Nomogram using intratumoral and peritumoral radiomics for the preoperative prediction of visceral pleural invasion in clinical stage IA lung adenocarcinoma.

BACKGROUND: Accurate prediction of visceral pleural invasion (VPI) in lung adenocarcinoma before operation can provide guidance and help for surgical operation and postoperative treatment. We investigate the value of intratumoral and peritumoral radiomics nomograms for preoperatively predicting the status of VPI in patients diagnosed with clinical stage IA lung adenocarcinoma. METHODS: A total of 404 patients from our hospital were randomly assigned to a training set (n = 283) and an internal validation set (n = 121) using a 7:3 ratio, while 81 patients from two other hospitals constituted the external validation set. We extracted 1218 CT-based radiomics features from the gross tumor volume (GTV) as well as the gross peritumoral tumor volume (GPTV5, 10, 15), respectively, and constructed radiomic models. Additionally, we developed a nomogram based on relevant CT features and the radscore derived from the optimal radiomics model. RESULTS: The GPTV10 radiomics model exhibited superior predictive performance compared to GTV, GPTV5, and GPTV15, with area under the curve (AUC) values of 0.855, 0.842, and 0.842 in the three respective sets. In the clinical model, the solid component size, pleural indentation, solid attachment, and vascular convergence sign were identified as independent risk factors among the CT features. The predictive performance of the nomogram, which incorporated relevant CT features and the GPTV10-radscore, outperformed both the radiomics model and clinical model alone, with AUC values of 0.894, 0.828, and 0.876 in the three respective sets. CONCLUSIONS: The nomogram, integrating radiomics features and CT morphological features, exhibits good performance in predicting VPI status in lung adenocarcinoma.

Clinicopathological Features and Outcomes of Endometrial Cancer: A single institution experience.

Objectives: This study aimed to report the demographic features, clinical presentation, pathological types and long-term outcomes of patients diagnosed with endometrial cancer (EC) in Oman. EC is the sixth most common cancer in women worldwide and the fifth most common cancer in women in Oman. Survival outcomes of EC have not been reported previously from Oman. Methods: This retrospective study was carried out on consecutive patients treated at the Sultan Qaboos University Hospital, Muscat, Oman, between 2008 and 2020. Survival was estimated using the Kaplan and Meier method. Results: A total of 50 patients with EC were included. The median age was 61 years (range: 31-86 years), and 72% of the patients had type I histology. Most patients were diagnosed with stage IA and IB EC (49% and 20%, respectively), and the majority had grade 1 or 2 tumours (40% and 34%, respectively). Overall, the 5-year survival and 10-year survival rates were estimated to be 70% and 56%, respectively. Weight (>75 kg) and body mass index (>30 kg/m2) were significantly associated with better survival. Tumour histology (type I versus type II or carcinosarcoma), grade (1 versus 2 versus 3) and stage (IA or IB versus II-IV) were associated with better overall survival (P = 0.007, P <0.0001 and P <0.0003, respectively). Patients diagnosed with EC with co-morbidities, other than obesity, had inferior survival compared to those without co-morbidities. Conclusion: Median age at presentation, histological sub-type, clinical stage and outcomes are comparable to the published literature. Almost two-thirds of the patients were obese. These data could be used as a benchmark for outcomes of EC in the region.

New staging of endometrial carcinoma - FIGO 2023.

AIM: To review the changes in the new version of the FIGO 2023 staging system for endometrial cancer. METHODS AND RESULTS: The new FIGO 2023 endometrial cancer staging system provides key updates for the diagnosis and treatment of endometrial cancer. An important step in diagnosis is molecular classification, which allows more accurate risk stratification for recurrence and the identification of targeted therapies. The new staging system, based on the recommendations of the international societies ESGO, ESTRO and ESP, incorporates not only the description of the pathological and anatomical extent of the disease, but also the histopathological characteristics of the tumour, including the histological type and the presence of lymphovascular space invasion. In addition, the staging system uses molecular testing to classify endometrial cancers into four prognostic groups: POLEmut, MMRd, NSMP and p53abn. Each group has its own specific characteristics and prognosis. The most significant changes have occurred in stages I and II, in which the sub-staging better reflects the biological behaviour of the tumour. This update increases the accuracy of prognosis and improves individualized treatment options for patients with endometrial cancer. CONCLUSION: The updated FIGO staging of endometrial cancer for 2023 incorporates different histologic types, tumour features, and molecular classifications to better reflect the current improved understanding of the complex nature of several endometrial cancer types and their underlying bio logic behaviour. The aim of the new endometrial cancer staging system is to better define stages with similar prognosis, allowing for more precise indication of individualised adjuvant radiation or systemic treatment, including the use of immunotherapy.

MRI-based radiomics feature combined with tumor markers to predict TN staging of rectal cancer.

The aim of this study is to evaluate the predictive ability of MRI-based radiomics combined with tumor markers for TN staging in patients with rectal cancer and to develop a prediction model for TN staging. A total of 190 patients with rectal adenocarcinoma who underwent total mesorectal excision at the First Affiliated Hospital of the Air Force Medical University between January 2016 and December 2020 were included in the study. An additional 54 patients from a prospective validation cohort were included between August 2022 and August 2023. Preoperative tumor markers and MRI imaging data were collected from all enrolled patients. The 190 patients were divided into a training cohort (n = 133) and a validation cohort (n = 57). Radiomics features were extracted by outlining the region of interest (ROI) on T2WI sequence images. Feature selection and radiomics score (Rad-score) construction were performed using least absolute shrinkage and selection operator regression analysis (LASSO). The postoperative pathology TNM stage was used to differentiate locally advanced rectal cancer (T3/4 or N1/2) from locally early rectal cancer (T1/2, N0). Logistic regression was used to construct separate prediction models for T stage and N stage. The models' predictive performance was evaluated using DCA curves and calibration curves. The T staging model showed that Rad-score, based on 8 radiomics features, was an independent predictor of T staging. When combined with CEA, tumor diameter, mesoretal fascia (MRF), and extramural venous invasion (EMVI), it effectively differentiated between T1/2 and T3/4 stage rectal cancers in the training cohort (AUC 0.87 [95% CI: 0.81-0.93]). The N-staging model found that Rad-score, based on 10 radiomics features, was an independent predictor of N-staging. When combined with CA19.9, degree of differentiation, and EMVI, it effectively differentiated between N0 and N1/2 stage rectal cancers. The training cohort had an AUC of 0.84 (95% CI: 0.77-0.91). The calibration curves demonstrated good precision between the predicted and actual results. The DCA curves indicated that both sets of predictive models could provide net clinical benefits for diagnosis. MRI-based radiomics features are independent predictors of T staging and N staging. When combined with tumor markers, they have good predictive efficacy for TN staging of rectal cancer.

Imaging in Lung Cancer Staging.

Lung cancer remains one of the leading causes of mortality worldwide, as well as in the United States. Clinical staging, primarily with imaging, is integral to stratify patients into groups that determine treatment options and predict survival. The eighth edition of the tumor, node, metastasis (TNM-8) staging system proposed in 2016 by the International Association for the Study of Lung Cancer remains the current standard for lung cancer staging. The system is used for all subtypes of lung cancer, including non-small cell lung cancer, small cell lung cancer, and bronchopulmonary carcinoid tumors.

Incidence rate of occult lymph node metastasis in clinical T1-2N0M0 small cell lung cancer patients and radiomic prediction based on contrast-enhanced CT imaging: a multicenter study : Original research.

BACKGROUND: This study aimed to explore the incidence of occult lymph node metastasis (OLM) in clinical T1 - 2N0M0 (cT1 - 2N0M0) small cell lung cancer (SCLC) patients and develop machine learning prediction models using preoperative intratumoral and peritumoral contrast-enhanced CT-based radiomic data. METHODS: By conducting a retrospective analysis involving 242 eligible patients from 4 centeres, we determined the incidence of OLM in cT1 - 2N0M0 SCLC patients. For each lesion, two ROIs were defined using the gross tumour volume (GTV) and peritumoral volume 15 mm around the tumour (PTV). By extracting a comprehensive set of 1595 enhanced CT-based radiomic features individually from the GTV and PTV, five models were constucted and we rigorously evaluated the model performance using various metrics, including the area under the curve (AUC), accuracy, sensitivity, specificity, calibration curve, and decision curve analysis (DCA). For enhanced clinical applicability, we formulated a nomogram that integrates clinical parameters and the rad_score (GTV and PTV). RESULTS: The initial investigation revealed a 33.9% OLM positivity rate in cT1 - 2N0M0 SCLC patients. Our combined model, which incorporates three radiomic features from the GTV and PTV, along with two clinical parameters (smoking status and shape), exhibited robust predictive capabilities. With a peak AUC value of 0.772 in the external validation cohort, the model outperformed the alternative models. The nomogram significantly enhanced diagnostic precision for radiologists and added substantial value to the clinical decision-making process for cT1 - 2N0M0 SCLC patients. CONCLUSIONS: The incidence of OLM in SCLC patients surpassed that in non-small cell lung cancer patients. The combined model demonstrated a notable generalization effect, effectively distinguishing between positive and negative OLMs in a noninvasive manner, thereby guiding individualized clinical decisions for patients with cT1 - 2N0M0 SCLC.

Advances in Diagnostic, Staging, and Restaging Evaluation of Esophageal and Gastric Cancer.

The initial endoscopic and staging evaluation of esophagogastric cancers must be accurate and comprehensive in order to select the optimal therapeutic plan for the patient. Esophageal and gastric cancers (and treatment paradigms) are delineated by their proximity to the cardia (within 2 cm). The most frequent and important symptom that informs the initial staging evaluation is dysphagia, which is associated with at least cT3 or locally advanced disease. Endoscopic ultrasound is often needed if earlier stage disease is suspected, preferably in combination with endoscopic mucosal or submucosal resection or fine-needle aspiration of suspicious lymph nodes to enhance staging accuracy.

A CT-based integrated model for preoperative prediction of occult lymph node metastasis in early tongue cancer.

Background: Occult lymph node metastasis (OLNM) is an essential prognostic factor for early-stage tongue cancer (cT1-2N0M0) and a determinant of treatment decisions. Therefore, accurate prediction of OLNM can significantly impact the clinical management and outcomes of patients with tongue cancer. The aim of this study was to develop and validate a multiomics-based model to predict OLNM in patients with early-stage tongue cancer. Methods: The data of 125 patients diagnosed with early-stage tongue cancer (cT1-2N0M0) who underwent primary surgical treatment and elective neck dissection were retrospectively analyzed. A total of 100 patients were randomly assigned to the training set and 25 to the test set. The preoperative contrast-enhanced computed tomography (CT) and clinical data on these patients were collected. Radiomics features were extracted from the primary tumor as the region of interest (ROI) on CT images, and correlation analysis and the least absolute shrinkage and selection operator (LASSO) method were used to identify the most relevant features. A support vector machine (SVM) classifier was constructed and compared with other machine learning algorithms. With the same method, a clinical model was built and the peri-tumoral and intra-tumoral images were selected as the input for the deep learning model. The stacking ensemble technique was used to combine the multiple models. The predictive performance of the integrated model was evaluated for accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC-ROC), and compared with expert assessment. Internal validation was performed using a stratified five-fold cross-validation approach. Results: Of the 125 patients, 41 (32.8%) showed OLNM on postoperative pathological examination. The integrated model achieved higher predictive performance compared with the individual models, with an accuracy of 84%, a sensitivity of 100%, a specificity of 76.5%, and an AUC-ROC of 0.949 (95% CI [0.870-1.000]). In addition, the performance of the integrated model surpassed that of younger doctors and was comparable to the evaluation of experienced doctors. Conclusions: The multiomics-based model can accurately predict OLNM in patients with early-stage tongue cancer, and may serve as a valuable decision-making tool to determine the appropriate treatment and avoid unnecessary neck surgery in patients without OLNM.

Identificación de las características de los ganglios evaluados en el procedimiento EBUS y su relación con el diagnóstico de malignidad en instituto de alta complejidad en cáncer / Identification of the Characteristics of the Lymph Nodes Evaluated in the EBUS Procedure and their Relationship with the Diagnosis of Malignancy in a Highly Complex Cancer Institute

Introducción: La EBUS ha sido el foco de numerosos estudios destinados a evaluar su utilidad y rendimiento diagnóstico en diversas patologías. Objetivo principal: Identificación de las características ganglionares evaluadas en el procedimiento de Ultrasonido Endobronquial (EBUS) y su relación con el diagnóstico de malignidad en pacientes del Instituto Nacional del Cáncer de Colombia del 1 de enero de 2017 al 31 de marzo de 2021.Métodos: Estudio analítico observacional transversal. La recopilación de datos implicó un muestreo de casos consecutivos no probabilísticos entre individuos que cumplían los criterios de inclusión.Resultados: Un total de 75 pacientes fueron sometidos a EBUS. Se identificaron 6 características ecográficas de los ganglios de la biopsia asociadas a malignidad destacándose los ganglios mayores de 1 cm, márgenes mal definidos, ecogenicidad heterogénea, ausencia de una estructura hiliar central, presencia de signos de necrosis o coagulación y presencia de conglomerado ganglionar. Conclusión: Este estudio caracterizó la frecuencia de los hallazgos en la ultrasonografía endobronquial destacando algunas características ecográficas de los ganglios mediastínicos que podrían predecir patología maligna.

Introduction: The EBUS has been the focus of numerous studies aiming to evaluate its utility and diagnostic performance across various pathologies. Objective: Identification of the node characteristics evaluated in the Endobronchial Ultrasound (EBUS) procedure and their relationship with malignancy diagnosis in patients at the National Cancer Institute of Colombia from January 1st, 2017, to March 31st, 2021. Methods: Observational cross-sectional analytical study. Data collection involved non-probabilistic consecutive case sampling among individuals meeting the inclusion criteria.Results: A total of 75 patients underwent the EBUS procedure. Our findings revealed six predictors of malignancy based on sonographic features of biopsy nodes, including nodes larger than 1 cm, poorly defined margins, heterogeneous echogenicity, absence of a central hilar structure, presence of signs indicating necrosis or coagulation, and the presence of a ganglion conglomerate. Conclusions: This study showed that endobronchial ultrasonography has several sonographic characteristics at the time of evaluating mediastinal nodes that could predict malignant and benign pathology.

The International Association for the Study of Lung Cancer Staging Project for Lung Cancer: Proposals for the Revision of the M Descriptors in the Forthcoming Ninth Edition of the TNM Classification for Lung Cancer.

INTRODUCTION: This study analyzed all metastatic categories of the current TNM classification of NSCLC to propose modifications of the M component in the next edition (ninth) of the classification. METHODS: A database of 124,581 patients diagnosed between 2011 and 2019 was established; of these, 14,937 with NSCLC in stages IVA to IVB were available for this analysis. Overall survival was calculated using the Kaplan-Meier method, and prognosis was assessed using multivariable-adjusted Cox proportional hazards regression. RESULTS: The eighth edition M categories revealed good discrimination in the ninth edition data set. Assessments revealed that an increasing number of metastatic lesions were associated with decreasing prognosis; because this seems to be a continuum and adjustment for confounders was not possible, no specific lesion number was deemed appropriate for stage classification. Among tumors involving multiple metastases, decreasing prognosis was found with an increasing number of organ systems involved. Multiple assessments, including after adjustment for potential confounders, revealed that M1c patients who had metastases to a single extrathoracic organ system were prognostically distinct from M1c patients who had involvement of multiple extrathoracic organ systems. CONCLUSIONS: These data validate the eighth edition M1a and M1b categories, which are recommended to be maintained. We propose the M1c category be divided into M1c1 (involvement of a single extrathoracic organ system) and M1c2 (involvement of multiple extrathoracic organ systems).

Validación de técnica de ganglio centinela en cáncer de endometrio en el Hospital de Talca / Validation of sentinel lymph node technique in endometrial cancer at the Hospital de Talca

Objetivo: Validar la técnica de ganglio centinela utilizando verde de indocianina en la estadificación del cáncer de endometrio. Método: Realizamos un estudio prospectivo entre enero y diciembre de 2021. Se incluyeron todas las pacientes portadoras de cáncer de endometrio clínicamente en etapa 1, de todos los grados de diferenciación e histologías. Todas las pacientes fueron sometidas a una estadificación laparoscópica. Se inició el procedimiento con identificación de ganglio centinela utilizando verde de indocianina. Posteriormente, se completó la cirugía de estadiaje estándar en todas las pacientes. Los ganglios centinelas fueron procesados con técnica de ultraestadiaje. Resultados: Se incluyeron 33 pacientes. El 81% presentaron histología endometrioide. El 100% fueron sometida además a una linfadenectomía pelviana estándar y el 20% a una linfadenectomía paraaórtica simultáneamente. Se detectó al menos un ganglio centinela en el 100% de los casos. La detección bilateral ocurrió en el 90,9%. La localización más frecuente fue la fosa obturatriz y la arteria hipogástrica. Obtuvimos una sensibilidad del 90% para detectar enfermedad ganglionar y un valor predictivo negativo del 95,8%. Conclusiones: La técnica de ganglio centinela utilizando verde de indocianina es replicable. Los resultados de nuestra serie nos permiten realizar procedimientos menos agresivos al estadificar el cáncer de endometrio.

Objective: To validate sentinel node mapping using indocyanine green in endometrial cancer staging. Method: A prospective study was conducted between January and December 2021. All patients with clinically stage 1 endometrial cancer, of all grades and histologies were included. All patients underwent laparoscopic staging. The procedure began with identification of the sentinel node using indocyanine green. Subsequently, standard staging surgery was completed in all patients. Sentinel nodes were processed using ultrastaging technique. Results: Thirty-three patients were enrolled. 81% of cases had endometrioid histology. All patients also underwent a standard pelvic lymphadenectomy and in 20% of cases a para-aortic lymphadenectomy. At least one sentinel node was detected in 100% of the cases. Bilateral detection occurred in 90.9%. The most frequent location was obturator fossa and hypogastric artery. Sensitivity to detect lymph node disease was 90% and negative predictive value 95.8%. Conclusions: Sentinel lymph node mapping using indocyanine green is a replicable technique. Our results allows us to perform less aggressive procedures in endometrial cancer staging.

Adenocarcinoma gástrico: revisión del TNM y de las vías de diseminación / Gastric adenocarcinoma: A review of the TNM classification system and ways of spreading

El cáncer gástrico es el quinto cáncer más frecuente en el mundo. El subtipo histológico más frecuente es el adenocarcinoma. Para su estadificación se utiliza la 8.ª edición de la clasificación TNM de la American Joint Comittee on Cancer. Los ligamentos perigástricos, el mesenterio, el omento y los espacios potenciales entre los revestimientos peritoneales parietal y visceral, son estructuras con gran implicación en la estadificación. La diseminación de la enfermedad se ve afectada por la localización del tumor en el estómago, así como por la anatomía ligamentaria y linfática. La tomografía computarizada es la modalidad de imagen de elección para la estadificación clínica preoperatoria del cáncer gástrico, y es esencial para la planificación del tratamiento. Existen múltiples vías de diseminación en el cáncer gástrico que se deben conocer para poder realizar una correcta valoración radiológica: linfática, subperitoneal, invasión directa, transperitoneal, hematógena e invasión venosa extramural. (AU)

Gastric cancer is the fifth most common cancer in the world. The most common histologic subtype is adenocarcinoma. Gastric adenocarcinomas are staged using the American Joint Committee on Cancer's 8th TNM classification. The perigastric ligaments, mesentery, omentum, and potential spaces between the parietal and visceral peritoneal linings are important structures for staging. The spread of disease is influenced by the location of the tumor within the stomach, as well as by the anatomy related to the ligaments and lymph vessels. CT is the imaging modality of choice for the preoperative clinical staging of gastric cancer, and it is essential for planning treatment. To be able to do an adequate imaging workup, radiologists need to know the different pathways through which gastric cancer can spread: lymphatic, subperitoneal, direct invasion, transperitoneal, hematogenous, and extramural venous invasion. (AU)

Retrospective audit: Utility of PET scan in routine preoperative rectal cancer staging.

BACKGROUND: Accurate staging for rectal cancer is pertinent with recent introduction of rectum-sparing approaches for patients showing complete clinical response on restaging. Positron emission tomography(PET) is used in detection of recurrence or metastasis, but its value in routine preoperative rectal cancer staging remains unclear. Studies report that preoperative PET altered the stage in 39% and changed the management in 17-27% of patients. Our study aims to look at the utility of PET in routine preoperative staging of rectal cancer within 2 two colorectal units, and to determine if PET did result in a change in management. METHODS: Patients in Nepean Hospital (NSW) and Peter MacCallum Cancer Centre (VIC) who were diagnosed with rectal cancer between 1 January 2017 and 31 December 2021 were included in this retrospective study. All patients who did not have a PET scan were excluded. PET scan results were then compared with MRI and CT results. RESULTS: Three hundred and fifty-seven patients were included in the study. 30.3% of the patients had Stage 3 rectal cancer. 71.7% received neoadjuvant therapy. PET scan provided additional information in 55.5% of patients when compared with CT and MRI alone; 18.2% of the PET findings resulted in an altered management for the patient. CONCLUSION: PET scan can be a valuable tool in accurate staging, especially for ambiguous or equivocal lesions on CT. Our study demonstrated that additional information from PET scan resulted in an altered management plan in 18.2% of the patients. PET/MRI as a newer modality may be more accurate with reduced radiation exposure.

Valor pronóstico del ratio nodal en el cáncer gástrico: análisis unicéntrico de 199 pacientes / Prognostic value of the nodal ratio in gastric cancer: Unicentric analysis pf 199 patients

IntroducciónEl sistema de clasificación ganglionar más utilizado en el cáncer gástrico es el TNM. No obstante presenta limitaciones, como la «migración de estadificación» en los casos con linfadenectomías subóptimas, por ello se han planteado distintos sistemas. Asimismo, el objetivo fue valorar la influencia del ratio nodal medido en terciles [RNt] como factor pronóstico, y compararlo con los sistemas TNM (7.ª ed.) y log odds of positive lymph nodes [LODDS].Material y métodosSe trata de un estudio retrospectivo y unicéntrico sobre 199 pacientes con neoplasia gástrica intervenidos con intención curativa entre 2010 y 2014. Se realizó un análisis univariante y multivariante de cada sistema, y se compararon las tasas de supervivencia global [SG] obtenidas mediante test ROC.ResultadosLos factores pronóstico que mostraron significación estadística en el análisis multivariante fueron: RNt2 (HR 2,87) y RNt3 (HR 7,29); LODDS 2 (HR 1,55), LODDS3 (HR 2,6) y LODDS4 (HR 4,9); pN2 (HR 1,84) y pN3 (HR 2,91). La SG a 5 años fue del 75,8, 61,4, 25,8 y 3,84% para RNt0, RNt1, RNt2 y RNt3; 72,4, 60, 29,1 y 13,9% para LODDS1, LODDS2, LODDS3 y LODDS4; y 77,6, 59,4, 28,8 y 25,5% para pN0, pN1, pN2 y pN3, respectivamente. Los 3 sistemas se comportaron como buenos predictores, con áreas bajo la curva >0,75.ConclusiónEl RNt fue un factor pronóstico independiente para la estimación de la supervivencia en el cáncer gástrico. Además, la facilidad de su cálculo en la práctica clínica podría disminuir el efecto de migración de estadificación (AU)

IntroductionIn the gastric cancer the most widely used classification is the AJCC TNM system. However, it presents limitations, such as staging migration in cases with suboptimal lymphadenectomies. The nodal ratio has been proposed as an alternative system, proving to be a good prognostic predictor of survival. The aim was to assess the influence of the nodal ratio measured in tertiles [tNR] as a prognostic factor and compare with the TNM systems (7th ed.) and log odds of positive lymph nodes [LODDS].Material and methodsRetrospective and single-center study on 199 patients operated on with curative intent between 2010 and 2014. For each system an univariate and multivariate analysis was performed and the overall survival rates [OS] were compared by the ROC test.ResultsThe prognostic factors that showed statistical significance in the multivariate analysis were: tNR2 (HR 2.87) and tNR 3 (HR 7.29); LODDS 2 (HR 1.55), LODDS3 (HR 2.6) and LODDS4 (HR 4.9); pN2 (HR 1.84) and pN3 (HR 2.91). The 5-year OS was 75.8, 61.4, 25.8 and 3.84% for tNR0, tNR1, tNR2 and tNR3; 72.4, 60, 29.1 and 13.9% for LODDS1, LODDS2, LODDS3 and LODDS4; and 77.6, 59.4, 28.8 and 25.5% for pN0, pN1, pN2 and pN3, respectively. The three systems behaved as good predictors, with areas under the curve >0.75.ConclusiontNR was an independent prognostic factor for estimating survival in gastric cancer. Furthermore, the ease of its calculation in clinical practice could reduce the effect of staging migration (AU)

The International Association for the Study of Lung Cancer Thymic Epithelial Tumor Staging Project: Unresolved Issues to be Addressed for the Next Ninth Edition of the TNM Classification of Malignant Tumors.

Thymic epithelial tumors are presently staged using a consistent TNM classification developed by the International Association for the Study of Lung Cancer (IASLC) and approved by the Union for International Cancer Control and the American Joint Committee on Cancer. The stage classification is incorporated in the eight edition of the TNM classification of thoracic malignancies. The IASLC Staging and Prognostic Factors Committee (SPFC)-Thymic Domain (TD) is in charge for the next (ninth) edition expected in 2024. The present article represents the midterm report of the SPFC-TD: in particular, it describes the unresolved issues identified by the group in the current stage classification which are worth being addressed and discussed for the ninth edition of the TNM classification on the basis of the available data collected in the central thymic database which will be managed and analyzed by Cancer Research And Biostatistics. These issues are grouped into issues of general importance and those specifically related to T, N, and M categories. Each issue is described in reference to the most recent reports on the subject, and the priority assigned by the IASLC SPFC-TD for the discussion of the ninth edition is provided.

PSMA PET/CT guided intensification of therapy in patients at risk of advanced prostate cancer (PATRON): a pragmatic phase III randomized controlled trial.

BACKGROUND: Positron emission tomography targeting the prostate specific membrane antigen (PSMA PET/CT) has demonstrated unparalleled performance as a staging examination for prostate cancer resulting in substantial changes in management. However, the impact of altered management on patient outcomes is largely unknown. This study aims to assess the impact of intensified radiotherapy or surgery guided by PSMA PET/CT in patients at risk of advanced prostate cancer. METHODS: This pan-Canadian phase III randomized controlled trial will enroll 776 men with either untreated high risk prostate cancer (CAPRA score 6-10 or stage cN1) or biochemically recurrent prostate cancer post radical prostatectomy (PSA > 0.1 ng/mL). Patients will be randomized 1:1 to either receive conventional imaging or conventional plus PSMA PET imaging, with intensification of radiotherapy or surgery to newly identified disease sites. The primary endpoint is failure free survival at 5 years. Secondary endpoints include rates of adverse events, time to next-line therapy, as well as impact on health-related quality of life and cost effectiveness as measured by incremental cost per Quality Adjusted Life Years gained. DISCUSSION: This study will help create level 1 evidence needed to demonstrate whether or not intensification of radiotherapy or surgery based on PSMA PET findings improves outcomes of patients at risk of advanced prostate cancer in a manner that is cost-effective. TRIAL REGISTRATION: This trial was prospectively registered in ClinicalTrials.gov as NCT04557501 on September 21, 2020.