB, Chung HH, Kim JW, Park NH, Song YS (2009) Comparison of chemoradiation with radiation as postoperative adjuvant therapy in cervical cancer patients with intermediate-risk factors. Eur J Surg oncology: J Eur Soc Surg Oncol Br Association Surg Oncol 35:192\u0026ndash;196\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee KB, Lee JM, Ki KD, Lee SK, Park CY, Ha SY (2008) Comparison of adjuvant chemotherapy and radiation in patients with intermediate risk factors after radical surgery in FIGO stage IB-IIA cervical cancer. Int J Gynecol cancer: official J Int Gynecol Cancer Soc 18:1027\u0026ndash;1031\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRyu SY, Park SI, Nam BH, Cho CK, Kim K, Kim BJ et al (2011) Is adjuvant chemoradiotherapy overtreatment in cervical cancer patients with intermediate risk factors? Int J Radiat Oncol Biol Phys 79:794\u0026ndash;799\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSong S, Song C, Kim HJ, Wu HG, Kim JH, Park NH et al (2012) 20 year experience of postoperative radiotherapy in IB-IIA cervical cancer patients with intermediate risk factors: impact of treatment period and concurrent chemotherapy. Gynecol Oncol 124:63\u0026ndash;67\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi L, Song X, Liu R, Li N, Zhang Y, Cheng Y et al (2016) Chemotherapy versus radiotherapy for FIGO stages IB1 and IIA1 cervical carcinoma patients with postoperative isolated deep stromal invasion: a retrospective study. BMC Cancer 16:403\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNakamura K, Kitahara Y, Satoh T, Takei Y, Takano M, Nagao S et al (2016) Analysis of the effect of adjuvant radiotherapy on outcomes and complications after radical hysterectomy in FIGO stage IB1 cervical cancer patients with intermediate risk factors (GOTIC Study). World J Surg Oncol 14:173\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMahmoud O, Hathout L, Shaaban SG, Elshaikh MA, Beriwal S, Small W (2016) Jr. Can chemotherapy boost the survival benefit of adjuvant radiotherapy in early stage cervical cancer with intermediate risk factors? A population based study. Gynecol Oncol 143:539\u0026ndash;544\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim H, Park W, Kim YS, Kim YJ (2020) Chemoradiotherapy is not superior to radiotherapy alone after radical surgery for cervical cancer patients with intermediate-risk factor. J gynecologic Oncol 31:e35\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAkilli H, Tohma YA, Bulut AN, Karakas LA, Haberal AN, Kuscu UE et al (2020) Comparison of no adjuvant treatment and radiotherapy in early-stage cervical carcinoma with intermediate risk factors. Int J Gynaecol Obstet 149:298\u0026ndash;302\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim SI, Kim TH, Lee M, Kim HS, Chung HH, Lee TS et al (2020) Impact of Adjuvant Radiotherapy on Survival Outcomes in Intermediate-Risk, Early-Stage Cervical Cancer: Analyses Regarding Surgical Approach of Radical Hysterectomy. J Clin Med. ;9\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCao L, Wen H, Feng Z, Han X, Zhu J, Wu X (2021) Role of adjuvant therapy after radical hysterectomy in intermediate-risk, early-stage cervical cancer. Int J Gynecol cancer: official J Int Gynecol Cancer Soc 31:52\u0026ndash;58\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNasioudis D, Latif NA, Giuntoli Ii RL, Haggerty AF, Cory L, Kim SH et al (2021) Role of adjuvant radiation therapy after radical hysterectomy in patients with stage IB cervical carcinoma and intermediate risk factors. Int J Gynecol cancer: official J Int Gynecol Cancer Soc 31:829\u0026ndash;834\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNie J, Wu Q, Yan A, Wu Z (2021) Impact of different therapies on the survival of patients with stage I-IIA cervical cancer with intermediate risk factors. Annals translational Med 9:142\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang J, Jiang P, Tu Y, Jiang S, Huang Y, Li N et al (2022) Significance of the Number of Intermediate-Risk Factors in Cervical Cancer Patients Treated with Radical Hysterectomy: A Retrospective Study of 976 Patients. J Invest surgery: official J Acad Surg Res 35:1098\u0026ndash;1105\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTurkmen O, Kilic F, Tokalioglu AA, Cakir C, Yuksel D, Kilic C et al (2022) The effect of adjuvant radiotherapy on oncological outcomes in patients with early-stage cervical carcinoma with only intermediate-risk factors: a propensity score matching analysis. J Obstet gynaecology: J Inst Obstet Gynecol 42:3204\u0026ndash;3211\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaguchi A, Kato K, Hara K, Furusawa A, Nakajima Y, Ishizawa C et al (2023) Heterogeneous treatment effects of adjuvant therapy for patients with cervical cancer in the intermediate-risk group. Cancer Med 12:18557\u0026ndash;18567\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCibula D, Akilli H, Jarkovsky J, van Lonkhuijzen L, Scambia G, Meydanli MM et al (2023) Role of adjuvant therapy in intermediate-risk cervical cancer patients - Subanalyses of the SCCAN study. Gynecol Oncol 170:195\u0026ndash;202\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTuscharoenporn T, Muangmool T, Charoenkwan K (2023) Adjuvant pelvic radiation versus observation in intermediate-risk early-stage cervical cancer patients following primary radical surgery: a propensity score-adjusted analysis. J gynecologic Oncol 34:e42\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMatsuo K, Shimada M, Matsuzaki S, Machida H, Shigeta S, Yoshida H et al (2024) Assessment of postoperative therapy de-escalation for early-stage, intermediate-risk cervical cancer. Int J Gynecol cancer: official J Int Gynecol Cancer Soc 34:1349\u0026ndash;1358\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAgust\u0026iacute; N, Viveros-Carre\u0026ntilde;o D, Wu CF, Wilke RN, Kanbergs A, Barajas K et al (2025) Adjuvant Chemoradiotherapy vs Radiotherapy Alone for Patients With Intermediate-Risk Cervical Cancer. JAMA Oncol 11:511\u0026ndash;518\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFu J, Liang C, Sun L, Zhao H, Cui Z, Lang J et al (2025) Postoperative adjuvant therapy for stage IA-IIA cervical adenocarcinoma (FIGO 2018) with one intermediate-risk factor: a multicentre retrospective cohort study of 63,926 cases. World J Surg Oncol 23:87\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRyu SY, Kim MH, Nam BH, Lee TS, Song ES, Park CY et al (2014) Intermediate-risk grouping of cervical cancer patients treated with radical hysterectomy: a Korean Gynecologic Oncology Group study. Br J Cancer 110:278\u0026ndash;285\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Y, Zhang S, Lan Z, Doan V, Kim B, Liu S et al (2022) SOX2 is essential for astrocyte maturation and its deletion leads to hyperactive behavior in mice. Cell Rep 41:111842\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee SW, Kim A, Lee SJ, Kim SH, Lee JH (2024) Intensity-Modulated Radiation Therapy for Uterine Cervical Cancer to Reduce Toxicity and Enhance Efficacy - an Option or a Must? A Narrative Review. Cancer Res Treat 56:1\u0026ndash;17\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLevinson K, Beavis AL, Purdy C, Rositch AF, Viswanathan A, Wolfson AH et al (2021) Beyond Sedlis-A novel histology-specific nomogram for predicting cervical cancer recurrence risk: An NRG/GOG ancillary analysis. Gynecol Oncol 162:532\u0026ndash;538\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChung HC, Ros W, Delord JP, Perets R, Italiano A, Shapira-Frommer R et al (2019) Efficacy and Safety of Pembrolizumab in Previously Treated Advanced Cervical Cancer: Results From the Phase II KEYNOTE-158 Study. J Clin oncology: official J Am Soc Clin Oncol 37:1470\u0026ndash;1478\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTakeuchi M, Honda M, Tsuboi A, Minato-Inokawa S, Kurata M, Wu B et al (2022) Weight Trajectory Since Birth, Current Body Composition, Dietary Intake, and Glucose Tolerance in Young Underweight Japanese Women, vol 3. Women's health reports, New Rochelle, NY, pp 215\u0026ndash;221\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee J, Chang CL, Lin JB, Wu MH, Sun FJ, Wu CJ et al (2018) The Effect of Body Mass Index and Weight Change on Late Gastrointestinal Toxicity in Locally Advanced Cervical Cancer Treated With Intensity-modulated Radiotherapy. Int J Gynecol cancer: official J Int Gynecol Cancer Soc 28:1377\u0026ndash;1386\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCibula D, Borčinov\u0026aacute; M, Kocian R, Feltl D, Argalacsova S, Dvorak P et al (2022) CERVANTES: an international randomized trial of radical surgery followed by adjuvant (chemo) radiation versus no further treatment in patients with early-stage, intermediate-risk cervical cancer (CEEGOG-CX-05; ENGOT-CX16). Int J Gynecol cancer: official J Int Gynecol Cancer Soc 32:1327\u0026ndash;1331\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-clinical-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijco","sideBox":"Learn more about [International Journal of Clinical Oncology](http://link.springer.com/journal/10147)","snPcode":"10147","submissionUrl":"https://www.editorialmanager.com/ijco/default2.aspx","title":"International Journal of Clinical Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"cervical cancer, systematic review, intermediate-risk, survival, complications","lastPublishedDoi":"10.21203/rs.3.rs-8559901/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8559901/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo evaluate the efficacy and safety of adjuvant treatment strategies following radical hysterectomy for intermediate-risk, early-stage cervical cancer using a reconstructed HR meta-analysis.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e A systematic review and meta-analysis was conducted by the Japan Society of Gynecologic Oncology Cervical Cancer Committee. PubMed/MEDLINE, Cochrane, and Ichushi were searched on July 29, 2025, using \u0026ldquo;cervical cancer,\u0026rdquo; \u0026ldquo;intermediate risk,\u0026rdquo; and \u0026ldquo;adjuvant therapy.\u0026rdquo; Studies comparing adjuvant radiotherapy alone (RT) with no further treatment (NFT), concurrent chemoradiotherapy (CCRT), or systemic chemotherapy (CT) after conventional radical hysterectomy were independently reviewed by two reviewers. Primary outcomes were survival and grade\u0026thinsp;\u0026ge;\u0026thinsp;3 treatment-related toxicities.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf 402 screened articles, 24 studies comprising 9,278 patients were included: RT (n\u0026thinsp;=\u0026thinsp;4,167), NFT (n\u0026thinsp;=\u0026thinsp;2,057), CCRT (n\u0026thinsp;=\u0026thinsp;2,118), and CT (n\u0026thinsp;=\u0026thinsp;936). The majority of studies enrolled patients with \u0026ge;\u0026thinsp;2 Sedlis risk factors (median 84.2%, interquartile range 44.7\u0026ndash;100%). Compared with NFT, RT significantly improved recurrence-free survival (HR 0.61, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) but did not confer a significant overall survival benefit (HR 0.77, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.09). RT also reduced recurrence in patients with a single risk factor (HR 0.55, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). RT showed no survival disadvantage compared with CCRT (recurrence-free survival: HR 1.26; overall survival: HR 1.07), and survival outcomes were comparable between RT and CT (recurrence-free survival: HR 0.86; overall survival: HR 1.16), (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Grade\u0026thinsp;\u0026ge;\u0026thinsp;3 toxicities were significantly lower with RT than with CCRT (odds ratio 0.25; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eAdjuvant RT represents an effective and well-tolerated postoperative strategy for intermediate-risk, early-stage cervical cancer. Adjuvant CT may represent a potential alternative option.\u003c/p\u003e","manuscriptTitle":"Optimal Adjuvant Strategy in Intermediate-Risk Cervical Cancer: A Systematic Review and Meta-Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-22 14:51:52","doi":"10.21203/rs.3.rs-8559901/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor revisions","date":"2026-03-09T06:53:45+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2026-01-21T10:34:22+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-21T00:05:06+00:00","index":"","fulltext":""},{"type":"submitted","content":"International Journal of Clinical Oncology","date":"2026-01-20T03:33:25+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-13T13:54:33+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-clinical-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijco","sideBox":"Learn more about [International Journal of Clinical Oncology](http://link.springer.com/journal/10147)","snPcode":"10147","submissionUrl":"https://www.editorialmanager.com/ijco/default2.aspx","title":"International Journal of Clinical Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"de6a8a48-0c1a-47fa-aeab-9d3bf73cd0b3","owner":[],"postedDate":"January 22nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-04-27T16:15:39+00:00","versionOfRecord":{"articleIdentity":"rs-8559901","link":"https://doi.org/10.1007/s10147-026-03028-9","journal":{"identity":"international-journal-of-clinical-oncology","isVorOnly":false,"title":"International Journal of Clinical Oncology"},"publishedOn":"2026-04-21 15:57:33","publishedOnDateReadable":"April 21st, 2026"},"versionCreatedAt":"2026-01-22 14:51:52","video":"","vorDoi":"10.1007/s10147-026-03028-9","vorDoiUrl":"https://doi.org/10.1007/s10147-026-03028-9","workflowStages":[]},"version":"v1","identity":"rs-8559901","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8559901","identity":"rs-8559901","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}