Neoplasms

All Conditions

Digestive System Diseases

Symptoms and General Pathology

Rare Diseases

Adenocarcinoma

Stomach Neoplasms

Inflammation

Recurrence

Carcinoma

Neoplasms, Glandular and Epithelial

Neoplasms by Histologic Type

Disease Attributes

Stomach Cancer

Changming Huang, M.D.

This study aimed to develop a novel Prognostic Oxidative Stress-Immune-Inflammatory Score (POSII Score) and introduce an innovative online calculator designed to predict long-term survival and assess the recurrence risk of gastric cancer (GC).

From 2009 to 2020, this study analyzed GC patients underwent Radical Gastrectomy at three hospitals, dividing them into training, internal, and external validation cohorts. Twelve blood indicators were analyzed. The POSII Score was developed in the training cohort using the Least Absolute Shrinkage and Selection Operator (LASSO) technique. Additionally, two online nomogram calculators were created based on multivariate Cox regression within the training cohort and subsequently validated in internal and external validation cohorts.

A Novel Online Calculator to Predict Long-term Survival and Recurrence Risk of Patients With Gastric Adenocarcinoma

A Novel Online Calculator to Predict Long-term Survival and Recurrence Risk of Patients With Gastric Adenocarcinoma After Radical Gastrectomy : A Multicenter Real-world Study

overall survival, death, survival with tumor, deletion

Fujian Medical University Union Hospital

Fujian Medical University

Professor

Urinary Tract, Sexual Organs, and Pregnancy Conditions

Uterine Diseases

Genital Diseases, Female

Genital Diseases

Urogenital Diseases

Female Urogenital Diseases

Pregnancy Complications

Female Urogenital Diseases and Pregnancy Complications

We evaluate the clinical, ultrasound and laboratory features to predict endometrial cancer disease preoperative

Training set

VERIFICATION SET

Roberto Angioli, MD

The purpose of this study was to obtain a predictive model to asses the Risk of Endometrial Malignancy (REM) in women with ultrasound endometrial abnormalities.

Objective: It is often difficult to distinguish a benign endometrial disease from a malignancy and tools to help physician are needed, in order to triage patients into high and low risk of endometrial cancer (EC). The purpose of this study was to obtain a predictive model to asses the Risk of Endometrial Malignancy (REM) in women with ultrasound endometrial abnormalities.Women, between 45 and 80 years, diagnosed with ultrasound endometrial abnormalities and scheduled to have surgery were enrolled on a prospective study at Department of Gynaecologic Oncology of Campus Bio-Medico of Rome. Preoperative clinical, ultrasound and laboratory features were taken into account. Logistic regression algorithm was utilized to categorize patients into low and high risk groups for EC.

REM (Risk Of Endometrial Malignancy)

REM (Risk Of Endometrial Malignancy): A Proposal for a New Scoring System to Evaluate Risk of Endometrial Malignancy

We consider training and verification set together to evaluate the overall sensitivity and specificity of predictive tool

We select patients affected by endometrial cancer and benign endometrial disease. Preoperative they underwent to pelvic ultrasound, CA125 and HE4 dosage and anamnesis. They will be considered as training group to obtaine the probability of endometrial malignancy based on HE4, ultrasound features and symptoms.

We select a verification set, composed by endometrial cancer disease and benign endometrial pathologies patients. In this set we apply the risk of endometrial cancer tool, obtained in the training set, in order to verify the sensitivity, specificity and reproducibility.

Campus Bio-Medico University

Skin and Connective Tissue Diseases

Breast Neoplasms

Breast Diseases

Skin Diseases

All Drugs and Chemicals

Hormones

postoperative hormone receptor-positive breast cancer

Young-Hyuck Im, M.D., Ph.D.

Gene expression studies have identified at least four molecularly distinct subtypes of breast cancer including two biologically distinct ER-positive subtypes of breast cancer: luminal A and luminal B (with luminal B tumors having poorer outcomes than luminal A tumors). Although some luminal B tumors can be identified by their expression of HER2, the major biological distinction between luminal A and B is the proliferation signatures, including genes such as CCNB1, MKI67, and MYBL2, which have higher expression in luminal B tumors than in luminal A tumors. The high cost of gene expression profiling has limited its incorporation into general clinical practice. To date, there is no available IHC-based surrogate assay that can distinguish between luminal A and luminal B tumors. We hypothesized that the IHC determination of the Ki67 index as well as ER, PgR, and HER2 status is able to distinguish the luminal B subtype of breast cancers from the luminal A subgroup.

Gene expression studies have identified five molecularly distinct subtypes of breast cancer that have prognostic value across multiple treatment settings including tow biologically distinct estrogen receptor (ER)-positive subtypes of breast cancer: luminal A and luminal B.The expression of ER-associated genes characterizes the luminal breast cancers, with luminal B tumors having poorer outcomes than luminal tumors. Although some luminal B tumors can be identified by their expression of HER2, the major biological distinction between luminal A and B is the proliferation signature, including genes such as CCNB1, MKI67, and MYBL2, which have higher expression in luminal B tumors than in luminal A tumors.Therefore, a distinction between luminal A and B tumor that is based on proliferation status among ER-positive luminal patients may be important to breast cancer biology and prognosis.

The high cost of gene expression profiling has limited its incorporation into most randomized clinical trials, and thus, DNA microarray-defined proliferation status is not used to provide prognostic information in general practice. Although the Ki67 gene may have prognostic value, evaluations of this marker in the adjuvant setting raise conflicts, and in the absence of a standardized test for Ki67, it is difficult to draw firm conclusions from trials.As a result, Ki67 cannot be used to assign patients to specific treatments or risk groups.

Yet despite great uncertainty, the panel of experts at the St. Gallen Consensus in 2009 proposed to (1) classify tumors as low, intermediate, or high in proliferative potential corresponding to Ki67 labelling index values of less than or equal to 15%, 16-30%, and more than 30%, respectively, and (2) use the Ki67 labeling index as a criterion for selecting to add chemotherapy to endocrine therapy in HR-positive BCs. Since proliferation is uniformly higher in basal-like and HER2 cancers but is variable within ER-positive cancer, the greatest practical prognostic value of proliferative index seems to be within ER-positive disease. Decisions regarding the use of adjuvant therapy in early operable breast cancer depend on an array of factors that predict prognosis and therapeutic efficacy. Multigene signatures related to cell proliferation show consistent accuracy in the clinical characterization of hormone receptor (HR)-positive BC, hence interest in biologic factors that predict the adjuvant response continues to increase.

Based on this consensus, we hypothesized that in a large patient population with a long follow-up, we could determine a cut-off value for the Ki67 labeling index that is sufficiently sensitive and specific to identify the patients with HR-positive luminal BC who will not require the addition of cytotoxic chemotherapy to endocrine treatment. In addition, a comparison of the objective significance level for Ki67 with values for other confirmed biomarkers (e.g., HER2, estrogen receptor, and histologic differentiation) may clarify the value of Ki67 as a biomarker in HR-positive luminal BCs.

Usefulness of Ki67 Index in Hormone Receptor-positive Breast Cancer

Usefulness of Ki67 Proliferative Index to Predict Recurrence and Benefit From Adjuvant Chemotherapy in Hormone Receptor (HR)-Positive Breast Cancer

Samsung Medical Center

professor

Mouth and Tooth Diseases

Ear, Nose, and Throat Diseases

Nasopharyngeal Carcinoma

Nasopharyngeal Neoplasms

Pharyngeal Neoplasms

Otorhinolaryngologic Neoplasms

Head and Neck Neoplasms

Nasopharyngeal Diseases

Pharyngeal Diseases

Stomatognathic Diseases

Otorhinolaryngologic Diseases

Antineoplastic Agents

Docetaxel

Cisplatin

Tubulin Modulators

Antimitotic Agents

low risk NPC treated with concurrent chemoradiotherapy

high risk NPC treated with concurrent chemoradiotherapy

high risk NPC treated with induction chemotherapy plus concurrent chemoradiotherapy

Docetaxel 65mg/m2 in induction chemotherapy

Cisplatin 75mg/m2 in induction chemotherapy

Cisplatin 1

Xeloda 2000mg/m2 D1-14 in induction chemotherapy

Xeloda

IMRT

Cisplatin 100mg/m2 in concurrent chemotherapy

Cisplatin 2

Fang-Yun Xie

The investigators aim to evaluate the efficiency and toxicities of induction chemotherapy of docetaxel, cisplatin and xeloda in nomogram-predicted high risk locoregionally advanced nasopharyngeal carcinoma.

All eligible patients receive intensity-modulated radiotherapy (IMRT) with a total dose of 68 Gy or higher in 33 fractions to the primary tumor. Nomogram-predicted low risk patients (Group A) receive concurrent chemotherapy, while nomogram-predicted high risk patients are randomized to receive concurrent chemotherapy (Group B) or induction chemotherapy followed by concurrent chemotherapy (Group C). Induction chemotherapy consists of docetaxel 65 mg/m², D1, cisplatin 75 mg/m², D1 and Xeloda 2000mg/m², D1-14 every 3 weeks for 3 cycles. Concurrent chemotherapy consists of cisplatin 100 mg/m², D1 every 3 weeks for 3 cycles.The primary endpoint is failure-free survival (FFS). Secondary end points include overall survival (OS), locoregional relapse-free survival (LRFS), distant metastasis-free survival (DMFS) and the incidence of grade 3 or higher acute toxicities. All efficacy analyses are conducted in the intention-to-treat population, and the safety population include only patients who receive their randomly assigned treatment.

Induction Chemotherapy of TPX in Nomogram-predicted High Risk Locoregionally Advanced Nasopharyngeal Carcinoma

Induction Chemotherapy of Docetaxel, Cisplatin and Xeloda in Nomogram-predicted High Risk Locoregionally Advanced Nasopharyngeal Carcinoma

Sun Yat-sen University

Prof.

This study aims to develop a nomogram to predict postoperative recurrence of HAS and guide individually tailored surveillance strategies.

Patients were included from the China Hepatoid Adenocarcinoma of the Stomach Study Group (China-HASSG) database, which comprises 14 tertiary referral centers. All the patients who had undergone complete resection of a primary HAS between April 2004 and December 2019 were included. First, univariate analysis was performed in Cox regression to identify the risk factors associated with RFS. Next, variables with P\< 0.05 in univariable analysis were included in the multivariable model, and the forward likelihood ratio method was used for analysis to confirm the independent prognostic factors associated with RFS. Finally, based on the results of multivariable analysis, variables that achieved significance at P\< 0.05 were selected to formulate a nomogram.

A Recurrence Nomogram for Hepatoid Adenocarcinoma of the Stomach

A Recurrence Nomogram to Guide Surveillance Strategies After the Resection of Hepatoid Adenocarcinoma of the Stomach: a China Hepatoid Adenocarcinoma of the Stomach Study Group Database Study

Reurrence-free survival was defined as the time interval from the date of the operation to the date of first recurrence or death from any cause.

Gland and Hormone Related Diseases

Neoplasm Metastasis

Thyroid Diseases

Thyroid Cancer, Papillary

Carcinoma, Papillary

Thyroid Neoplasms

Lymphatic Metastasis

Neoplastic Processes

Endocrine System Diseases

Neoplasms, Squamous Cell

Adenocarcinoma, Papillary

Endocrine Gland Neoplasms

Papillary Thyroid Carcinoma

Nine preoperative predictors were identified for the nomogram: gender, age, platelet counts, TPOAb level and US signatures including maximum diameter, boundary, component, calcification and cervical lymph node enlargement.

male

mingtong xu, professor

To establish and validate a suitable and practical nomogram for primary hospitals to predict the risk of central lymph node metastasis (CLNM) among thyroid papillary carcinoma (PTC) patients based on clinical and ultrasound characteristics among Chinese population，1000 PTC patients were retrospectively reviewed who underwent bilateral thyroidectomy or lobectomy plus central lymph node dissection（CLND） between June 2014 and September 2019 in Sun Yat-sen Memorial Hospital (Guangzhou, South China), and then LASSO regression analysis was performed to screen out the possible predictors. Another 200 PTC patients from the First Affiliated Hospital of Zhengzhou University (Zhengzhou, North China) who underwent bilateral thyroidectomy or lobectomy plus CLND between March 2019 and November 2020 were enrolled to construct the nomogram. The area under the receiver operating characteristic (ROC) curves (AUC), calibration curves and decision curve analysis (DCA) were used to evaluate the nomogram.

1000 Patients who underwent total thyroidectomy or lobectomy and were diagnosed as PTC by pathological examination between June 2014 and September 2019 in Sun Yat-sen Memorial Hospital (Guangzhou, South China) and 200 patients in the First Affiliated Hospital of Zhengzhou University (Zhengzhou, North China) from March 2019 to November 2020 were selected as the subjects to construct the nomogram. 1000 patients were randomized at 7:3 and divided into a training set and a verification set. Besides, 200 cases that met the inclusion and exclusion criteria above-mentioned in the First affiliated Hospital of Zhengzhou University were enrolled as a external verification set.

The following clinical features for each patient were obtained before surgery: gender, age, occupation, complicated with autoimmune diseases (absent / present), history of radiation exposure (absent / present), family history of thyroid cancer (absent / present), with other tumors (absent / present) and preoperative laboratory examinations including neutrophil count, lymphocyte count, platelet count, thyroid-stimulating hormone (TSH), free triiodothyronine (fT3), free thyroxine (fT4), anti-thyroglobulin antibody (TgAb), thyroid peroxidase antibody (TPOAb).

Preoperative US signatures of thyroid tumors were also included: distribution (unilateral / bilateral), shape (regular / irregular), maximum diameter, number (single / multiple), boundary（clear /heliclear / unclear), component (solid /cystic-solid), calcification (absent / microcalcification / macrocalcification), blood flow (absent / internal / annular), cervical lymph node enlargement (absent / present).

A nomogram were established for predicting CLNM based on the universally available baseline Characteristics of PTC patients at a tertiary hospital in South China and externally validate it with data from North China. Odd ratios (ORs), 95% confidence interval (CI) and probability values were obtained by logistic regression analysis. The area under the receiver operating characteristic (ROC) curve (AUC) was calculated to evaluate the accuracy of the nomogram for predicting CLNM. The calibration curve and Hosmer-Lemeshow tests were performed to evaluate the calibration of the nomogram. The decision curve analysis (DCA) was applied to validate clinical utility of the nomogram.

A Nomogram Model to Predict Central Lymphnode Metastasis in Thyroid Papillary Carcinoma

A Nomogram Model to Predict Central Lymphnode Metastasis in Thyroid Papillary Carcinoma Suitable for Primary Hospitals

Multivariate logistic regression analysis were conducted to determine the potential nonlinear association between predictors and and the risk of CLNM.

The First Affiliated Hospital of Zhengzhou University

Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Nutritional and Metabolic Diseases

Uterine Cervical Neoplasms

Malnutrition

Uterine Neoplasms

Genital Neoplasms, Female

Urogenital Neoplasms

Uterine Cervical Diseases

Nutrition Disorders

A primary cohort of eligible patients from the cancer center of Zhejiang Provincial People's Hospital is used for developing the radiomics-based nomogram prediction model. In the training cohort, a sample size of 88 was required to accept the hypothesis that the prediction accuracy of the radiomics-based nomogram model was greater than 45% with 90% power and to reject the hypothesis that the prediction accuracy rate was less than 30% with an α error of 5%. Initially, we planned to enroll 77 patients in the first stage. If 27 or more prediction accuracy rates were observed, we planned to continue to the second stage for a total of 88 patients for the analysis. Considering some deviant cases, the preplanned accrual number was set to 100 patients in the training cohort.

An independent cohort of eligible patients is used for external validation. we are planning to enroll an additional 50 patients to further validate this radiomics-based nomogram prediction model.

There are no interventions.

Hong'en Xu, M.D.

Huafeng Shou, M.D.

Yongshi Jia, M.D.

Loss of skeletal muscle, is one of the most prevalent symptoms of malnutrition, and has been frequently reported as a negative factor in cancer patients at any disease stage. In this study, we are planning to firstly analyze the radiomics features of psoas extracted at the level of the third lumbar vertebra (L3) and then, develop a CT-based radiomics nomogram prediction model for predicting malnutrition based on their Patient-Generated Subjective Global Assessment (PG-SGA) scores in patients with International Federation of Gynecology and Obstetrics (FIGO, 2014 version) stage IB1-IIA2 cervical cancer (CC) who received postoperative radiotherapy/chemoradiotherapy (RT/CRT).

Cervical cancer is still a significant health problem worldwide. Based on the pathological findings after surgery, patients with intermediate or high risk factors for recurrence are recommended to receive adjuvant pelvic RT and/or platinum (cisplatin or carboplatin) based CRT to reduce the risk of tumor recurrence. However, around 30% of individuals with CC will still eventually develop tumor relapse, necessitating the investigation of better supportive care, like nutritional support, to improve therapeutic tolerance and reduce toxic reactions in these patients. In this respect, how to early identification of malnutrition by PG-SGA tool is crucial.

Meanwhile, CT-based radiomics approaches have been successfully applied to generate imaging biomarkers as decision support tools for clinical practice. In our recently accepted research (not yet publish on line, abstract available at https://www.frontiersin.org/articles/10.3389/fnut.2023.1113588/abstract), we firstly analyzed the radiomics features of psoas extracted at the level of L3 and then, developed a nomogram prediction model for patients with FIGO stage IB1-IIA2 CC who received postoperative RT/CRT. Our results demonstrated that this nomogram prediction model showed promising ability for detecting malnutrition based on their PG-SGA scores. The aim of the current study is designed to verify the prediction accuracy of the developed radiomics-based nomogram prospectively.

Radiomics-based Malnutrition for Cervical Cancer.

Development and Validation of a CT-Based Radiomics Nomogram for the Prediction of Postoperative Malnutrition in Stage IB1-IIA2 Cervical Cancer (Nutrition Helper-1).

Analyze the correlation among NRS-2002 score, PG-SGA score and the GLIM criteria.

Construction and validation of a radiomics-based nomogram for the prediction of malnutrition based on the PG-SGA scores in cervical cancer patients who underwent postoperative radiotherapy/chemoradiotherapy.

Predict malnutrition assessed by the new Global Leadership Initiative on Malnutrition (GLIM) criteria.

Zhejiang Provincial People's Hospital

Attending Doctor

Jianguo Lai, M.D.

Jianguo Lai, M.D

Fengyan Yu, M.D,PHD

Fengyan Yu, M.D.,Ph.D

Axillary lymph node status is a vital prognostic factors in breast cancer patients and provides crucial information for making treatment decisions.This projective observational study is planned to identify risk factors for axillary metastases in breast cancer patients with axillary ultrasound and to construct a nomogram to predict the risk of axillary metastases in these patients.

Breast carcinoma is the most common malignancy in women, accounting for 25% of all female cancer cases and 15% of all cancer-related deaths in the world.Lymph node metastasis is a multifactorial event. Among patients with a preoperative axillary ultrasound, almost 40% of patients are pathologically proved to be free from axillary metastasis.The purpose of this study is to develop a nomogram to evaluate the probability of axillary metastasis as a tool to support clinical decision-making.

Predict the Risk of Axillary Metastases in Breast Cancer Patients With Axillary Ultrasound

A Nomogram to Predict the Risk of Axillary Metastases in Breast Cancer Patients With Axillary Ultrasound

Surgical treatment for breast cancer patients include breast-conserving surgery or mastectomy with or without breast reconstruction. Intraoperative ALND is carried out when the SLNs are positive by intraoperative frozen section. Post-operative H\&E permanent staining is administered to confirm the results of the frozen section. Serial H\&E and immunohistochemistry stain (IHC) are only carried out when axillary metastases are not visible after H\&E staining.

Principal Investigator

Constriction, Pathologic

Rectal Neoplasms

Colorectal Neoplasms

Intestinal Neoplasms

Gastrointestinal Neoplasms

Digestive System Neoplasms

Gastrointestinal Diseases

Intestinal Diseases

Rectal Diseases

Pathological Conditions, Anatomical

without any intervention, patients diagnose as anastomotic stricture after rectal cancer surgery

without any intervention, patients does not diagnose as anastomotic stricture after rectal cancer surgery

without any intervention

Background: Anastomotic stricture significantly impacts patients' quality of life and long-term prognosis. However, current clinical practice lacks accurate tools for predicting anastomotic stricture. This study aimed to develop a nomogram to predict anastomotic stricture in patients with rectal cancer who have undergone anterior resection.

Methods: 1542 eligible patients will be recruited for the study. Least absolute shrinkage selection operator (Lasso) analysis will be used to preliminarily select predictors. A prediction model will be constructed using multivariate logistic regression and presented as a nomogram. The performance of the nomogram will be evaluated using receiver operating characteristic (ROC) curves, calibration diagrams, and decision curve analysis (DCA). Internal validation will be conducted by assessing the model's performance on a validation cohort.

A Prediction Model of Anastomotic Stricture After Rectal Cancer

A Prediction Model of Anastomotic Stricture After Rectal Cancer: a Retrospective Cohort Analysis

Within six months after rectal cancer surgery, the patient was diagnosed with benign stricture of the rectal anastomosis

Within six months after rectal cancer surgery, the patient was not diagnosed with benign stricture of the rectal anastomosis

Northern Jiangsu People's Hospital

Clinical Professor

Cholangiocarcinoma

Carcinoma, Hepatocellular

Bile Duct Cancer

Intrahepatic Cholangiocarcinoma

Training cohort consists of the patients diagnosed with intrahepatic cholangiocarcinoma who collected from January 2010 to July 2021 retrospectively.

Internal validation cohort consists of the intrahepatic cholangiocarcinoma patients who enrolled from September 2021 of Qilu Hospital prospectively.

External validation cohort consists of the intrahepatic cholangiocarcinoma patients who enrolled from September 2021 of Shandong Province Hospital, Jinan Military General Hospital and Jinan Central Hospital prospectively.

Yanjing Gao, PhD.MD

The purpose of this study is to develop and validate a radiological nomogram including radiological characteristics, clinical risk factors, and medical history. And we aim to establish a noninvasive method for the diagnosis of intrahepatic cholangiocarcinoma (ICC), and to construct a differential diagnosis model for ICC and hepatocellular carcinoma (HCC) with higher sensitivity and accuracy.

In recent years, the incidence and mortality of intrahepatic cholangiocarcinoma (ICC) have been increasing worldwide. Due to the different treatment options for hepatocellular carcinoma (HCC) and ICC, accurate differential diagnosis is critical for subsequent treatment of patients. However, because of their similar CT image enhancement patterns, they are easily misdiagnosed by clinicians, leading to an incorrect treatment. Based on the above research background, our objective is to establish a noninvasive method for the diagnosis of ICC and and to construct a differential diagnosis model for ICC and HCC with higher sensitivity and accuracy.

Establishment of Scoring Model for Early and Differential Diagnosis of Intrahepatic Cholangiocarcinoma

Establishment of Scoring Model for Early Diagnosis and Differential Diagnosis of Intrahepatic Cholangiocarcinoma

The golden standard is the pathological biopsy.Compare the accuracy of the noninvasive model with the pathological biopsy.

Sensitivity of noninvasive model for diagnosis of intrahepatic cholangiocarcinoma.

Specificity of noninvasive model for diagnosis of intrahepatic cholangiocarcinoma.

Jinan Central Hospital

Shandong Provincial Hospital

Jinan Military General Hospital

Qilu Hospital of Shandong University

Liver Neoplasms

Liver Diseases

HCC patients receiving curative hepatic resection

whether HCC patients having tumor micronecrosis or not

observing whether HCC patients having tumor micronecrosis

Tingbo Liang, PhD

Qi Zhang, MD

Tingbo Liang, MD, PHD

The heterogeneity of hepatocellular carcinoma (HCC) leads to the unsatisfying predicting performance of current staging systems. HCC patients with pathological tumor micronecrosis have immunosuppressive microenvironment. We aimed to develop novel prognostic models by integrating micronecrosis to more precisely predict the survival of HCC patients after hepatectomy.

Prognostic Models for HCC Based on Tumor Micronecrosis

Development and Validation of Novel Models Including Tumor Micronecrosis for Predicting the Postoperative Survival of Patients With Hepatocellular Carcinoma

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
A Novel Online Calculator to Predict Long-term Survival and Recurrence Risk of Patients With Gastric Adenocarcinoma	NCT06337266	Gastric Cancer		-	Fujian Medical University
REM (Risk Of Endometrial Malignancy)	NCT01830192	Endometrial Dis...	Training set VERIFICATION SE...	45 Years - 80 Years	Campus Bio-Medico University
Usefulness of Ki67 Index in Hormone Receptor-positive Breast Cancer	NCT01273415	Breast Cancer		20 Years - 85 Years	Samsung Medical Center
Induction Chemotherapy of TPX in Nomogram-predicted High Risk Locoregionally Advanced Nasopharyngeal Carcinoma	NCT02786641	Nasopharyngeal ...	Docetaxel Cisplatin 1 Xeloda IMRT Cisplatin 2	18 Years - 65 Years	Sun Yat-sen University
A Recurrence Nomogram for Hepatoid Adenocarcinoma of the Stomach	NCT05274464	Gastric Cancer		-	Fujian Medical University
A Nomogram Model to Predict Central Lymphnode Metastasis in Thyroid Papillary Carcinoma	NCT05191927	Thyroid Papilla...	male	-	Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Radiomics-based Malnutrition for Cervical Cancer.	NCT05709769	Cervical Cancer Malnutrition	There are no in...	18 Years - 80 Years	Zhejiang Provincial People's Hospital
Predict the Risk of Axillary Metastases in Breast Cancer Patients With Axillary Ultrasound	NCT02992769	Breast Cancer F...		18 Years - 70 Years	Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
A Prediction Model of Anastomotic Stricture After Rectal Cancer	NCT06404554	Colorectal Canc... Rectal Cancer Anastomotic Ste...	without any int...	18 Years - 80 Years	Northern Jiangsu People's Hospital
Radiomics-based Malnutrition for Cervical Cancer.	NCT05709769	Cervical Cancer Malnutrition	There are no in...	18 Years - 80 Years	Zhejiang Provincial People's Hospital
A Prediction Model of Anastomotic Stricture After Rectal Cancer	NCT06404554	Colorectal Canc... Rectal Cancer Anastomotic Ste...	without any int...	18 Years - 80 Years	Northern Jiangsu People's Hospital
Establishment of Scoring Model for Early and Differential Diagnosis of Intrahepatic Cholangiocarcinoma	NCT05327907	Intrahepatic Ch...		18 Years - 80 Years	Qilu Hospital of Shandong University
REM (Risk Of Endometrial Malignancy)	NCT01830192	Endometrial Dis...	Training set VERIFICATION SE...	45 Years - 80 Years	Campus Bio-Medico University
Prognostic Models for HCC Based on Tumor Micronecrosis	NCT05837065	Hepatocellular ...	observing wheth...	18 Years - 90 Years	Zhejiang University

Spots Global Cancer Trial Database for nomogram

Every month we try and update this database with for nomogram cancer trials from around the world to help patients and their families find trials that might be right for them.
We offer this 100% free of charge and do not endorse any of the trials listed here, we hope it helps you or a loved one.

Spots Global Cancer Trial Database for nomogram

Every month we try and update this database with for nomogram cancer trials from around the world to help patients and their families find trials that might be right for them. We offer this 100% free of charge and do not endorse any of the trials listed here, we hope it helps you or a loved one.

Every month we try and update this database with for nomogram cancer trials from around the world to help patients and their families find trials that might be right for them.
We offer this 100% free of charge and do not endorse any of the trials listed here, we hope it helps you or a loved one.