Locally Advanced Cervical Cancer Patients Research Articles

Predictive Value of Pre-treatment Hematological Parameters for Response to Definitive Chemoradiation in Locally Advanced Cervical Cancer: A Prospective Study

Background: More than 90% of cervical cancers are related to chronic inflammation caused by HPV. Several studies have shown that laboratory hematological parameters can detect the severity of systemic inflammation. Objectives: Our current cohort study investigated the predictive role of pretreatment hematological parameters for response to definitive chemoradiotherapy in patients with locally advanced cervical cancer (LACC). Methods: Prospectively, patients with LACC who candidates for definitive chemoradiation at Shohadaye Haftom-e-Tir are and Firozgar Hospitals (Tehran, Iran) were included in our study between April 2021 and December 2022. Hematological parameters were obtained from the blood sample test and peripheral blood smear before treatment. All patients diagnosed in stage IB to IVA received a similar treatment protocol and follow-up. Patients were divided into complete clinical (CR) and non-complete clinical responses (Non-CR). Leukocyte, Lymphocyte, neutrophil, platelet, hemoglobin (Hb), platelet-to-lymphocyte ratio (PLR), and neutrophil-to-lymphocyte ratio (NLR), were documented and then compared between two groups of responders. We used receiver operating characteristic (ROC) analysis to investigate the predictive value of these hematological parameters. Results: Out of 34 patients who met the inclusion criteria, 25 (73/5%) patients were complete responders and 9 (26.5%) were non-complete responders. The average number of neutrophils, leukocytes, and NLR was significantly higher among Non-complete responders. Hemoglobin in patients with non-complete responses was significantly lower than that of the other group of responders. Receiver operating characteristic curve analysis showed that the optimized cut-off values for pretreatment Hb and NLR were 11 and 2.1, respectively. Neutrophil-to-lymphocyte ratio cut-off point > 2.1 is significantly associated with larger tumor size, low Hb, high platelet, and high leukocyte. Conclusions: hematological markers such as NLR can be a simple and inexpensive predictive factor to evaluate therapeutic response to chemoradiation in LACC patients.

Prognostic prediction of oxidative stress related hematological biomarkers in locally advanced cervical cancer patients undergoing chemoradiotherapy

Objective This investigation aimed to develop and validate a novel oxidative stress score for prognostic prediction in locally advanced cervical cancer (LACC) patients receiving chemoradiotherapy. Methods A total of 301 LACC patients were enrolled and randomly divided into a training and a validation set. The association between oxidative stress parameters and prognosis was analyzed for oxidative stress score (OSS) establishment. A Cox regression model was conducted for overall survival (OS) and progression-free survival (PFS). A nomogram prediction model was developed using independent prognostic factors from the training set and validated in the validation set. Results A novel OSS was established with four oxidative stress parameters, including albumin, total bilirubin, blood urea nitrogen, and lactate dehydrogenase. Multivariate regression analysis identified OSS as an independent prognostic factor for OS (P = 0.001) and PFS (P < 0.001). A predictive nomogram based on the OSS was established and validated. The C-indexes of the nomogram in the training set were 0.772 for OS and 0.781 for PFS, while in the validation set the C-indexes were 0.642 for OS and 0.621 for PFS. Conclusion This study confirmed that preoperative OSS could serve as a useful independent prognostic factor in LACC patients who received CCRT.

Efficacy and safety of different chemotherapy regimens concurrent with radiotherapy in the treatment of locally advanced cervical cancer

BackgroundEvaluate the efficacy and safety of different chemotherapy regimens concurrent with radiotherapy in treating locally advanced cervical cancer (LACC).MethodsRetrospective data was collected from LACC patients who were treated at our institution. These patients were categorized into three groups: the single-agent cisplatin (DDP) chemoradiotherapy group, the paclitaxel plus cisplatin (TP) chemoradiotherapy group, and the nanoparticle albumin-bound (nab-) paclitaxel combined with cisplatin (nPP) chemoradiotherapy group. The primary endpoints were overall survival (OS) and progression-free survival (PFS) and the secondary endpoints were objective response rate (ORR) and incidence of adverse events (AEs).ResultsA total of 124 patients were enrolled (32 in the DDP group, 41 in the TP group, and 51 in the nPP group). There were differences in OS (P = 0.041, HR 0.527, 95% CI 0.314–0.884) and PFS (P = 0.003, HR 0.517, 95% CI 0.343–0.779) between the three groups. Notably, the 2-year OS rate was significantly higher in the nPP group compared to the DDP group (92.2% vs. 85.4%, P = 0.012). The 2-year PFS rates showed a marked increase in the TP group (78.0% vs. 59.4%, P = 0.048) and the nPP group (88.2% vs. 59.4%, P = 0.001) relative to the DPP group, with multiple comparisons indicating that the 2-year PFS rate was significantly superior in the nPP group versus the DDP group (88.2% vs. 59.4%, P = 0.001). Moreover, the ORR was also significantly higher in the nPP group than in the DDP group (P = 0.013); and no statistically significant differences were found in the incidence of AEs among the groups (P > 0.05).ConclusionsIn LACC treatment, the two cisplatin-based doublet chemotherapy regimens are associated with better outcomes, with the nab-paclitaxel plus cisplatin regimen showing better efficacy than the paclitaxel plus cisplatin regimen. Furthermore, the AEs associated with these regimens were deemed tolerable. These findings could provide a reference for the clinical treatment of LACC. However, further prospective studies are needed to verify it.

MRI-guided dynamic risk assessment in cervical cancer based on tumor hypoxia at diagnosis and volume response at brachytherapy

Background and purposeImprovements in treatment outcome for patients with locally advanced cervical cancer (LACC) require a better classification of patients according to their risk of recurrence. We investigated whether an imaging-based approach, combining pretreatment hypoxia and tumor response during therapy, could improve risk classification. Material and methodsNinety-three LACC patients with T2-weigthed (T2W)-, dynamic contrast enhanced (DCE)- and diffusion weighted (DW)-magnetic resonance (MR) images acquired before treatment, and T2W- and, for 64 patients, DW-MR images, acquired at brachytherapy, were collected. Pretreatment hypoxic fraction (HFpre) was determined from DCE- and DW-MR images using the consumption and supply-based hypoxia (CSH)-imaging method. Volume regression at brachytherapy was assessed from T2W-MR images and combined with HFpre. In 17 patients with adequate DW-MR images at brachytherapy, the apparent diffusion coefficient (ADC), reflecting tumor cell density, was calculated. Change in ADC during therapy was combined with volume regression yielding functional regression as explorative response measure. Endpoint was disease free survival (DFS). ResultsHFpre was the strongest predictor of DFS, but a significant correlation with outcome was found also for volume regression. The combination of HFpre and volume regression showed a stronger association with DFS than HFpre alone. Patients with disease recurrence were selected to either the intermediate- or high-risk group with a 100 % accuracy. Functional regression showed a stronger correlation to HFpre than volume regression. ConclusionThe combination of pretreatment hypoxia and volume regression at brachytherapy improved patient risk classification. Integration of ADC with volume regression showed promise as a new tumor response parameter.

A randomized trial evaluating a novel hydrogel packing system compared to standard packing during image-guided high-dose rate brachytherapy boost for cervical cancer

INTRODUCTIONThe purpose of this prospective randomized trial was to compare the use of a novel vaginal hydrogel packing system (BrachyGel) to standard vaginal packing (VP) during high dose rate (HDR) brachytherapy (BT) for locally advanced cervical cancer (LACC). METHODSThis cross-over study included LACC patients receiving HDR BT boost (intracavitary +/- interstitial). All patients received alternating gauze or BrachyGel VP on Arms A and B. Patients, physicians, and physicists evaluated BT characteristics via a 4-point Likert scale. Adverse events (AEs) were prospectively collected and scored per CTCAE. RESULTSThe 20 patients enrolled. The mean bladder D2cc difference between gauze and BrachyGel in Arm A was 0.117 Gray (Gy) and in Arm B 0.013 Gy. The mean difference in rectum D2cc in Arm A and Arm B was -0.189 Gy and -0.191 Gy, respectively. The mean dose to 90% of the high-risk clinical target volume (HR-CTV) for gauze compared to BrachyGel was -0.032 Gy (95% CI: 0.472, 0.409). Patient-reported discomfort was similar with BrachyGel and gauze (“mild/moderate” 70.0% vs 74.0%, respectively). The clarity of VP was similar between BrachyGel and gauze (86.8% vs 89.7%, respectively). The completeness of VP was more frequently “excellent/good” with BrachyGel (79.0%) compared to gauze (56.4%). The ease of packing was more frequently “extremely easy” with BrachyGel (21.2% vs 0%). No serious AEs were reported. CONCLUSIONThis randomized trial found no clinically significant difference in OAR or HR-CTV dosimetry between BrachyGel and standard VP. BrachyGel performed well compared to gauze for the patient and physician use experience.

Dosimetric impact of bone marrow sparing for robustly optimized IMPT for locally advanced cervical cancer

Background and purposeTo investigate the trade-off between bone marrow sparing (BMS) and dose to organs at risk (OARs) for intensity modulated proton therapy (IMPT) for women with locally advanced cervical cancer (LACC). Materials and methodsTwenty LACC patients were retrospectively included. IMPT plans were created for each patient using automated treatment planning. These plans progressively reduced bone marrow mean doses by steps of 1 GyRBE, while constraining target coverage and conformality. The relation between bone marrow dose and bladder, small bowel, rectum, and sigmoid doses was evaluated. ResultsA total of 140 IMPT plans were created. Plans without BMS had an average [range] bone marrow mean dose of 17.3 [14.7–21.6] GyRBE , which reduced to 12.0 [10.0–14.0] GyRBE with maximum BMS. The mean OAR dose [range] increased modestly for 1 GyRBE BMS: 0.2 [0.0 – 0.6] GyRBE for bladder, 0.3 [-0.2 – 0.7] GyRBE for rectum, 0.4 [0.1 – 0.8] GyRBE for small bowel, and 0.2 [-0.2 – 0.4] GyRBE for sigmoid. Moreover, for maximum BMS, mean OAR doses [range] escalated by 3.3 [0.1 – 6.7] GyRBE for bladder, 5.8 [1.8 – 12.4] GyRBE for rectum, 3.9 [1.6 – 5.9] GyRBE for small bowel, and 2.7 [0.6 – 5.9] GyRBE for sigmoid. ConclusionAchieving 1 GyRBE BMS for IMPT is feasible for LACC patients with limited dosimetric impact on other OARs. While further bone marrow dose reduction is possible for some patients, it may increase OAR doses substantially for others. Hence, we recommend a personalized approach when introducing BMS into clinical IMPT treatment planning to carefully assess individual patient benefits and risks.

Nomograms for predicting prognostic value of combined neutrophil-to-lymphocyte ratio and SCC-Ag in locally advanced cervical cancer.

Accumulating evidence supports the important role of inflammation in tumorigenesis and progression. Squamous cell carcinoma-associated antigen (SCC-Ag) is a tumor marker widely used to predict the prognosis of patients with cervical squamous cell carcinoma. This paper explored the predictive value of combined detection of neutrophil-to-lymphocyte ratio (NLR) to SCC-Ag for prognosis in patients with locally advanced cervical cancer (LACC). A retrospective analysis was conducted on 190 LACC patients who underwent concurrent chemoradiotherapy (CCRT) from January 2012 to December 2016. NLR and SCC-Ag were analyzed before treatment. Receiver operating characteristic (ROC) curve analysis was employed to determine the optimal cutoff point for NLR and SCC-Ag. Kaplan-Meier analysis and Cox regression analysis were performed to assess their prognostic values. Nomograms were established to predict progression-free survival (PFS) and overall survival (OS), and the Harrell's concordance index (C-index) was introduced to evaluate the accuracy of predictions. The optimal cutoff values for SCC-Ag and NLR were 3.25 ng/mL and 2.52, respectively. Patients with SCC-Ag >3.25 ng/mL and NLR >2.52 were significantly associated with decreased PFS and OS. Multivariate analysis indicated that SCC-Ag and NLR were independent prognostic factors for PFS (P=0.022 and P=0.004, respectively) and OS (P=0.031 and P=0.001, respectively). The area under the curve of SCC-Ag, NLR and their combination to predict PFS and OS of LACC were 0.688, 0.623, 0.708 and 0.684, 0.658, 0.723, respectively. C-index of nomograms based on PFS and OS were 0.725 [95% confidence interval (CI): 0.653-0.797] and 0.731 (95% CI: 0.658-0.804), respectively. The combination of SCC-Ag and NLR could provide a better predictive prognosis than SCC-Ag or NLR alone, and nomograms based on PFS and OS can be recommended as practical models for evaluating the prognosis of LACC patients.

Development and validation of a 18F-FDG PET/CT radiomics nomogram for predicting progression free survival in locally advanced cervical cancer: a retrospective multicenter study

BackgroundThe existing staging system cannot meet the needs of accurate survival prediction. Accurate survival prediction for locally advanced cervical cancer (LACC) patients who have undergone concurrent radiochemotherapy (CCRT) can improve their treatment management. Thus, this present study aimed to develop and validate radiomics models based on pretreatment 18Fluorine-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)-computed tomography (CT) images to accurately predict the prognosis in patients.MethodsThe data from 190 consecutive patients with LACC who underwent pretreatment 18F-FDG PET-CT and CCRT at two cancer hospitals were retrospectively analyzed; 176 patients from the same hospital were randomly divided into training (n = 117) and internal validation (n = 50) cohorts. Clinical features were selected from the training cohort using univariate and multivariate Cox proportional hazards models; radiomic features were extracted from PET and CT images and filtered using least absolute shrinkage and selection operator and Cox proportional hazard regression. Three prediction models and a nomogram were then constructed using the previously selected clinical, CT and PET radiomics features. The external validation cohort that was used to validate the models included 23 patients with LACC from another cancer hospital. The predictive performance of the constructed models was evaluated using receiver operator characteristic curves, Kaplan Meier curves, and a nomogram.ResultsIn total, one clinical, one PET radiomics, and three CT radiomics features were significantly associated with progression-free survival in the training cohort. Across all three cohorts, the combined model displayed better efficacy and clinical utility than any of these parameters alone in predicting 3-year progression-free survival (area under curve: 0.661, 0.718, and 0.775; C-index: 0.698, 0.724, and 0.705, respectively) and 5-year progression-free survival (area under curve: 0.661, 0.711, and 0.767; C-index, 0.698, 0.722, and 0.676, respectively). On subsequent construction of a nomogram, the calibration curve demonstrated good agreement between actually observed and nomogram-predicted values.ConclusionsIn this study, a clinico-radiomics prediction model was developed and successfully validated using an independent external validation cohort. The nomogram incorporating radiomics and clinical features could be a useful clinical tool for the early and accurate assessment of long-term prognosis in patients with LACC patients who undergo concurrent chemoradiotherapy.

Comparing deep learning and handcrafted radiomics to predict chemoradiotherapy response for locally advanced cervical cancer using pretreatment MRI

Concurrent chemoradiotherapy (CRT) is the standard treatment for locally advanced cervical cancer (LACC), but its responsiveness varies among patients. A reliable tool for predicting CRT responses is necessary for personalized cancer treatment. In this study, we constructed prediction models using handcrafted radiomics (HCR) and deep learning radiomics (DLR) based on pretreatment MRI data to predict CRT response in LACC. Furthermore, we investigated the potential improvement in prediction performance by incorporating clinical factors. A total of 252 LACC patients undergoing curative chemoradiotherapy are included. The patients are randomly divided into two independent groups for the training (167 patients) and test datasets (85 patients). Contrast-enhanced T1- and T2-weighted MR scans are obtained. For HCR analysis, 1890 imaging features are extracted and a support vector machine classifier with a five-fold cross-validation is trained on training dataset to predict CRT response and subsequently validated on test dataset. For DLR analysis, a 3-dimensional convolutional neural network was trained on training dataset and validated on test dataset. In conclusion, both HCR and DLR models could predict CRT responses in patients with LACC. The integration of clinical factors into radiomics prediction models tended to improve performance in HCR analysis. Our findings may contribute to the development of personalized treatment strategies for LACC patients.

Information needs during cancer care: Qualitative research with locally advanced cervical cancer patients in Brazil, China, Germany, & the US

ObjectiveThis study aimed to identify the information needs and factors for making informed treatment decisions among a diverse group of locally advanced cervical cancer (LACC) patients. MethodsSemi-structured interviews were conducted with LACC patients of diverse demographic and socioeconomic backgrounds within two years of their cancer diagnosis. Trained moderators asked open-ended questions about patients’ cancer journeys. Transcripts were analyzed using NVivo software to identify emergent themes. ResultsIn 2022, 92 LACC patients in the United States (n = 26), Brazil (n = 25), China (n = 25), and Germany (n = 16) participated in the study. Physicians were valued sources of information, providing patients with details on prognosis, treatment options, and side effects. While most patients trusted their physicians, one-third sought a second opinion to validate their diagnosis or find a more trusted physician.Most patients conducted their own research on treatment options, side effects, causes of LACC, symptoms, and others’ experiences. Challenges to information searches included understanding medical terms, finding relevant information, and evaluating source credibility.Overall, patients felt knowledgeable enough to participate in treatment decisions, either by accepting the recommended treatment or collaborating with their physicians. Nearly one-third of patients desired a more significant role in the decision-making process. ConclusionThis study highlights the importance of physicians providing LACC patients comprehensive and understandable information, while involving them in the decision-making process. Understanding LACC patients’ motivations to seek information and their willingness to actively engage in treatment decisions can lead to improved patient satisfaction in their cancer care.

Automated Prediction of Neoadjuvant Chemoradiotherapy Response in Locally Advanced Cervical Cancer Using Hybrid Model-Based MRI Radiomics.

This study aimed to develop a model that automatically predicts the neoadjuvant chemoradiotherapy (nCRT) response for patients with locally advanced cervical cancer (LACC) based on T2-weighted MR images and clinical parameters. A total of 138 patients were enrolled, and T2-weighted MR images and clinical information of the patients before treatment were collected. Clinical information included age, stage, pathological type, squamous cell carcinoma (SCC) level, and lymph node status. A hybrid model extracted the domain-specific features from the computational radiomics system, the abstract features from the deep learning network, and the clinical parameters. Then, it employed an ensemble learning classifier weighted by logistic regression (LR) classifier, support vector machine (SVM) classifier, K-Nearest Neighbor (KNN) classifier, and Bayesian classifier to predict the pathologic complete response (pCR). The area under the receiver operating characteristics curve (AUC), accuracy (ACC), true positive rate (TPR), true negative rate (TNR), and precision were used as evaluation metrics. Among the 138 LACC patients, 74 were in the pCR group, and 64 were in the non-pCR group. There was no significant difference between the two cohorts in terms of tumor diameter (p = 0.787), lymph node (p = 0.068), and stage before radiotherapy (p = 0.846), respectively. The 109-dimension domain features and 1472-dimension abstract features from MRI images were used to form a hybrid model. The average AUC, ACC, TPR, TNR, and precision of the proposed hybrid model were about 0.80, 0.71, 0.75, 0.66, and 0.71, while the AUC values of using clinical parameters, domain-specific features, and abstract features alone were 0.61, 0.67 and 0.76, respectively. The AUC value of the model without an ensemble learning classifier was 0.76. The proposed hybrid model can predict the radiotherapy response of patients with LACC, which might help radiation oncologists create personalized treatment plans for patients.

Urinary, Gastrointestinal, and Sexual Dysfunctions after Chemotherapy, Radiotherapy, Radical Surgery or Multimodal Treatment in Women with Locally Advanced Cervical Cancer: A Multicenter Retrospective Study.

Different strategies have been proposed for the treatment of locally advanced cervical cancer (LACC), with different impacts on patient's quality of life (QoL). This study aimed to analyze urinary, bowel, and sexual dysfunctions in a series of LACC patients who underwent chemotherapy, radiotherapy, radical surgery, or a combination of these treatments. Patients with LACC who underwent neoadjuvant radio-chemotherapy (NART/CT; n = 35), neoadjuvant chemotherapy (NACT; n = 17), exclusive radio-chemotherapy (ERT/CT; n = 28), or upfront surgery (UPS; n = 10) from November 2010 to September 2019 were identified from five oncological referral centers. A customized questionnaire was used for the valuation of urinary, gastrointestinal, and sexual dysfunctions. A total of 90 patients were included. Increased urinary frequency (>8 times/day) was higher in ERT/CT compared with NACT/RT (57.1% vs. 28.6%; p = 0.02) and NACT (57.1% vs. 17.6%; p = 0.01). The use of sanitary pads for urinary leakage was higher in ERT/CT compared with NACT/RT (42.9% vs. 14.3%; p = 0.01) and NACT (42.9% vs. 11.8%; p = 0.03). The rate of reduced evacuations (<3 times a week) was less in UPS compared with NACT/RT (50% vs. 97.1%; p < 0.01), NACT (50% vs. 88.2, p < 0.01), and ERT/CT (50% vs. 96.4%; p < 0.01). A total of 52 women were not sexually active after therapy, and pain was the principal reason for the avoidance of sexual activity. The rate and severity of urinary, gastrointestinal, and sexual dysfunction were similar in the four groups of treatment. Nevertheless, ERT/CT was associated with worse sexual and urinary outcomes.

Dosimetric comparison of stereotactic MR-guided radiation therapy (SMART) and HDR brachytherapy boost in cervical cancer

The standard of care in locally advanced cervical cancer (LACC) is concomitant chemoradiotherapy followed by high-dose-rate brachytherapy (HDR-BT). Although previous studies compared HDR-BT with stereotactic body radiotherapy (SBRT), there is scarce data regarding the dosimetric outcomes of stereotactic MR-guided adaptive radiation therapy (SMART) boost in lieu of HDR-BT. In this single-institutional in-silico comparative study, LACC patients who were definitively treated with external beam radiotherapy followed by HDR-BT were selected. Target volumes and organs at risk (OARs) were delineated in MRI and HDR-planning CT. An HDR-BT and a SMART boost plan were generated with a prescribed dose of 28 Gy in four fractions for all patients. The HDR-BT and SMART boost plans were compared in regard to target coverage as well OARs doses. Mean EQD2 D90 to HR-CTV and IR-CTV for HDR-BT plans were 89.7 and 70.5 Gy, respectively. For SMART, the mean EQD2 D90 to HR-PTV, HR-CTV, and IR-CTV were 82.9, 95.4, and 70.2 Gy, respectively. The mean D2cc EQD2 of bladder, rectum, and sigmoid colon for HDR-BT plans were 86.4, 70.7, and 65.7 Gy, respectively. The mean D2cc EQD2 of bladder, rectum, and sigmoid colon for SMART plans were 81.4, 70.8, and 73.6 Gy, respectively. All dose constraints in terms of target coverage and OARs constraints were met for both HDR-BT and SMART plans. This dosimetric study demonstrates that SMART can be applied in cases where HDR-BT is not available or ineligible with acceptable target coverage and OAR sparing. However, prospective clinical studies are needed to validate these results.

Prognostic Value of Body Composition and Systemic Inflammatory Markers in Patients with Locally Advanced Cervical Cancer Following Chemoradiotherapy.

Abnormal changes in body composition and systemic inflammation response have been associated with poor survival of cancer patients. Our study was to explore the prognostic value of the association between body composition indicators and systemic inflammation markers among patients with locally advanced cervical cancer (LACC) who underwent concurrent chemoradiotherapy (CCRT). We retrospectively reviewed medical records of LACC patients treated between 2016 and 2019. Subcutaneous, visceral and intra-muscular adipose index (SAI, VAI and IMAI) and skeletal muscle index (SMI) were derived from computed tomography (CT). Kaplan-Meier analysis and Univariate and multivariate Cox analyses were used to evaluate the survival. A nomogram was constructed to assess the prognostic value. The study included 196 patients treated with CCRT. According to multivariable Cox analyses, IIIC1r (P = 0.045), high systemic immune-inflammation index (SII) (P = 0.004), sarcopenia (P = 0.008), high SAI (P = 0.016) and high VAI (P = 0.001) were significantly risk factors for overall survival (OS). Kaplan-Meier analysis showed that patients with low lymphocyte-to-monocyte ratio (LMR) and sarcopenia had longer OS than those with high LMR and sarcopenia (P = 0.023). The high neutrophil-to-lymphocyte ratio (NLR) in non-sarcopenic patients showed better survival (P = 0.022). Low VAI (P = 0.019) or low IMAI (P = 0.019) combined with low SII had a favorable OS. Low LMR combined with low SAI was associated with longer OS (P = 0.022). The calibration plots of nomogram predicting the 3-year and 5-year OS rates were close to the ideal models. Inflammation factors were closely associated with abnormal muscle and fat distribution. The combined prognostic value of body composition indicators and systemic inflammation markers was reliable in predicting survival for LACC patients.

Co-occurrence of symptoms after radiochemotherapy in locally advanced cervix cancer patients: a cluster analysis

Background State of the art combined radiochemotherapy and image-guided brachytherapy for locally advanced cervical cancer (LACC) has shown improved disease control and survival as well as a significant reduction of organ related morbidity. However, LACC cancer survivors are still experiencing a spectrum of symptoms. The aim of this study was to identify co-occurring symptoms in cervix cancer survivors by using patient-reported outcome and physician assessed morbidity. Materials and method EMBRACE I is a multicenter prospective observational study with 1416 LACC patients (2008–2015). Information on physician-assessed morbidity and patient-reported outcome was assessed at baseline and at regular follow-ups up with the CTCAE v.3 and EORTC-C30/CX24, respectively. Patients with at least 2 years of follow-up were included and data from 3 months to 2 years was used in the analysis. Factor analysis was used on both EORTC and CTCAE data with symptoms and follow-ups as observations. The extracted factors represent clusters of symptoms. Subsequently, regression models were built to investigate associations between the symptom clusters and QOL. Results The analysis included 742 patients. Despite the differences in the definition of physician-assessed and patient-reported symptoms, similar clusters are identified by the two assessment methods. Three main organ-related clusters are recognized for urinary, gastro-intestinal and vaginal morbidity. Furthermore, a general symptoms cluster where fatigue, pain, insomnia, neuropathy, and hot flashes have large weights is found. Lastly, a cluster with nausea, vomit and lack of appetite is also identified. The general, gastrointestinal and nausea clusters show significant associations with general QOL. Conclusions This analysis on both PRO and physician-assessed morbidity found a cluster associated with general symptoms and organ-related symptom clusters (urinary, gastrointestinal, vaginal). This shows that LACC survivors experience a variety of co-occurring symptoms. Our analysis also shows that the cluster of general symptoms is associated with a decrease in QOL.

Decoding the Complexity of Systemic Inflammation Predictors in Locally Advanced Cervical Cancer, with Hemoglobin as the Hidden Key (the ESTHER Study).

Locally advanced cervical cancer (LACC) is treated with concurrent chemoradiation (CRT). Predictive models could improve the outcome through treatment personalization. Several factors influence prognosis in LACC, but the role of systemic inflammation indices (IIs) is unclear. This study aims to assess the correlation between IIs and prognosis in a large patient cohort considering several clinical data. We retrospectively analyzed pretreatment IIs (NLR, PLR, MLR, SII, LLR, COP-NLR, APRI, ALRI, SIRI, and ANRI) in 173 LACC patients. Patient, tumor, and treatment characteristics were also considered. Univariate and multivariate Cox's regressions were conducted to assess associations between IIs and clinical factors with local control (LC), distant metastasis-free survival (DMFS), disease-free survival (DFS), and overall survival (OS). Univariate analysis showed significant correlations between age, HB levels, tumor stage, FIGO stage, and CRT dose with survival outcomes. Specific pretreatment IIs (NLR, PLR, APRI, ANRI, and COP-NLR) demonstrated associations only with LC. The multivariate analysis confirmed Hb levels, CRT dose, and age as significant predictors of OS, while no II was correlated with any clinical outcome. The study findings contradict some prior research on IIs in LACC, emphasizing the need for comprehensive assessments of potential confounding variables.

Development of a Radiomic Signature from Pre-Treatment FDG-PET for Recurrence Prediction in Cervical Cancer.

As many as 30-50% of patients with locally advanced cervical cancer (LACC) experience recurrence after standard-of-care chemoradiation therapy (CRT), creating a critical need to identify pre-treatment biomarkers of treatment failure. The purpose of this study is to identify whether radiomic features derived from pre-treatment FDG-PET imaging can be used to construct a predictive signature useful for assessing risk of recurrence during treatment planning. Standardized uptake values (SUV) were obtained from within the physician-defined metabolic tumor volumes (MTV) delineated on FDG-PET scans acquired for 90 LACC patients at our institution prior to standard of care curative-intent CRT. Clinical outcome data of these patients has a median follow-up time of 85 months. The clinical endpoint was local recurrence within 3 years of treatment. 851 quantitative radiomic features describing intensity, shape, texture and high and low frequency spatial filters of the MTV were extracted for each patient. Low information features, defined by pairwise correlation > 0.85 with another feature or a maximum deviation within 20% of the mean, were discarded, leaving 146 features. Predictive signatures were constructed from features using multiple techniques, including multivariate Cox modelling, a set of machine learning models (random forest (RF), support vector classifier (SVC), ridge regression, LASSO regression, and elastic net regression), and a deep neural network (DNN) classifier. The DNN classifier had the best overall performance, predicting a patient's recurrence group with an F1 score of 0.917 ± 0.028 under 5-fold cross-validation. By contrast, the Cox model classifier yielded an F1 score of 0.604 ± 0.085 and the best performing of the alternative machine learning models, elastic net, yielded F1 score of 0.868 ± 0.018. A set of textural features contributed the most to the output of the DNN classifier, including Large Area Low Gray Level Emphasis of the gray level size zone matrix (GLSZM) and coarseness and busyness of the neighboring gray tone difference matrix (NGTDM), reflecting the important role patterns of tumor heterogeneity play in post-treatment recurrence. In this pilot study, we investigated multiple techniques to construct predictive radiomic signatures for local recurrence in LACC, determining that a DNN classifier is most capable of stratifying patients by risk of early recurrence. Future work will seek to validate this result on additional PET imaging data sets and to integrate radiomic features with gene expression data from matched tumor samples to establish radiogenomic biomarkers for recurrence.

Prognostic Value of Tumor Volume Reduction during Radiotherapy in Patients with Locally Advanced Cervical Cancer in Different Risk Groups

To evaluate the risk factors of patients with locally advanced cervical cancer (LACC) undergoing radical radiotherapy (with or without concurrent chemotherapy) and to assess the prognostic value of tumor volume regression (TVR) based on magnetic resonance imaging (MRI) in different risk groups. A retrospective analysis was performed on 176 individuals diagnosed with stage IIA-IVA cervical cancer (CC) who underwent radical intensity-modulated radiotherapy in our center between January 2012 and December 2020. The tumor volume before radiotherapy (TVp) and before brachytherapy (TVmid) were evaluated based on three-dimensional MRI images, TVR = (TVp -TVmid)/TVp × 100%. Kaplan-Meier curves were used to assess patient's overall survival (OS) and progression-free survival (PFS). Prognostic factors were identified using Cox proportional hazards models. For the entire cohort, patients with TVR ≥ 94% had better 5-year OS (82.7% vs 49.8%, p<0.001) and 5-year PFS (82.5% vs 51.1%, p<0.001) compared to TVR < 94%. Patients with TVR ≥ 94% were more likely to receive concurrent chemoradiotherapy (CCRT) than those with TVR < 94% (70.1% vs 40.5%, p<0.05). Among patients undergoing CCRT, those with a TVR ≥ 94% had a better prognosis than those with a TVR < 94%. However, among patients who received RT alone, those with TVR ≥ 94% had better PFS but no statistically significant difference in OS. Likewise, among patients with CYFRA21-1 < 7.7 ng/ml, patients with TVR ≥ 94% had a better prognosis. However, TVR was not a prognostic factor in patients with CYFRA21-1 ≥ 7.7 ng/ml. Both CYFRA21-1 (OS, PFS interaction, p<0.001) and FIGO stage (PFS interaction, p = 0.035) were found to significantly impact predictive effects of TVR. In LACC patients with CRYFA21-1 < 7.7 ng/ml who received CCRT, TVR was an important prognostic factor. However, in patients with CRYFA21-1 ≥ 7.7 ng/ml who received RT alone, the prognostic value of TVR needs to be further explored.

Optimal Cisplatin Cycles in Locally Advanced Cervical Carcinoma Patients Treated with Concurrent Chemoradiotherapy

To analyze the effect of cisplatin cycles on the clinical outcomes of patients with locally advanced cervical cancer (LACC) treated with concurrent chemoradiotherapy (CCRT). This study included 749 patients with LACC treated with CCRT between January 2011 and December 2015. A receiver operating characteristic (ROC) curve was used to analyze the optimal cut-off of cisplatin cycles in predicting clinical outcomes. Clinicopathological features of the patients were compared using the Chi-square test. Prognosis was assessed using log-rank tests and Cox proportional hazard models. Toxicities were compared among different cisplatin cycle groups. Based on the ROC curve, the optimal cut-off of the cisplatin cycles was 4.5 (sensitivity, 64.3%; specificity, 54.3%). The 3-year overall, disease-free, loco-regional relapse-free, and distant metastasis-free survival for patients with low-cycles (cisplatin cycles < 5) and high-cycles (≥ 5) were 81.5% and 89.0% (P < 0.001), 73.4% and 80.1% (P = 0.024), 83.0% and 90.8% (P = 0.005), and 84.9% and 86.8% (P = 0.271), respectively. In multivariate analysis, cisplatin cycles were an independent prognostic factor for overall survival. In the subgroup analysis of high-cycle patients, patients who received over five cisplatin cycles had similar overall, disease-free, loco-regional relapse-free, and distant metastasis-free survival to patients treated with five cycles. Acute and late toxicities were not different between the two groups. Cisplatin cycles were associated with overall, disease-free, and loco-regional relapse-free survival in LACC patients who received CCRT. Five cycles appeared to be the optimal number of cisplatin cycles during CCRT.

Patient-Reported Distress and Acute Care Utilization for Cervical Cancer Patients Undergoing Concurrent Chemoradiation

Although concurrent chemo-radiation (CRT) and brachytherapy (BT) is curative for locally advanced cervical cancer (LACC), it requires complex coordination of care and is associated with treatment-related toxicity. Our objective was to evaluate patient-reported symptoms and social distress in LACC patients undergoing concurrent CRT and BT to determine whether they are predictive of unplanned acute care utilization. Patients with LACC treated with concurrent CRT and BT between 2013-2020 completed the Edmonton Symptom Assessment Scale-revised (ESAS-r; 9 cancer-related symptoms ranked 0-10) and the Social Difficulties Inventory-21 (SDI-21; 21 social issues ranked 0-3) at every visit as part of routine distress screening. Acute care utilization was defined as any unplanned visit to the radiation nursing clinic, urgent care clinic, emergency department or hospitalization within 1 year from starting treatment. A logistic regression model will be used to evaluate associations between ESAS-r and SDI-21 scores and acute care utilization. Among 151 LACC patients, a total of 354 ESAS-r and SDI questionnaires were completed longitudinally. Mean age at diagnosis was 49.9 years (30-90), 44% were FIGO 2B and overall treatment time was 53.6 days (32-135). At baseline, the most prevalent moderate to severe symptoms (ESAS-r score ≥4) were well-being (50%), anxiety (44%), tiredness (43%) and pain (36%). Post-treatment, these persisted in 42%, 27%, 38%, and 26%, respectively. The most common social distress at baseline was financial (33%). Financial distress post-treatment was significantly predictive of worse well-being (OR = 5.80, p<0.06), anxiety (OR = 3.33, p<0.04) and depression (OR = 4.76, p<0.01). Use of acute care within 1 year after starting treatment occurred in 103 patients (68%) for a total of 617 visits: radiation nursing clinic 71.3%, urgent care clinic 4.4%, emergency department 8.3%, hospitalization 16%. On average there were 6.6 visits/patient (0-31), with the average number of days between treatment start and first acute care visit being 17.9 (0-74). Cervical cancer patients undergoing concurrent CRT report prevalent financial distress and moderate to severe symptoms that persist post-treatment. Acute care utilization commonly occurred during treatment, highlighting a time when additional support is needed. Predictive modelling for distress factors resulting in acute care utilization is now underway.