Prognostic factors of locally advanced cervical cancer after concurrent chemoradiotherapy

Prognostic factors of locally advanced cervical cancer after concurrent chemoradiotherapy | 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 Prognostic factors of locally advanced cervical cancer after concurrent chemoradiotherapy Xiuying Li, Zejia Mao, Qiaoling Li, Misi He, Mingfang Guo, Hao He, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5678120/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Oct, 2025 Read the published version in BMC Cancer → Version 1 posted 8 You are reading this latest preprint version Abstract Objective To investigate the prognostic value of magnetic resonance imaging (MRI) and clinical features in locally advanced cervical cancer (LACC) after concurrent chemoradiotherapy (CCRT). Method This study recruited 189 patients with LACC who received definitive CCRT between May 2018 and December 2020 and underwent MRI, including diffusion-weighted imaging, before and 1 month after initial therapy. The tumor size and mean apparent diffusion coefficient (ADC mean ) values were evaluated. A Cox proportional hazards model was used to determine the association of clinical characteristics and imaging factors with progression-free survival (PFS) and overall survival (OS) based on univariate and multivariate analysis. Result The median follow-up time was 58 (range: 11–71) months. The 5-year PFS and OS rates were 73.8% and 85.5%, respectively. Univariate analysis revealed that serum squamous cell carcinoma (SCC) antigen level, stage, Pre-treatment tumor size, residual disease (RD) and post-treament ADC mean values were significant predictors of PFS and OS. Positive pelvic lymph node and adjuvant chemotherapy after CCRT were adverse predictors of PFS and OS, respectively. Multivariate analysis revealed that stage, SCC antigen level, and RD were independent predictors of PFS (hazard ratio [HR] = 3.282, P < 0.001; HR = 2.567, P = 0.002; and HR = 1.621, P < 0.001, respectively) and OS (HR = 2.517, P = 0.043; HR = 1.025, P = 0.015; and HR = 1.712, P = 0.008, respectively). Based on the threshold, RD size ≥ 1.1 cm resulted in a considerably worse PFS and OS. Conclusion Elevated SCC antigen level, advanced stage, and RD size ≥ 1.1 cm were linked to worse PFS and OS. Furthermore, the ADC mean values was not a reliable predictor of survival outcomes. Locally advanced cervical cancer Concurrent chemoradiotherapy Residual disease Magnetic resonance imaging Diffusion-weighted imaging Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Cervical cancer is the fourth most common malignancy in women worldwide [ 1 ] . Its incidence and mortality rates in China have dramatically increased owing to successful screening programs [ 2 ] . More than fifty percent of new patients are diagnosed with locally advanced cervical cancer (LACC) (International Federation of Gynecology and Obstetrics,2018 [International Federation of Gynecology and Obstetrics,FIGO 2018] stages 1B2 to 4A) [ 3 ] . Based on five important randomized controlled trials [ 4 – 8 ] , which revealed that adding chemotherapy to radiotherapy increases survival rates, external beam radiotherapy (EBRT) and concurrent chemotherapy, followed by brachytherapy (BT), have been the mainstay treatment for LACC. Unfortunately, recurrences occur frequently primarily within the first 2 years of follow-up. The prognosis of LACC remains dismal. Previous studies [ 9 , 10 ] have revealed that approximately 35% of patients with LACC demonstrated disease progression after concurrent chemoradiotherapy (CCRT), with a 5-year disease-free survival rate of 58%. The tumor stage, histology, tumor volume, lymph node involvement and residual diease (RD) were the primary early prognostic variables [ 9 , 11 ] . The apparent diffusion coefficient (ADC) values has also been reported to predict tumor treatment response, prognosis and survival of locally advanced cervical cancer after chemotherapy and radiotherapy [ 12 – 16 ] . As known, Functional magnetic resonance imaging (MRI) plays a critical role in many aspects of radiotherapy management, including tumor staging, treatment planning and delivery, post-treatment response assessment, and long-term surveillance [ 17 ] . Diffusion-weighted imaging (DWI), a common functional imaging modality, can study the movement of water molecules in tissue to detect and characterise disease. The ADC is used to quantify DWI and can provide information regarding tumor cellularity and proliferation by reflecting the restricted motion of water molecules [ 18 ] . In general, malignant tumor tends to have lower ADC values. In recent years, the challenge of reducing recurrence and improving survival has emerged in patients with LACC. Thereby, general clinical characteristics and pre- and post-treatment MRI characteristics of the patients were collected to analyze the factors affecting the prognosis and enhance the prognosis of LACC In this study, we investigated a variety of clinical and imaging parameters to figure out which factors affected the prognosis following CCRT for LACC. It may provide some guidance for additional subsequent treatment after initial chemoradiotherapy in order to improve prognosis. Materials and methods Patients Between May 2018 and December 2020, 443 paients diagnosed with biopsy-proven locally advanced squamous cell carcinoma (SCC) of the cervix (American Joint Committee on Cancer (AJCC) stage T2b to T3b) were initially screened. The tumors were confined to the pelvic cavity without any evidence of distant metastases (including para-aortic lymph node metastases), underwent DWI-MRI, before and 1 month after treatment and none of the patients had received prior treatment. Patients who did not receive chemotherapy during radiotherapy, other modulated radiotherapy rather than EBRT. and did not complete radiotherapy were also excluded. In total, 189 patients had complete clinical records, including variables as age, stage, serum hemoglobin level, SCC antigen level, radiotherapy duration, pre-treatment tumor size, RD, pelvic lymph nodes (PLNs) status, pre-treatment ADC mean value, post-treatment ADC mean value, and change ADC mean value. The flowchart of including patients was drawn (Fig. 1 ). This retrospective study was approved by the institutional review board of our hospital (ethic number: 011). Furthermore, written informed consent was obtained from all patients. Treatments All patients were treated CCRT with a combination of EBRT and platinum-based chemotherapy at least one course, administered by weekly or tr-weekly. Intensity-modulated radiotherapy and high–dose-rate image-guided brachytherapy (HDR-BT) were included. EBRT was delivered at a dose of 45 to 50.8Gy in 25 or 28 fractions, with a daily fraction size of 1.8 or 2.0Gy. The maximum and minimum values within the target range did not exceed ± 10% of the prescribed dose, the dosage of enlarged lymph nodes reached 50 to 66Gy and involving parametrial reached 50 to 54Gy. Simultaneously, HDR-BT was performed with a source of 192 Ir. A dose of minimum dose covering 90% of high risk clinical tumor volume (D90 HR-CTV) reached 22 to 33Gy in 4 to 6 fractions.Patients with positive common iliac lymph nodes (short axis diameter ≥ 15 mm) were treated with expanded-field radiotherapy ( included the area adjacent to the aorta and inferior vena cava, with a lower border of the aortic bifurcation. And the upper boundary of the extended field was usually at T12 or the renal vessel). Imaging protocol and predictive parameter calculation Imaging protocol and predictive parameter calculation MRI was performed using a 1.5T system machine. Pelvic MRI was performed before (within 4 weeks of the initiation of treatment) and 1 month (within 6 weeks following the final BT) after treatment. Our institution started performing DWI–MRI since 2018. The protocol included enhanced DWI, T1-weighted imaging (T1WI), and T2-weighted imaging (T2WI). T2WI revealed that the cervical tumor demonstrated a significant signal intensity. Tumor size was defined as the maximum diameter of tumor dimension measured on T2WI–MRI (in cm). The positive PLNs defined as the short diameter ≥ 1.5 cm. Enhanced DWI was used, and the ADC map was automatically generated. The ADC maps were calculated using all three B values. The ADC mean value was measured in the tumor at each time point. A region of interest (ROI) was manually established on the single axial ADC map image displaying the tumor’s maximal dimension. The ROIs was drawn by an experienced radiologists specialising in gynecological oncology who was blinded to outcome. Areas of necrosis within the tumour were avoided. Follow-up After one month following chemoradiation, clinical and radiological examinations were performed every 3 months for the first 2 years, every 6 months for the next 3 years, and once yearly thereafter. Statistical analysis The study endpoints included progression-free survival PFS and OS. The duration of PFS was calculated from the date of treatment initiation to the date of any disease progression or last follow-up, whereas the duration of OS was calculated from the date of treatment initiation to the date of death or last follow-up. Data analysis was conducted using Statistical Package for the Social Sciences Statistics software (version 26.0) and R Studio (version 4.2.2). The Cox proportional hazards model was utilized to evaluate the effect of significant factors on the survival endpoints for univariate and multivariate analyses. The optimal cutoff value of SCC antigen level, RD and post-ADC mean were identified as the point at which the log-rank p -value was at a minimum (Supplementary 1a,1b,2a,2b,3a,3b). The Kaplan–Meier method was used to calculate PFS and OS, and the results were compared using the log-rank test. A P -value of < 0.05 was considered to indicate statistical significance. Statistical tests were conducted according to a two-sided significance level.In this study, missing variables were imputed using multiple imputation by chained equations (MICE) and the random forest (RF) algorithm. (Supplementary 4). Results Baseline characteristics This study included 189 patients with pathological evidence of SCC. Clinical and radiological features were summarized in Table 1 . The mean and median age at diagnosis were 53.6(± 7.6) and 53(range: 36 − 71) years, respectively. The median hemoglobin and SCC antigen level were 121.0 g/L (range: 48.0-161.0) and 4.4 mg/dl ( range: 0.6–96.0), respectively. Pre-treatment T2WI–MRI revealed mean and median maximal tumor sizes of 4.4 (± 0.5) and 4.3 (range: 1.3–8.2) cm, respectively. Thirty patients were diagnosed with positive pelvic lympha nodes. Eleven patients of them with positive common iliac lymph nodes received extended field radiotherapy. Most patients of 85% completed EBRT and HDR-BT within 8 weeks and 80.9% completed concurrent platinum-based chemotherapy (five cycles weekly or two cycles of tri-weekly cisplatin-based chemotherapy). Additionally, adjuvant chemotherapy (ACT) was administered to 41.2% of patients following CCRT. The median ADC mean values of pre- and post-treatment were 0.88 × 10 − 3 and 1.55 × 10 − 3 mm 2 /s, respectively. The median change in ADC was 0.70 × 10 − 3 mm 2 /s. Based on the AJCC stage system, 115, 2,and 74 of patients were diagnosed with stage T2b, T3a, and T3b, respectively. RD was detected in the cervix of 64 patients but not in any of the PLNs.The median RD size was 0.0 cm (range: 0.0-4.8). Table 1 Patient characteristics (N = 189) Characteristic Median (range) / N (%) Age (years; median) 53.0 (36.0–71.0) SCC antigen level (ng/ml) 4.4 (0.6–96.0) Hemoglobin (g/l) 121.0 (48.0-161.0) Pretreament tumor size (cm) 4.3 (1.30–8.2) Pretreatment ADC mean 0.88 (0.45–1.58) Post-treatment ADC mean 1.55 (0.94–2.36) Change in ADC mean 0.70 (0.00-3.04) Duration of radiotherapy (days) 47 (28–84) Residual disease size (cm) 0.0 (0.0-4.8) AJCC staging T2b T3a-3b 113(59.79) 76(40.21) Pelvic lymph node Negative Positive 159 (84.13) 30 (15.87) Chemotherapy regimen Weekly Tri-weekly 89 (47.10) 100 (52.90) Chemotherapy Complete Incomplete 153 (80.95) 36 (19.05) Adjuvant chemotherapy No Yes 111 (58.73) 78 (41.27) Extended radiotherapy No Yes 178 (94.18) 11 (5.82) Data presented as median (range) or n (%). SCC: squamous cell carcinoma; ADC mean : mean apparent diffusion coefficient; AJCC: American Joint Committee on Cancer; HR: hazard ratio; CI: confidence interval. Survival During a median follow-up period of 58 months (range, 11–71 months). 123 (65.0%) patients were revealed no residual tumor one month following CCRT. About 80% of patients had no RD in the cervix at six months following treatment, which was confirmed by MRI. 56 (29.6%) patients demonstrated disease progression at the latest follw-up time, including central recurrence (n = 21, 37.5%), local regional recurrence (n = 20, 35.7%), local regional recurrence with distant metastasis (n = 12, 21.4%), and distant metastasis only (n = 3, 5.4%). Furthermore, 23 patients died of their disease whereas 33 remained alive.The 5-year PFS and OS rates were 73.8% and 85.5%, respectively. For patients with AJCC T2b and T3a-3b, the 5-year PFS and OS rates were 87.1% and 53.7%, respectively. Univariate and multivariate analysis Tables 2 and 3 present the univariate and multivariate clinical outcome results. Univariate analysis revealed that SCC antigen level, stage, pre-treatment tumor size, RD and post-treatment ADC mean were significant predictors of PFS and OS. Positive PLN and ACT were predictors of PFS and OS, respectively. Other factors, including age, pre-treatment hemoglobin levels, duration of radiation therapy, chemotherapy regimen, pre-treatment ADC mean and the change ADC mean were not associated with PFS and OS. In multivariate analysis, SCC antigen level, stage, and were the independent predictors of PFS and OS. Table 2 Cox regression analysis of clinical and MRI variables for progression-free survival Variable Univariate Multivariate HR 95% CI P -value HR 95% CI P -value Age (years) 0.997 0.963–1.033 0.883 AJCC T stage (T3a-3b) 3.467 2.008–5.986 0.000 3.282 1.821–5.914 0.000 SCC (ng/ml) 1.025 1.013–1.037 0.000 2.567 1.380–4.778 0.002 Hemoglobin (g/L) 0.988 0.976–1.001 0.062 Duration of radiotherapy (days) 0.996 0.967–1.025 0.774 Chemotherapy regimen (Triweekly) 1.116 0.659–1.893 0.682 Chemotherapy (Incomplete) 1.243 0.656–2.354 0.505 Adjuvant chemotherapy (Yes) 1.604 0.948–2.713 0.078 Pelvic lymph node (Positive) 2.417 1.273–4.590 0.007 1.109 0.540–2.278 0.777 Extended radiotherapy (No) 1.699 0.610–4.736 0.311 Pretreatment tumor size (cm) 1.610 1.312–1.975 0.000 1.367 0.746–2.506 0.095 Residual disease 2.004 1.608–2.498 0.000 1.621 1.282–2.050 0.000 Pretreatment ADC mean 0.160 0.025–1.038 0.055 Post-treatment ADC mean 0.234 0.094–0.581 0.002 0.558 0.225–1.382 0.207 Change in ADC mean 0.709 0.404–1.244 0.231 MRI: magnetic resonance imaging; SCC: squamous cell carcinoma; ADC mean : mean apparent diffusion coefficient; AJCC: American Joint Committee on Cancer; HR: hazard ratio; CI: confidence interval. Table 3 Cox regression analysis of clinical and MRI variables for overall survival Variable Univariate Multivariate HR 95% CI P -value HR 95% CI P -value Age (years) 0.980 0.927–1.036 0.472 AJCC T stage (T3a-3b) 3.142 1.330–7.426 0.009 2.517 0.783–4.834 0.043 SCC (ng/ml) 1.033 1.018–1.049 0.000 1.025 1.005–1.045 0.015 Hemoglobin (g/L) 0.982 0.964-1.000 0.050 Duration of radiotherapy (days) 1.015 0.972–1.059 0.501 Chemotherapy regimen (Triweekly) 2.323 0.953–5.662 0.064 Chemotherapy (Incomplete) 1.888 0.776–4.593 0.161 Adjuvant chemotherapy (Yes) 2.521 1.088–5.841 0.031 2.237 0.872–5.745 0.094 Pelvic lymph node (Positive) 2.376 0.921–6.127 0.073 Extended radiotherapy (No) 3.044 0.890–10.410 0.076 Pretreatment tumor size (cm) 1.691 1.237–2.311 0.001 1.2027 0.821–1.760 0.343 Residual disease 1.877 1.380–2.580 0.000 1.712 1.149–2.578 0.008 Pretreatment ADC mean 0.962 0.076–12.242 0.976 Post-treatment ADC mean 0.217 0.051–0.918 0.038 0.719 0.158–3.269 0.669 Change in ADC mean 0.461 0.176–1.207 0.115 MRI: magnetic resonance imaging; SCC: squamous cell carcinoma; AJCC: American Joint Committee on Cancer; ADC mean : mean apparent diffusion coefficient; HR: hazard ratio; CI: confidence interval. The optimal cutoff value was identified as the point at which the log-rank p-value was at a minimum. The optimal cutoff values of post-treatment ADC mean were 1.23 × 10 − 3 and 1.33 × 10 − 3 mm 2 /s for PFS and OS, respectively. As a categorical variable analyzed in multivariate analysis again, post-treatment ADC mean was not a significant predictor of PFS and OS.The optimal cutoff value of SCC antigen level were 3.2ng/ml for PFS and 12.8ng/ml. The optimal cutoff values of RD was 1.1 cm for both PFS and OS. The Kaplan-Meier curves were plotted. The optimal cutoff values of SCC antigen level for PFS and OS were different. However, when analyzed with median value, patients with median SCC antigen level > 4.4 ng/ml demonstrated both worse PFS ( P = 0.002) (Fig. 2 a) and OS ( P = 0.015) (Fig. 2 b) compared to patients with SCC antigen level of ≤ 4.4 ng/ml. Patients with AJCC stage T3a-3b exhibited worse PFS ( P < 0.001) (Fig. 3 a) and OS ( P = 0.043) compared with those with AJCC stage T2b (Fig. 3 b). The 5-year PFS (34.7% vs. 85.9%; P < 0.001) (Fig. 4 a) and 5-year OS (65.2% vs. 91.4%; P = 0.008) (Fig. 4 b) were poorer in patients with RD ≥ 1.1 cm than in those with RD < 1.1 cm. Discussion Based on our research, SCC antigen level, pre-treatment tumor size, positive PLN, stage, ACT, RD and post-treatment ADC mean were predictors of PFS and OS. On multivariate analysis, SCC antigen level, stage and RD were significant independent factors excluding ADC mean value. As we know, the benefit of CCRT for survival may diminish as staging increases. The FIGO 2009 and 2018 schema indicated that the 5-year survival rates for stage IIB tumors were 61.3% and 63.9%, those for stage IIIA tumors were 40.5% and 40.7%, and those for stage IIIB tumors were 38.4% and 41.4%, respectively [ 19 ] . The same trend was observed in our study. The 5-year PFS and OS for patients with AJCC stage T3a-3b compared to T2b declined by 33.4% and 12.6%, respectively. The stage was illustrated as a major predictor of survival in patients with LACC after CCRT. Other variables, such as histological subtype, SCC antigen level, HGB level, ADC mean value, and RD were also reported to associate with survival [ 10 – 12 ] . The prognosis was worse for patients with adenocarcinoma (AC) or adenosquamous carcinoma (ASC) than those with SCC [ 10 , 20 ] . Patiens with only histological subtype of SCC were analyzed in our study. The PFS and OS rates of them were higher than AC and ASC histological subtype reported by other studies [ 10 , 20 ] and the SCC antigen level was a significant prognostic factor for survival outcome also discovered in this study. However, different results from other studies [ 21 , 22 ] indicated that locally progressed cervical AC/ASC exhibited comparable survival rates to SCC. Therfore, it also remains controversial whether the type of pathology influences prognosis. We can make relevant comparative studies in our future research. DWI–MRI has the ability to differentiate normal tissue from cervical carcinoma and its results are quantified in terms of ADC. The decreased ADC of malignant tumors indicate the limited mobility of water molecules. Multiple studies have demonstrated that pre-treatment ADC, post-treatment ADC, change in ADC and the 90th percentile ADC value over the chemoradiotherapy course for cervical cancer are predictors of prolonged survival, recurrence outcomes, and clinical or rapid response to treatment [ 12 – 17 ] . Our research revealed that the post-treatment ADC mean was associated with PFS and OS based on univariate analysis but not statistically significant in multivariate analysis. Valentini [ 23 ] showed the similar conclusion that ADC mean did not correlate with treatment outcome. The reason were more factors including in this study and some of them may existed interaction,and data imputation affecting the results. The presence of RD has been reported as a important prognostic factor for survival. which was determined via MRI in clinical practice. MRI was considered a crucial tool for evaluating treatment response and positron emission tomography/computed tomography (PET/CT) was often employed [ 24 , 25 ] . The existence of a remnant tumor on MRI as an independent indicator of disease progression [ 27 , 28 ] . A similar finding was reported in this study. In addition, we revealed the optimal cutoff value of was 1.1 cm. Patients with RD size ≥ 1.1 cm demonstrated a poor PFS and OS on the survival curve. However, studies [ 28 , 29 ] revealed that MRI had limited accuracy in evaluating residual tumors. Histopathological assessment was the most effective method for determining RD after CCRT. According to Hequet [ 27 ] , the pathologically confirmed RD size larger 1 cm decreased DFS but showed no effect on OS ( P = 0.08). But MRI exhibited a false positive rate of 29.2% and a false negative rate of 11.1% for identifying RD. Federico [ 30 ] also made the conclusion that pathological RD in the cervix was statistically significantly associated with worse DFS and OS. Although RD was an important factor affecting the survival of LACC after radiotherapy, the methods applied to indentify RD and the post-radiation treatment interventions are uncertain. Salvage surgery improved the outcome in individuals with central pelvic RD who do not have metastatic disease following CCRT [ 31 – 32 ] , The 3-year and 5-year OS rates for patients with RD size ≥ 2 cm improved to 64.9% and 55.6%, respectively. However, it is related to an increased risk of complications, including fistulas, gastrointestinal or urinary tract complications, and sexual dysfunction, which can lower patients’ quality of life and affect their survival. Furthermore, ACT was often used as an additional therapy to improve survival for patients with LACC following CCRT. According to two retrospective studies from Turkey [ 33 – 34 ] , DFS and OS increased especially in patients with stage III disease. However, the results of two large prospective trials—the OUTBACK trial [ 35 ] and the ACTLACC trial [ 36 ] —indicated that ACT couldn’t improve prognosis. Compared with systemic ACT, salvage hysterectomy decreased mortality by approximately 60% in patients with persistent cervical cancer after definitive RT/CCRT in another retrospective study. In fact, ACT was commonly employed in clinical practice at our center to treat patients with advanced stage or RD after chemoradiotherapy. Our study found ACT was a predictor of OS in univariate analysis, but not significant in mulitivariate analysis. The reason maybe there was no uniform criteria to identify the patients who accept ACT after CCRT. The OUTBACK trial also didn’t randomised patients after completion of standard chemoradiation. Although patients who had salvage surgery were not included in our analysis, individuals with RD size ≥ 1.1 cm were given the option to be considered for salvage surgery. Therefore, Our center is currently conducting prospective clinical trials (NCT: 04409860 and NCT: 05749887) to evaluate the effectiveness of ACT and salvage surgery for patients with RD after CCRT for cervical cancer. The two trails aim to investigate suitable treatment options for high-risk patients with LACC following CCRT and to further explore the prognostic factors. Compared with other studies, our study only concluded the histological subtype of SCC, thus avoiding the prognostic impact of the pathological type. Moreover, this study included plenty variabes of imaging and clinical features for prognostic analysis. Additionally, we found that adjuvant therapy may be necessary for patients with advanced stage and RD size ≥ 1.1 cm following CCRT. Our study had some limitations. Neither pathological evidence nor PET/CT scans were used to help detect RD in the cervix. Pathology confirmation of locoregional RD prior to adjuvant treatment is necessary in future. Furthermore, tumor volume, tumor size reduction rate, and percentage ADC value reported by other studies that may affect prognosis were ignored in this study. More imaging parameters should be take into consideration in future investigation. Additionally, this was a retrospective study with a limited sample size. The results were unreliable and have not been validated in an independent dataset, which may limit the generalizability of our results beyond the study population. Muiltcenter prospective studies with larger sample sizes should be conducted. Conclusion This study revealed that SCC antigen level, stage, and RD were independent variables associated with OS and PFS in patients with AJCC stage Tab-T3b squamous cell cervical cancer receiving CCRT. The ADC mean value could not be a preditor of PFS and OS. Adjuvant therapy may be recommended for patients with advanced stage, higher SCC antigen level and RD size ≥ 1.1 cm in order to improve survival. Abbreviations MRI Magnetic resonance imaging LACC Locally advanced cervical cancer CCRT Concurrent chemoradiotherapy ADC mean Mean apparent diffusion coefficient PFS Progression-free survival OS Overall survival SCC Squamous cell carcinoma RD Residual disease AJCC American Joint Committee on Cancer FIGO International Federation of Gynecology and Obstetrics ADC Apparent diffusion coefficient DWI Diffusion-weighted imaging HDR High–dose-rate BT brachytherapy ERBT External beam radiotherapy PLN Pelvic lymph node ACT Adjuvant chemotherapy AJCC American Joint Committee on Cancer AC Adenocarcinoma ASC Adenosquamous carcinoma Declarations Acknowledgements The authors express sincere appreciation to all the individuals involved in the improvement of this manuscript. Special thanks are extended to experienced radiologist Lu Yang for her invaluable support in conducting radiology evaluation. Authors' contributions Conceptualization: Xiuying Li, Dongling Zou; Data collection: Zejia Mao, Qian Zheng, Yue Huang; Investigation: Zejia mao, Hao He, Ling Long, Jing Wang; Data analysis and graphing: Xiuying Li, Qiaoling Li; Supervision: Misi He, Mingfang Guo; Writing original draft: Xiuying Li; Writing review & editing: Dongling Zou. All authors contributed to the article and approved the submitted version. Funding This research was supported by Beijing Heaalth Alliance Charitable Foundation (BJHA-CRP-092), Wu Jieping Medical Foundation (320.6750.2022-22-12), Qujiang District Quzhou City Life Oasis Public Service Center (113), Talent Program of Chongqing (cstc2024rcih-bgzxm0162), Chongqing Health Commission (2023ZDXM029), The Project for Enhancing Scientific Research Capabilities of Chongqing University Cancer Hospital (2023nlts005, 2023nlts009). Availability of data and materials The data supporting the results of this study are available from the corresponding authors upon reasonable request. Ethics approval and consent to participate The study has been performed in accordance with the 1964 Helsinki Declaration and has been approved by the Institutional Review Board of Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital and the ethic number was 011. A written informed consent was obtained from all patients included in this study. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Author details First author: Xiuying Li Authors and Affiliations Department of Gynecologic Oncology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, 400030, China. Xiuying Li, Qiaoling Li1, Misi He, Mingfang Guo, Hao He, Yue Huang, Qian Zheng, Jing Wang & Dongling Zou Chongqing Specialized Medical Research Center of Ovarian Cancer, Chongqing, 400030, China. Misi He, Qian Zheng & Dongling Zou Organoid Transformational Research Center, Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment, Chongqing University Cancer Hospital, Chongqing, 400030, China. Misi He, Qian Zheng & Dongling Zou School of Medicine,Chongqing University,Chongqing University Cancer Hospital, Chongqing, 400030, China. Zejia Mao & Ling Long References Ferlay J, Colombet M, Soerjomataram I, Parkin DM, Piñeros M, Znaor A, et al. Cancer statistics for the year 2020: An overview. Int J Cancer 2021;149:778-89. Xia C, Dong X, Li H, Cao M, Sun D, He S, et al. Cancer statistics in China and United States, 2022: profiles, trends, and determinants. Chin Med J (Engl) 2022;135:584-90. Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F, et al. 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Watanabe Y, Nakamura S, Ichikawa Y, Ii N, Kawamura T, Kondo E, et al. Early alteration in apparent diffusion coefficient and tumor volume in cervical cancer treated with chemoradiotherapy or radiotherapy: Incremental prognostic value over pretreatment assessments. Radiother Oncol. 2021;155:3-9. Dong EE, Xu J, Kim JW, Bryan J, Appleton J, Hamstra DA, et al. Apparent diffusion coefficient values predict response to brachytherapy in bulky cervical cancer. Radiat Oncol. 2024;19(1):35. Published 2024 Mar 13. Hricak H, Swift PS, Campos Z, Quivey JM, Gildengorin V, Göranson H. Irradiation of the cervix uteri: value of unenhanced and contrast-enhanced MR imaging. Radiology. 1993;189:381-88. Yang W, Qiang JW, Tian HP, Chen B, Wang AJ, Zhao JG. Multi-parametric MRI in cervical cancer: early prediction of response to concurrent chemoradiotherapy in combination with clinical prognostic factors. Eur Radiol. 2018;28:437-45. Lee J, Kim YT, Kim S, Lee B, Lim MC, Kim J, et al. Prognosis of Cervical Cancer in the Era of Concurrent Chemoradiation from National Database in Korea: A Comparison between Squamous Cell Carcinoma and Adenocarcinoma. PLoS One. 2015;10:e0144887. Wright JD, Matsuo K, Huang Y, Tergas AI, Hou JY, Khoury-Collado F, et al. Prognostic Performance of the 2018 International Federation of Gynecology and Obstetrics Cervical Cancer Staging Guidelines. Obstet Gynecol. 2019;134:49-57. Katanyoo K, Sanguanrungsirikul S, Manusirivithaya S. Comparison of treatment outcomes between squamous cell carcinoma and adenocarcinoma in locally advanced cervical cancer. Gynecol Oncol. 2012;125:292–6. Rose PG, Java JJ, Whitney CW, Stehman FB, Lanciano R, Thomas GM. Locally advanced adenocarcinoma and adenosquamous carcinomas of the cervix compared to squamous cell carcinomas of the cervix in gynecologic oncology group trials of cisplatin-based chemoradiation. Gynecol Oncol. 2014;135:208–12. Valentini AL, Miccò M, Gui B, Giuliani M, Rodolfino E, Telesca AM, et al. The PRICE study: The role of conventional and diffusion-weighted magnetic resonance imaging in assessment of locally advanced cervical cancer patients administered by chemoradiation followed by radical surgery. Eur Radiol. 2018;28(6):2425-2435. Jalaguier-Coudray A, Villard-Mahjoub R, Delouche A, Delarbre B, Lambaudie E, Houvenaeghel G, et al. Value of Dynamic Contrast-enhanced and Diffusion-weighted MR Imaging in the Detection of Pathologic Complete Response in Cervical Cancer after Neoadjuvant Therapy: A Retrospective Observational Study. Radiology. 2017;284(2):432-442. Pasciuto T, Moro F, Collarino A, Gambacorta MA, Zannoni GF, Oradei M, et al. The Role of Multimodal Imaging in Pathological Response Prediction of Locally Advanced Cervical Cancer Patients Treated by Chemoradiation Therapy Followed by Radical Surgery. Cancers (Basel). 2023;15(12):3071. Park JJ, Kim CK, Park BK. Prediction of disease progression following concurrent chemoradiotherapy for uterine cervical cancer: value of post-treatment diffusion-weighted imaging. Eur Radiol. 2016;26:3272-9. Angeles MA, Baissas P, Leblanc E, Lusque A, Ferron G, Ducassou A, et al. Magnetic resonance imaging after external beam radiotherapy and concurrent chemotherapy for locally advanced cervical cancer helps to identify patients at risk of recurrence. Int J Gynecol Cancer. 2019;29(3):480-486. Hequet D, Marchand E, Place V, Fourchotte V, De La Rochefordière A, Dridi S, et al. Evaluation and impact of residual disease in locally advanced cervical cancer after concurrent chemoradiation therapy: results of a multicenter study. Eur J Surg Oncol. 2013;39:1428-34. Van Kol K, Ebisch R, Beugeling M, Cnossen J, Nederend J, van Hamont D, et al. Comparing Methods to Determine Complete Response to Chemoradiation in Patients with Locally Advanced Cervical Cancer. Cancers (Basel). 2023;16:198. Federico A, Anchora LP, Gallotta V, Fanfani F, Cosentino F, Turco LC, et al. Clinical Impact of Pathologic Residual Tumor in Locally Advanced Cervical Cancer Patients Managed by Chemoradiotherapy Followed by Radical Surgery: A Large, Multicenter, Retrospective Study. Ann Surg Oncol. 2022;29:4806-14. Houvenaeghel G, Lelievre L, Buttarelli M, Jacquemier J, Carcopino X, Viens P, et al. Contribution of surgery in patients with bulky residual disease after chemoradiation for advanced cervical carcinoma. Eur J Surg Oncol. 2007;33:498-503. Ota T, Takeshima N, Tabata T, Hasumi K, Takizawa K. Adjuvant hysterectomy for treatment of residual disease in patients with cervical cancer treated with radiation therapy. Br J Cancer. 2008;99:1216-20. Yavas G, Yavas C, Sen E, Oner I, Celik C, Ata O. Adjuvant carboplatin and paclitaxel after concurrent cisplatin and radiotherapy in patients with locally advanced cervical cancer. Int J Gynecol Cancer. 2019;29:42-7. Atci MM, Akagunduz B, Demir M, Dönmez Yilmaz B, Akin Telli T, Can O, et al. Effect of Adjuvant Chemotherapy in Stage III Cervical Cancer Patients Treated with Concurrent Chemoradiation: A Multicenter Study. Oncol Res Treat. 2022;45:254-61. Mileshkin LR, Moore KN, Barnes EH, Gebski V, Narayan K, King MT, et al. Adjuvant chemotherapy following chemoradiotherapy as primary treatment for locally advanced cervical cancer versus chemoradiotherapy alone (OUTBACK): an international, open-label, randomised, phase 3 trial. Lancet Oncol. 2023;24:468-82. Tovanabutra C, Asakij T, Rongsriyam K, Tangjitgamol S, Tharavichitkul E, Sukhaboon J, et al. Long-Term Outcomes and Sites of Failure in Locally Advanced, Cervical Cancer Patients Treated by Concurrent Chemoradiation with or without Adjuvant Chemotherapy: ACTLACC Trial. Asian Pac J Cancer Prev. 2021;22:2977-85. Takekuma M, Takahashi F, Mabuchi S, Kudaka W, Horie K, Ikeda M, et al. Propensity score-matched analysis of systemic chemotherapy versus salvage hysterectomy for persistent cervical cancer after definitive radiotherapy/concurrent chemoradiotherapy. BMC Cancer. 2020;20:1169. Additional Declarations No competing interests reported. Supplementary Files supplementary1a.docx supplementary1b.docx supplementary2a.docx supplementary2b.docx supplementary3a.docx supplementary3b.docx Supplementary4.docx Cite Share Download PDF Status: Published Journal Publication published 02 Oct, 2025 Read the published version in BMC Cancer → Version 1 posted Editorial decision: Revision requested 02 Apr, 2025 Reviews received at journal 01 Apr, 2025 Reviewers agreed at journal 27 Mar, 2025 Reviews received at journal 27 Mar, 2025 Reviewers agreed at journal 26 Mar, 2025 Reviewers invited by journal 24 Mar, 2025 Submission checks completed at journal 19 Mar, 2025 First submitted to journal 18 Mar, 2025 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. 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Zou","email":"","orcid":"","institution":"Chongqing University Cancer Hospital \u0026 Chongqing Cancer Institute \u0026 Chongqing Cancer Hospital","correspondingAuthor":false,"prefix":"","firstName":"Dongling","middleName":"","lastName":"Zou","suffix":""}],"badges":[],"createdAt":"2024-12-19 15:38:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5678120/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5678120/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12885-025-14691-y","type":"published","date":"2025-10-02T15:57:02+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":79179974,"identity":"645de94e-6fc2-4530-84b8-ca27df4e8a64","added_by":"auto","created_at":"2025-03-25 10:21:23","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":258113,"visible":true,"origin":"","legend":"\u003cp\u003eThe flowchart of our studying patiens.\u003c/p\u003e","description":"","filename":"11.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5678120/v1/3821fe15a7a11a20129417d1.jpg"},{"id":79179976,"identity":"7b68f652-92c4-4893-9caf-83011bbb4895","added_by":"auto","created_at":"2025-03-25 10:21:23","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":298017,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier analyses of overall survival (2a) and progression-free survival (2b) comparing patients with SCC antigen level of \u0026gt; 4.4 vs. ≤ 4.4 ng/ml.\u003c/p\u003e","description":"","filename":"12.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5678120/v1/a9b6b7063729dad51b0804d5.jpg"},{"id":79177445,"identity":"9efc764e-05bf-4f7e-ab58-ec283355602e","added_by":"auto","created_at":"2025-03-25 10:05:23","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":295687,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier analyses of overall survival (3a) and progression-free survival (3b), comparing patients with AJCC stage T3a-3b vs. T2b\u003c/p\u003e","description":"","filename":"13.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5678120/v1/ad38ab6a761c9860458278ef.jpg"},{"id":79179263,"identity":"5420082b-7af3-4c21-b235-e3c087ea0585","added_by":"auto","created_at":"2025-03-25 10:13:23","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":293626,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier analyses of overall survival (4a) and progression-free survival (4b), comparing patients with residual disease size of ≥ 1.1 cm vs. \u0026lt; 1.1 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10:13:23","extension":"docx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":13238,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary4.docx","url":"https://assets-eu.researchsquare.com/files/rs-5678120/v1/a9256b8e9bcc9c47c5467391.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prognostic factors of locally advanced cervical cancer after concurrent chemoradiotherapy","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCervical cancer is the fourth most common malignancy in women worldwide \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Its incidence and mortality rates in China have dramatically increased owing to successful screening programs \u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. More than fifty percent of new patients are diagnosed with locally advanced cervical cancer (LACC) (International Federation of Gynecology and Obstetrics,2018 [International Federation of Gynecology and Obstetrics,FIGO 2018] stages 1B2 to 4A) \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. Based on five important randomized controlled trials \u003csup\u003e[\u003cspan additionalcitationids=\"CR5 CR6 CR7\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e, which revealed that adding chemotherapy to radiotherapy increases survival rates, external beam radiotherapy (EBRT) and concurrent chemotherapy, followed by brachytherapy (BT), have been the mainstay treatment for LACC. Unfortunately, recurrences occur frequently primarily within the first 2 years of follow-up. The prognosis of LACC remains dismal. Previous studies \u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e have revealed that approximately 35% of patients with LACC demonstrated disease progression after concurrent chemoradiotherapy (CCRT), with a 5-year disease-free survival rate of 58%.\u003c/p\u003e \u003cp\u003eThe tumor stage, histology, tumor volume, lymph node involvement and residual diease (RD) were the primary early prognostic variables \u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. The apparent diffusion coefficient (ADC) values has also been reported to predict tumor treatment response, prognosis and survival of locally advanced cervical cancer after chemotherapy and radiotherapy \u003csup\u003e[\u003cspan additionalcitationids=\"CR13 CR14 CR15\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. As known, Functional magnetic resonance imaging (MRI) plays a critical role in many aspects of radiotherapy management, including tumor staging, treatment planning and delivery, post-treatment response assessment, and long-term surveillance \u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Diffusion-weighted imaging (DWI), a common functional imaging modality, can study the movement of water molecules in tissue to detect and characterise disease. The ADC is used to quantify DWI and can provide information regarding tumor cellularity and proliferation by reflecting the restricted motion of water molecules \u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. In general, malignant tumor tends to have lower ADC values.\u003c/p\u003e \u003cp\u003eIn recent years, the challenge of reducing recurrence and improving survival has emerged in patients with LACC. Thereby, general clinical characteristics and pre- and post-treatment MRI characteristics of the patients were collected to analyze the factors affecting the prognosis and enhance the prognosis of LACC In this study, we investigated a variety of clinical and imaging parameters to figure out which factors affected the prognosis following CCRT for LACC. It may provide some guidance for additional subsequent treatment after initial chemoradiotherapy in order to improve prognosis.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003e Between May 2018 and December 2020, 443 paients diagnosed with biopsy-proven locally advanced squamous cell carcinoma (SCC) of the cervix (American Joint Committee on Cancer (AJCC) stage T2b to T3b) were initially screened. The tumors were confined to the pelvic cavity without any evidence of distant metastases (including para-aortic lymph node metastases), underwent DWI-MRI, before and 1 month after treatment and none of the patients had received prior treatment. Patients who did not receive chemotherapy during radiotherapy, other modulated radiotherapy rather than EBRT. and did not complete radiotherapy were also excluded. In total, 189 patients had complete clinical records, including variables as age, stage, serum hemoglobin level, SCC antigen level, radiotherapy duration, pre-treatment tumor size, RD, pelvic lymph nodes (PLNs) status, pre-treatment ADC\u003csub\u003emean\u003c/sub\u003e value, post-treatment ADC\u003csub\u003emean\u003c/sub\u003e value, and change ADC\u003csub\u003emean\u003c/sub\u003e value. The flowchart of including patients was drawn (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This retrospective study was approved by the institutional review board of our hospital (ethic number: 011). Furthermore, written informed consent was obtained from all patients.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eTreatments\u003c/h3\u003e\n\u003cp\u003eAll patients were treated CCRT with a combination of EBRT and platinum-based chemotherapy at least one course, administered by weekly or tr-weekly. Intensity-modulated radiotherapy and high\u0026ndash;dose-rate image-guided brachytherapy (HDR-BT) were included. EBRT was delivered at a dose of 45 to 50.8Gy in 25 or 28 fractions, with a daily fraction size of 1.8 or 2.0Gy. The maximum and minimum values within the target range did not exceed\u0026thinsp;\u0026plusmn;\u0026thinsp;10% of the prescribed dose, the dosage of enlarged lymph nodes reached 50 to 66Gy and involving parametrial reached 50 to 54Gy. Simultaneously, HDR-BT was performed with a source of 192 Ir. A dose of minimum dose covering 90% of high risk clinical tumor volume (D90 HR-CTV) reached 22 to 33Gy in 4 to 6 fractions.Patients with positive common iliac lymph nodes (short axis diameter\u0026thinsp;\u0026ge;\u0026thinsp;15 mm) were treated with expanded-field radiotherapy ( included the area adjacent to the aorta and inferior vena cava, with a lower border of the aortic bifurcation. And the upper boundary of the extended field was usually at T12 or the renal vessel).\u003c/p\u003e\n\u003ch3\u003eImaging protocol and predictive parameter calculation\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003eImaging protocol and predictive parameter calculation\u003c/div\u003e \u003cp\u003eMRI was performed using a 1.5T system machine. Pelvic MRI was performed before (within 4 weeks of the initiation of treatment) and 1 month (within 6 weeks following the final BT) after treatment. Our institution started performing DWI\u0026ndash;MRI since 2018. The protocol included enhanced DWI, T1-weighted imaging (T1WI), and T2-weighted imaging (T2WI). T2WI revealed that the cervical tumor demonstrated a significant signal intensity. Tumor size was defined as the maximum diameter of tumor dimension measured on T2WI\u0026ndash;MRI (in cm). The positive PLNs defined as the short diameter\u0026thinsp;\u0026ge;\u0026thinsp;1.5 cm. Enhanced DWI was used, and the ADC map was automatically generated. The ADC maps were calculated using all three B values. The ADC\u003csub\u003emean\u003c/sub\u003e value was measured in the tumor at each time point. A region of interest (ROI) was manually established on the single axial ADC map image displaying the tumor\u0026rsquo;s maximal dimension. The ROIs was drawn by an experienced radiologists specialising in gynecological oncology who was blinded to outcome. Areas of necrosis within the tumour were avoided.\u003c/p\u003e\n\u003ch3\u003eFollow-up\u003c/h3\u003e\n\u003cp\u003eAfter one month following chemoradiation, clinical and radiological examinations were performed every 3 months for the first 2 years, every 6 months for the next 3 years, and once yearly thereafter.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe study endpoints included progression-free survival PFS and OS. The duration of PFS was calculated from the date of treatment initiation to the date of any disease progression or last follow-up, whereas the duration of OS was calculated from the date of treatment initiation to the date of death or last follow-up. Data analysis was conducted using Statistical Package for the Social Sciences Statistics software (version 26.0) and R Studio (version 4.2.2). The Cox proportional hazards model was utilized to evaluate the effect of significant factors on the survival endpoints for univariate and multivariate analyses. The optimal cutoff value of SCC antigen level, RD and post-ADC\u003csub\u003emean\u003c/sub\u003e were identified as the point at which the log-rank \u003cem\u003ep\u003c/em\u003e-value was at a minimum (Supplementary 1a,1b,2a,2b,3a,3b). The Kaplan\u0026ndash;Meier method was used to calculate PFS and OS, and the results were compared using the log-rank test. A \u003cem\u003eP\u003c/em\u003e-value of \u0026lt;\u0026thinsp;0.05 was considered to indicate statistical significance. Statistical tests were conducted according to a two-sided significance level.In this study, missing variables were imputed using multiple imputation by chained equations (MICE) and the random forest (RF) algorithm. (Supplementary 4).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eBaseline characteristics\u003c/h2\u003e \u003cp\u003eThis study included 189 patients with pathological evidence of SCC. Clinical and radiological features were summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The mean and median age at diagnosis were 53.6(\u0026plusmn;\u0026thinsp;7.6) and 53(range: 36 \u0026minus;\u0026thinsp;71) years, respectively. The median hemoglobin and SCC antigen level were 121.0 g/L (range: 48.0-161.0) and 4.4 mg/dl ( range: 0.6\u0026ndash;96.0), respectively. Pre-treatment T2WI\u0026ndash;MRI revealed mean and median maximal tumor sizes of 4.4 (\u0026plusmn;\u0026thinsp;0.5) and 4.3 (range: 1.3\u0026ndash;8.2) cm, respectively. Thirty patients were diagnosed with positive pelvic lympha nodes. Eleven patients of them with positive common iliac lymph nodes received extended field radiotherapy. Most patients of 85% completed EBRT and HDR-BT within 8 weeks and 80.9% completed concurrent platinum-based chemotherapy (five cycles weekly or two cycles of tri-weekly cisplatin-based chemotherapy). Additionally, adjuvant chemotherapy (ACT) was administered to 41.2% of patients following CCRT. The median ADC\u003csub\u003emean\u003c/sub\u003e values of pre- and post-treatment were 0.88 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e and 1.55 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e mm\u003csup\u003e2\u003c/sup\u003e/s, respectively. The median change in ADC was 0.70 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e mm\u003csup\u003e2\u003c/sup\u003e/s. Based on the AJCC stage system, 115, 2,and 74 of patients were diagnosed with stage T2b, T3a, and T3b, respectively. RD was detected in the cervix of 64 patients but not in any of the PLNs.The median RD size was 0.0 cm (range: 0.0-4.8).\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\u003ePatient characteristics (N\u0026thinsp;=\u0026thinsp;189)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedian (range) / N (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years; median)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53.0 (36.0\u0026ndash;71.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCC antigen level (ng/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.4 (0.6\u0026ndash;96.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (g/l)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e121.0 (48.0-161.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePretreament tumor size (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.3 (1.30\u0026ndash;8.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePretreatment ADC\u003csub\u003emean\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.88 (0.45\u0026ndash;1.58)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost-treatment ADC\u003csub\u003emean\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.55 (0.94\u0026ndash;2.36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChange in ADC\u003csub\u003emean\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.70 (0.00-3.04)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of radiotherapy (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47 (28\u0026ndash;84)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidual disease size (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0 (0.0-4.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAJCC staging\u003c/p\u003e \u003cp\u003eT2b\u003c/p\u003e \u003cp\u003eT3a-3b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e113(59.79)\u003c/p\u003e \u003cp\u003e76(40.21)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePelvic lymph node\u003c/p\u003e \u003cp\u003eNegative\u003c/p\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e159 (84.13)\u003c/p\u003e \u003cp\u003e30 (15.87)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemotherapy regimen\u003c/p\u003e \u003cp\u003eWeekly\u003c/p\u003e \u003cp\u003eTri-weekly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89 (47.10)\u003c/p\u003e \u003cp\u003e100 (52.90)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemotherapy\u003c/p\u003e \u003cp\u003eComplete\u003c/p\u003e \u003cp\u003eIncomplete\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e153 (80.95)\u003c/p\u003e \u003cp\u003e36 (19.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdjuvant chemotherapy\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e111 (58.73)\u003c/p\u003e \u003cp\u003e78 (41.27)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExtended radiotherapy\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e178 (94.18)\u003c/p\u003e \u003cp\u003e11 (5.82)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eData presented as median (range) or n (%). SCC: squamous cell carcinoma; ADC\u003csub\u003emean\u003c/sub\u003e: mean apparent diffusion coefficient; AJCC: American Joint Committee on Cancer; HR: hazard ratio; CI: confidence interval.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSurvival\u003c/h3\u003e\n\u003cp\u003eDuring a median follow-up period of 58 months (range, 11\u0026ndash;71 months). 123 (65.0%) patients were revealed no residual tumor one month following CCRT. About 80% of patients had no RD in the cervix at six months following treatment, which was confirmed by MRI. 56 (29.6%) patients demonstrated disease progression at the latest follw-up time, including central recurrence (n\u0026thinsp;=\u0026thinsp;21, 37.5%), local regional recurrence (n\u0026thinsp;=\u0026thinsp;20, 35.7%), local regional recurrence with distant metastasis (n\u0026thinsp;=\u0026thinsp;12, 21.4%), and distant metastasis only (n\u0026thinsp;=\u0026thinsp;3, 5.4%). Furthermore, 23 patients died of their disease whereas 33 remained alive.The 5-year PFS and OS rates were 73.8% and 85.5%, respectively. For patients with AJCC T2b and T3a-3b, the 5-year PFS and OS rates were 87.1% and 53.7%, respectively.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eUnivariate and multivariate analysis\u003c/h2\u003e \u003cp\u003eTables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e present the univariate and multivariate clinical outcome results. Univariate analysis revealed that SCC antigen level, stage, pre-treatment tumor size, RD and post-treatment ADC\u003csub\u003emean\u003c/sub\u003e were significant predictors of PFS and OS. Positive PLN and ACT were predictors of PFS and OS, respectively. Other factors, including age, pre-treatment hemoglobin levels, duration of radiation therapy, chemotherapy regimen, pre-treatment ADC\u003csub\u003emean\u003c/sub\u003e and the change ADC\u003csub\u003emean\u003c/sub\u003e were not associated with PFS and OS. In multivariate analysis, SCC antigen level, stage, and were the independent predictors of PFS and OS.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCox regression analysis of clinical and MRI variables for progression-free survival\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnivariate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMultivariate\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.963\u0026ndash;1.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.883\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAJCC T stage (T3a-3b)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.008\u0026ndash;5.986\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.821\u0026ndash;5.914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCC (ng/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.013\u0026ndash;1.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.380\u0026ndash;4.778\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.988\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.976\u0026ndash;1.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of radiotherapy (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.967\u0026ndash;1.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.774\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemotherapy regimen (Triweekly)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.659\u0026ndash;1.893\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.682\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemotherapy (Incomplete)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.656\u0026ndash;2.354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.505\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdjuvant chemotherapy (Yes)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.604\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.948\u0026ndash;2.713\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePelvic lymph node (Positive)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.273\u0026ndash;4.590\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.540\u0026ndash;2.278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.777\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExtended radiotherapy (No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.699\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.610\u0026ndash;4.736\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePretreatment tumor size (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.610\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.312\u0026ndash;1.975\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.746\u0026ndash;2.506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidual disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.608\u0026ndash;2.498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.621\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.282\u0026ndash;2.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePretreatment ADC\u003csub\u003emean\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.025\u0026ndash;1.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost-treatment ADC\u003csub\u003emean\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.094\u0026ndash;0.581\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.225\u0026ndash;1.382\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.207\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChange in ADC\u003csub\u003emean\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.709\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.404\u0026ndash;1.244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eMRI: magnetic resonance imaging; SCC: squamous cell carcinoma; ADC\u003csub\u003emean\u003c/sub\u003e: mean apparent diffusion coefficient; AJCC: American Joint Committee on Cancer; HR: hazard ratio; CI: confidence interval.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCox regression analysis of clinical and MRI variables for overall survival\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnivariate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMultivariate\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.980\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.927\u0026ndash;1.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.472\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAJCC T stage (T3a-3b)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.330\u0026ndash;7.426\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.517\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.783\u0026ndash;4.834\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.043\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCC (ng/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.018\u0026ndash;1.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.005\u0026ndash;1.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.015\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.964-1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of radiotherapy (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.972\u0026ndash;1.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemotherapy regimen (Triweekly)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.953\u0026ndash;5.662\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemotherapy (Incomplete)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.776\u0026ndash;4.593\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdjuvant chemotherapy (Yes)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.521\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.088\u0026ndash;5.841\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.031\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.872\u0026ndash;5.745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.094\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePelvic lymph node (Positive)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.376\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.921\u0026ndash;6.127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExtended radiotherapy (No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.890\u0026ndash;10.410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePretreatment tumor size (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.691\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.237\u0026ndash;2.311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.2027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.821\u0026ndash;1.760\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.343\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidual disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.877\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.380\u0026ndash;2.580\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.712\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.149\u0026ndash;2.578\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePretreatment ADC\u003csub\u003emean\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.962\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.076\u0026ndash;12.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.976\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost-treatment ADC\u003csub\u003emean\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.051\u0026ndash;0.918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.038\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.719\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.158\u0026ndash;3.269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.669\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChange in ADC\u003csub\u003emean\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.461\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.176\u0026ndash;1.207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eMRI: magnetic resonance imaging; SCC: squamous cell carcinoma; AJCC: American Joint Committee on Cancer; ADC\u003csub\u003emean\u003c/sub\u003e: mean apparent diffusion coefficient; HR: hazard ratio; CI: confidence interval.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe optimal cutoff value was identified as the point at which the log-rank p-value was at a minimum. The optimal cutoff values of post-treatment ADC\u003csub\u003emean\u003c/sub\u003e were 1.23 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e and 1.33 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e mm\u003csup\u003e2\u003c/sup\u003e/s for PFS and OS, respectively. As a categorical variable analyzed in multivariate analysis again, post-treatment ADC\u003csub\u003emean\u003c/sub\u003e was not a significant predictor of PFS and OS.The optimal cutoff value of SCC antigen level were 3.2ng/ml for PFS and 12.8ng/ml. The optimal cutoff values of RD was 1.1 cm for both PFS and OS.\u003c/p\u003e \u003cp\u003eThe Kaplan-Meier curves were plotted. The optimal cutoff values of SCC antigen level for PFS and OS were different. However, when analyzed with median value, patients with median SCC antigen level\u0026thinsp;\u0026gt;\u0026thinsp;4.4 ng/ml demonstrated both worse PFS (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea) and OS (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.015) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb) compared to patients with SCC antigen level of \u0026le;\u0026thinsp;4.4 ng/ml. Patients with AJCC stage T3a-3b exhibited worse PFS (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea) and OS (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.043) compared with those with AJCC stage T2b (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). The 5-year PFS (34.7% vs. 85.9%; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea) and 5-year OS (65.2% vs. 91.4%; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb) were poorer in patients with RD\u0026thinsp;\u0026ge;\u0026thinsp;1.1 cm than in those with RD\u0026thinsp;\u0026lt;\u0026thinsp;1.1 cm.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eBased on our research, SCC antigen level, pre-treatment tumor size, positive PLN, stage, ACT, RD and post-treatment ADC\u003csub\u003emean\u003c/sub\u003e were predictors of PFS and OS. On multivariate analysis, SCC antigen level, stage and RD were significant independent factors excluding ADC\u003csub\u003emean\u003c/sub\u003e value.\u003c/p\u003e \u003cp\u003eAs we know, the benefit of CCRT for survival may diminish as staging increases. The FIGO 2009 and 2018 schema indicated that the 5-year survival rates for stage IIB tumors were 61.3% and 63.9%, those for stage IIIA tumors were 40.5% and 40.7%, and those for stage IIIB tumors were 38.4% and 41.4%, respectively \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. The same trend was observed in our study. The 5-year PFS and OS for patients with AJCC stage T3a-3b compared to T2b declined by 33.4% and 12.6%, respectively.\u003c/p\u003e \u003cp\u003eThe stage was illustrated as a major predictor of survival in patients with LACC after CCRT. Other variables, such as histological subtype, SCC antigen level, HGB level, ADC\u003csub\u003emean\u003c/sub\u003e value, and RD were also reported to associate with survival \u003csup\u003e[\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. The prognosis was worse for patients with adenocarcinoma (AC) or adenosquamous carcinoma (ASC) than those with SCC \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Patiens with only histological subtype of SCC were analyzed in our study. The PFS and OS rates of them were higher than AC and ASC histological subtype reported by other studies \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e and the SCC antigen level was a significant prognostic factor for survival outcome also discovered in this study. However, different results from other studies \u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e indicated that locally progressed cervical AC/ASC exhibited comparable survival rates to SCC. Therfore, it also remains controversial whether the type of pathology influences prognosis. We can make relevant comparative studies in our future research.\u003c/p\u003e \u003cp\u003eDWI\u0026ndash;MRI has the ability to differentiate normal tissue from cervical carcinoma and its results are quantified in terms of ADC. The decreased ADC of malignant tumors indicate the limited mobility of water molecules. Multiple studies have demonstrated that pre-treatment ADC, post-treatment ADC, change in ADC and the 90th percentile ADC value over the chemoradiotherapy course for cervical cancer are predictors of prolonged survival, recurrence outcomes, and clinical or rapid response to treatment \u003csup\u003e[\u003cspan additionalcitationids=\"CR13 CR14 CR15 CR16\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Our research revealed that the post-treatment ADC\u003csub\u003emean\u003c/sub\u003e was associated with PFS and OS based on univariate analysis but not statistically significant in multivariate analysis. Valentini \u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e showed the similar conclusion that ADC\u003csub\u003emean\u003c/sub\u003e did not correlate with treatment outcome. The reason were more factors including in this study and some of them may existed interaction,and data imputation affecting the results.\u003c/p\u003e \u003cp\u003eThe presence of RD has been reported as a important prognostic factor for survival. which was determined via MRI in clinical practice. MRI was considered a crucial tool for evaluating treatment response and positron emission tomography/computed tomography (PET/CT) was often employed \u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. The existence of a remnant tumor on MRI as an independent indicator of disease progression \u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. A similar finding was reported in this study. In addition, we revealed the optimal cutoff value of was 1.1 cm. Patients with RD size\u0026thinsp;\u0026ge;\u0026thinsp;1.1 cm demonstrated a poor PFS and OS on the survival curve. However, studies \u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e revealed that MRI had limited accuracy in evaluating residual tumors. Histopathological assessment was the most effective method for determining RD after CCRT. According to Hequet \u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e, the pathologically confirmed RD size larger 1 cm decreased DFS but showed no effect on OS (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.08). But MRI exhibited a false positive rate of 29.2% and a false negative rate of 11.1% for identifying RD. Federico \u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e also made the conclusion that pathological RD in the cervix was statistically significantly associated with worse DFS and OS.\u003c/p\u003e \u003cp\u003eAlthough RD was an important factor affecting the survival of LACC after radiotherapy, the methods applied to indentify RD and the post-radiation treatment interventions are uncertain. Salvage surgery improved the outcome in individuals with central pelvic RD who do not have metastatic disease following CCRT \u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e, The 3-year and 5-year OS rates for patients with RD size\u0026thinsp;\u0026ge;\u0026thinsp;2 cm improved to 64.9% and 55.6%, respectively. However, it is related to an increased risk of complications, including fistulas, gastrointestinal or urinary tract complications, and sexual dysfunction, which can lower patients\u0026rsquo; quality of life and affect their survival.\u003c/p\u003e \u003cp\u003eFurthermore, ACT was often used as an additional therapy to improve survival for patients with LACC following CCRT. According to two retrospective studies from Turkey \u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e, DFS and OS increased especially in patients with stage III disease. However, the results of two large prospective trials\u0026mdash;the OUTBACK trial \u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e and the ACTLACC trial \u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e\u0026mdash;indicated that ACT couldn\u0026rsquo;t improve prognosis. Compared with systemic ACT, salvage hysterectomy decreased mortality by approximately 60% in patients with persistent cervical cancer after definitive RT/CCRT in another retrospective study.\u003c/p\u003e \u003cp\u003eIn fact, ACT was commonly employed in clinical practice at our center to treat patients with advanced stage or RD after chemoradiotherapy. Our study found ACT was a predictor of OS in univariate analysis, but not significant in mulitivariate analysis. The reason maybe there was no uniform criteria to identify the patients who accept ACT after CCRT. The OUTBACK trial also didn\u0026rsquo;t randomised patients after completion of standard chemoradiation. Although patients who had salvage surgery were not included in our analysis, individuals with RD size\u0026thinsp;\u0026ge;\u0026thinsp;1.1 cm were given the option to be considered for salvage surgery.\u003c/p\u003e \u003cp\u003eTherefore, Our center is currently conducting prospective clinical trials (NCT: 04409860 and NCT: 05749887) to evaluate the effectiveness of ACT and salvage surgery for patients with RD after CCRT for cervical cancer. The two trails aim to investigate suitable treatment options for high-risk patients with LACC following CCRT and to further explore the prognostic factors.\u003c/p\u003e \u003cp\u003eCompared with other studies, our study only concluded the histological subtype of SCC, thus avoiding the prognostic impact of the pathological type. Moreover, this study included plenty variabes of imaging and clinical features for prognostic analysis. Additionally, we found that adjuvant therapy may be necessary for patients with advanced stage and RD size\u0026thinsp;\u0026ge;\u0026thinsp;1.1 cm following CCRT. Our study had some limitations. Neither pathological evidence nor PET/CT scans were used to help detect RD in the cervix. Pathology confirmation of locoregional RD prior to adjuvant treatment is necessary in future. Furthermore, tumor volume, tumor size reduction rate, and percentage ADC value reported by other studies that may affect prognosis were ignored in this study. More imaging parameters should be take into consideration in future investigation. Additionally, this was a retrospective study with a limited sample size. The results were unreliable and have not been validated in an independent dataset, which may limit the generalizability of our results beyond the study population. Muiltcenter prospective studies with larger sample sizes should be conducted.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study revealed that SCC antigen level, stage, and RD were independent variables associated with OS and PFS in patients with AJCC stage Tab-T3b squamous cell cervical cancer receiving CCRT. The ADC\u003csub\u003emean\u003c/sub\u003e value could not be a preditor of PFS and OS. Adjuvant therapy may be recommended for patients with advanced stage, higher SCC antigen level and RD size\u0026thinsp;\u0026ge;\u0026thinsp;1.1 cm in order to improve survival.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMRI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMagnetic resonance imaging\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLACC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLocally advanced cervical cancer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCCRT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConcurrent chemoradiotherapy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eADC\u003csub\u003emean\u003c/sub\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMean apparent diffusion coefficient\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePFS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProgression-free survival\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOverall survival\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSCC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSquamous cell carcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eResidual disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAJCC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAmerican Joint Committee on Cancer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFIGO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInternational Federation of Gynecology and Obstetrics\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eADC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eApparent diffusion coefficient\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDWI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDiffusion-weighted imaging\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHDR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHigh\u0026ndash;dose-rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ebrachytherapy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eERBT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eExternal beam radiotherapy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePLN\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePelvic lymph node\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eACT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAdjuvant chemotherapy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAJCC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAmerican Joint Committee on Cancer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAdenocarcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eASC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAdenosquamous carcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors express sincere appreciation to all the individuals involved in the improvement of this manuscript. Special thanks are extended to experienced radiologist Lu Yang for her invaluable support in conducting radiology evaluation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: Xiuying Li, Dongling Zou; Data collection: Zejia Mao, Qian Zheng, Yue Huang; Investigation: Zejia mao, Hao He, Ling Long, Jing Wang; Data analysis and graphing: Xiuying Li, Qiaoling Li; Supervision: Misi He, Mingfang Guo; Writing original draft: Xiuying Li; Writing review \u0026amp; editing: Dongling Zou. All authors contributed to the article and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by Beijing Heaalth Alliance Charitable Foundation (BJHA-CRP-092), Wu Jieping Medical Foundation (320.6750.2022-22-12), Qujiang District Quzhou City Life Oasis Public Service Center (113), Talent Program of Chongqing (cstc2024rcih-bgzxm0162), Chongqing Health Commission (2023ZDXM029), The Project for Enhancing Scientific Research Capabilities of Chongqing University Cancer Hospital (2023nlts005, 2023nlts009).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data supporting the results of this study are available from the corresponding authors upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study has been performed in accordance with the 1964 Helsinki Declaration and has been approved by the Institutional Review Board of\u0026nbsp;Chongqing University Cancer Hospital \u0026amp; Chongqing Cancer Institute \u0026amp; Chongqing Cancer Hospital\u0026nbsp;and the ethic number was 011. A written informed consent was obtained from all patients included in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFirst author: Xiuying Li\u003c/p\u003e\n\u003cp\u003eAuthors and Affiliations\u003c/p\u003e\n\u003cp\u003eDepartment of Gynecologic Oncology, Chongqing University Cancer Hospital \u0026amp; Chongqing Cancer Institute \u0026amp; Chongqing Cancer Hospital, Chongqing, 400030, China.\u003c/p\u003e\n\u003cp\u003eXiuying Li, Qiaoling Li1, Misi He, Mingfang Guo, Hao He, Yue Huang, Qian Zheng, Jing Wang \u0026amp; Dongling Zou\u003c/p\u003e\n\u003cp\u003eChongqing Specialized Medical Research Center of Ovarian Cancer, Chongqing, 400030, China.\u003c/p\u003e\n\u003cp\u003eMisi He, Qian Zheng \u0026amp; Dongling Zou\u003c/p\u003e\n\u003cp\u003eOrganoid Transformational Research Center, Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment, Chongqing University Cancer Hospital, Chongqing, 400030, China.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMisi He, Qian Zheng \u0026amp; Dongling Zou\u003c/p\u003e\n\u003cp\u003eSchool of Medicine,Chongqing University,Chongqing University Cancer Hospital, Chongqing, 400030, China.\u003c/p\u003e\n\u003cp\u003eZejia Mao \u0026amp; Ling Long\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFerlay J, Colombet M, Soerjomataram I, Parkin DM, Pi\u0026ntilde;eros M, Znaor A, et al. 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Locally advanced adenocarcinoma and adenosquamous carcinomas of the cervix compared to squamous cell carcinomas of the cervix in gynecologic oncology group trials of cisplatin-based chemoradiation. Gynecol Oncol. 2014;135:208\u0026ndash;12. \u003c/li\u003e\n\u003cli\u003eValentini AL, Micc\u0026ograve; M, Gui B, Giuliani M, Rodolfino E, Telesca AM, et al. The PRICE study: The role of conventional and diffusion-weighted magnetic resonance imaging in assessment of locally advanced cervical cancer patients administered by chemoradiation followed by radical surgery. Eur Radiol. 2018;28(6):2425-2435.\u003c/li\u003e\n\u003cli\u003eJalaguier-Coudray A, Villard-Mahjoub R, Delouche A, Delarbre B, Lambaudie E, Houvenaeghel G, et al. Value of Dynamic Contrast-enhanced and Diffusion-weighted MR Imaging in the Detection of Pathologic Complete Response in Cervical Cancer after Neoadjuvant Therapy: A Retrospective Observational Study. Radiology. 2017;284(2):432-442.\u003c/li\u003e\n\u003cli\u003ePasciuto T, Moro F, Collarino A, Gambacorta MA, Zannoni GF, Oradei M, et al. The Role of Multimodal Imaging in Pathological Response Prediction of Locally Advanced Cervical Cancer Patients Treated by Chemoradiation Therapy Followed by Radical Surgery. Cancers (Basel). 2023;15(12):3071.\u003c/li\u003e\n\u003cli\u003ePark JJ, Kim CK, Park BK. Prediction of disease progression following concurrent chemoradiotherapy for uterine cervical cancer: value of post-treatment diffusion-weighted imaging. Eur Radiol. 2016;26:3272-9.\u003c/li\u003e\n\u003cli\u003eAngeles MA, Baissas P, Leblanc E, Lusque A, Ferron G, Ducassou A, et al. Magnetic resonance imaging after external beam radiotherapy and concurrent chemotherapy for locally advanced cervical cancer helps to identify patients at risk of recurrence. Int J Gynecol Cancer. 2019;29(3):480-486.\u003c/li\u003e\n\u003cli\u003eHequet D, Marchand E, Place V, Fourchotte V, De La Rochefordi\u0026egrave;re A, Dridi S, et al. Evaluation and impact of residual disease in locally advanced cervical cancer after concurrent chemoradiation therapy: results of a multicenter study. Eur J Surg Oncol. 2013;39:1428-34. \u003c/li\u003e\n\u003cli\u003eVan Kol K, Ebisch R, Beugeling M, Cnossen J, Nederend J, van Hamont D, et al. Comparing Methods to Determine Complete Response to Chemoradiation in Patients with Locally Advanced Cervical Cancer. Cancers (Basel). 2023;16:198.\u003c/li\u003e\n\u003cli\u003eFederico A, Anchora LP, Gallotta V, Fanfani F, Cosentino F, Turco LC, et al. Clinical Impact of Pathologic Residual Tumor in Locally Advanced Cervical Cancer Patients Managed by Chemoradiotherapy Followed by Radical Surgery: A Large, Multicenter, Retrospective Study. Ann Surg Oncol. 2022;29:4806-14. \u003c/li\u003e\n\u003cli\u003eHouvenaeghel G, Lelievre L, Buttarelli M, Jacquemier J, Carcopino X, Viens P, et al. Contribution of surgery in patients with bulky residual disease after chemoradiation for advanced cervical carcinoma. Eur J Surg Oncol. 2007;33:498-503.\u003c/li\u003e\n\u003cli\u003eOta T, Takeshima N, Tabata T, Hasumi K, Takizawa K. Adjuvant hysterectomy for treatment of residual disease in patients with cervical cancer treated with radiation therapy. Br J Cancer. 2008;99:1216-20.\u003c/li\u003e\n\u003cli\u003eYavas G, Yavas C, Sen E, Oner I, Celik C, Ata O. Adjuvant carboplatin and paclitaxel after concurrent cisplatin and radiotherapy in patients with locally advanced cervical cancer. Int J Gynecol Cancer. 2019;29:42-7.\u003c/li\u003e\n\u003cli\u003eAtci MM, Akagunduz B, Demir M, D\u0026ouml;nmez Yilmaz B, Akin Telli T, Can O, et al. Effect of Adjuvant Chemotherapy in Stage III Cervical Cancer Patients Treated with Concurrent Chemoradiation: A Multicenter Study. Oncol Res Treat. 2022;45:254-61.\u003c/li\u003e\n\u003cli\u003eMileshkin LR, Moore KN, Barnes EH, Gebski V, Narayan K, King MT, et al. Adjuvant chemotherapy following chemoradiotherapy as primary treatment for locally advanced cervical cancer versus chemoradiotherapy alone (OUTBACK): an international, open-label, randomised, phase 3 trial. Lancet Oncol. 2023;24:468-82.\u003c/li\u003e\n\u003cli\u003eTovanabutra C, Asakij T, Rongsriyam K, Tangjitgamol S, Tharavichitkul E, Sukhaboon J, et al. Long-Term Outcomes and Sites of Failure in Locally Advanced, Cervical Cancer Patients Treated by Concurrent Chemoradiation with or without Adjuvant Chemotherapy: ACTLACC Trial. Asian Pac J Cancer Prev. 2021;22:2977-85. \u003c/li\u003e\n\u003cli\u003eTakekuma M, Takahashi F, Mabuchi S, Kudaka W, Horie K, Ikeda M, et al. Propensity score-matched analysis of systemic chemotherapy versus salvage hysterectomy for persistent cervical cancer after definitive radiotherapy/concurrent chemoradiotherapy. BMC Cancer. 2020;20:1169. \u003c/li\u003e\n\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":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Locally advanced cervical cancer, Concurrent chemoradiotherapy, Residual disease, Magnetic resonance imaging, Diffusion-weighted imaging","lastPublishedDoi":"10.21203/rs.3.rs-5678120/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5678120/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo investigate the prognostic value of magnetic resonance imaging (MRI) and clinical features in locally advanced cervical cancer (LACC) after concurrent chemoradiotherapy (CCRT).\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e \u003cp\u003eThis study recruited 189 patients with LACC who received definitive CCRT between May 2018 and December 2020 and underwent MRI, including diffusion-weighted imaging, before and 1 month after initial therapy. The tumor size and mean apparent diffusion coefficient (ADC\u003csub\u003emean\u003c/sub\u003e) values were evaluated. A Cox proportional hazards model was used to determine the association of clinical characteristics and imaging factors with progression-free survival (PFS) and overall survival (OS) based on univariate and multivariate analysis.\u003c/p\u003e\u003ch2\u003eResult\u003c/h2\u003e \u003cp\u003eThe median follow-up time was 58 (range: 11\u0026ndash;71) months. The 5-year PFS and OS rates were 73.8% and 85.5%, respectively. Univariate analysis revealed that serum squamous cell carcinoma (SCC) antigen level, stage, Pre-treatment tumor size, residual disease (RD) and post-treament ADC\u003csub\u003emean\u003c/sub\u003e values were significant predictors of PFS and OS. Positive pelvic lymph node and adjuvant chemotherapy after CCRT were adverse predictors of PFS and OS, respectively. Multivariate analysis revealed that stage, SCC antigen level, and RD were independent predictors of PFS (hazard ratio [HR]\u0026thinsp;=\u0026thinsp;3.282, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; HR\u0026thinsp;=\u0026thinsp;2.567, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002; and HR\u0026thinsp;=\u0026thinsp;1.621, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, respectively) and OS (HR\u0026thinsp;=\u0026thinsp;2.517, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.043; HR\u0026thinsp;=\u0026thinsp;1.025, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.015; and HR\u0026thinsp;=\u0026thinsp;1.712, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008, respectively). Based on the threshold, RD size\u0026thinsp;\u0026ge;\u0026thinsp;1.1 cm resulted in a considerably worse PFS and OS.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eElevated SCC antigen level, advanced stage, and RD size\u0026thinsp;\u0026ge;\u0026thinsp;1.1 cm were linked to worse PFS and OS. Furthermore, the ADC\u003csub\u003emean\u003c/sub\u003e values was not a reliable predictor of survival outcomes.\u003c/p\u003e","manuscriptTitle":"Prognostic factors of locally advanced cervical cancer after concurrent chemoradiotherapy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-25 10:05:18","doi":"10.21203/rs.3.rs-5678120/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-02T10:55:07+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-01T16:34:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"116157425773013820117236654264839579529","date":"2025-03-27T18:51:15+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-27T07:10:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"114983292557662367067856965408781496605","date":"2025-03-26T15:10:44+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-24T06:29:56+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-19T11:56:40+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2025-03-18T17:55:02+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e2e298f3-6c21-4fab-8fef-b9f7a136e1c7","owner":[],"postedDate":"March 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-06T16:06:25+00:00","versionOfRecord":{"articleIdentity":"rs-5678120","link":"https://doi.org/10.1186/s12885-025-14691-y","journal":{"identity":"bmc-cancer","isVorOnly":false,"title":"BMC Cancer"},"publishedOn":"2025-10-02 15:57:02","publishedOnDateReadable":"October 2nd, 2025"},"versionCreatedAt":"2025-03-25 10:05:18","video":"","vorDoi":"10.1186/s12885-025-14691-y","vorDoiUrl":"https://doi.org/10.1186/s12885-025-14691-y","workflowStages":[]},"version":"v1","identity":"rs-5678120","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5678120","identity":"rs-5678120","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}