Multimodal Prediction of Postoperative Prognosis After Partial Nephrectomy for Endophytic Renal Cell Carcinoma (PN-ProMM)

Development and External Validation of an Imaging-Clinical Multimodal Fusion Model for Predicting Postoperative Prognosis After Partial Nephrectomy in Patients With Endophytic Renal Cell Carcinoma

This retrospective observational cohort study aims to develop and externally validate an imaging-clinical multimodal fusion model for predicting postoperative prognosis in patients with endophytic renal cell carcinoma undergoing partial nephrectomy. Preoperative computed tomography imaging features, three-dimensional reconstruction-derived tumor characteristics, radiomics features, and clinical variables will be integrated using machine learning and deep learning approaches. The primary objective is to evaluate whether the multimodal model improves prediction of postoperative prognostic outcomes compared with single-modality models based on clinical or imaging features alone.

Study Overview

• Status: Active, not recruiting
• Conditions: Kidney Neoplasms; Renal Cell Carcinoma; Endophytic Renal Tumor; Postoperative Renal Function; Partial Nephrectomy Outcome
• Intervention / Treatment: Other: Imaging-clinical multimodal prognostic modeling

Detailed Description

Partial nephrectomy is a standard nephron-sparing treatment for localized renal cell carcinoma. However, postoperative functional and oncologic outcomes remain heterogeneous, especially in patients with endophytic renal tumors, in whom tumor complexity may increase surgical difficulty and affect postoperative recovery. Conventional clinical variables and anatomical scoring systems may not fully capture the multidimensional risk profile of these patients.

This study will retrospectively collect clinical, pathological, perioperative, and imaging data from patients with endophytic renal cell carcinoma who underwent partial nephrectomy. Preoperative multiphase computed tomography images will be used for radiomics feature extraction and deep learning-based image representation. Three-dimensional reconstruction-derived tumor features and conventional clinical variables will also be incorporated.

The study will develop and validate multimodal prediction models, including clinical models, radiomics models, deep learning imaging models, and imaging-clinical fusion models. Model performance will be assessed using discrimination, calibration, and clinical utility metrics, including the area under the receiver operating characteristic curve, calibration curves, decision curve analysis, and external validation across independent cohorts.

• Study Type: Observational
• Enrollment (Actual): 406

Contacts and Locations

Study Locations

• China
  • Tianjin Municipality
    • Tianjin, Tianjin Municipality, China
      • Tianjin Medical University Second Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

The study population will include adult patients with endophytic renal cell carcinoma who underwent partial nephrectomy at participating medical centers and had available preoperative imaging, clinical, pathological, perioperative, and postoperative follow-up data. Patients will be identified retrospectively from institutional databases and electronic medical records.

Description

Inclusion Criteria:

• Patients diagnosed with renal cell carcinoma. Patients with endophytic renal tumors based on preoperative imaging assessment. Patients who underwent partial nephrectomy. Available preoperative contrast-enhanced computed tomography images. Available clinical, pathological, perioperative, and postoperative follow-up data.

Age 18 years or older at the time of surgery.

Exclusion Criteria:

• Patients who underwent radical nephrectomy as the primary surgical treatment. Patients with missing or poor-quality preoperative imaging data. Patients with incomplete key clinical, pathological, or follow-up information. Patients with hereditary renal cancer syndromes. Patients with bilateral renal tumors or solitary kidney. Patients who received neoadjuvant systemic therapy before partial nephrectomy.

Study Plan

How is the study designed?

Number of groups / cohorts

4

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Development Cohort; Patients with endophytic renal cell carcinoma who underwent partial nephrectomy and were included for model development and internal validation.	Other: Imaging-clinical multimodal prognostic modeling; Preoperative CT imaging features, radiomics features, three-dimensional reconstruction-derived features, and clinical variables will be retrospectively analyzed to develop and validate a multimodal model for predicting postoperative prognosis after partial nephrectomy. No intervention will be assigned to participants.
External Validation Cohort 1; An independent cohort of patients with endophytic renal cell carcinoma who underwent partial nephrectomy and were used for external validation of the prediction model.	Other: Imaging-clinical multimodal prognostic modeling; Preoperative CT imaging features, radiomics features, three-dimensional reconstruction-derived features, and clinical variables will be retrospectively analyzed to develop and validate a multimodal model for predicting postoperative prognosis after partial nephrectomy. No intervention will be assigned to participants.
External Validation Cohort 2; An independent validation cohort used to evaluate the generalizability of the multimodal prognostic prediction model.	Other: Imaging-clinical multimodal prognostic modeling; Preoperative CT imaging features, radiomics features, three-dimensional reconstruction-derived features, and clinical variables will be retrospectively analyzed to develop and validate a multimodal model for predicting postoperative prognosis after partial nephrectomy. No intervention will be assigned to participants.
External Validation Cohort 3; An additional independent validation cohort used to assess model robustness across different patient populations or institutions.	Other: Imaging-clinical multimodal prognostic modeling; Preoperative CT imaging features, radiomics features, three-dimensional reconstruction-derived features, and clinical variables will be retrospectively analyzed to develop and validate a multimodal model for predicting postoperative prognosis after partial nephrectomy. No intervention will be assigned to participants.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Modified Pentafecta Achievement After Partial Nephrectomy	Modified pentafecta achievement will be defined as the simultaneous fulfillment of predefined postoperative outcome criteria, including negative surgical margin, absence of major postoperative complications, preservation of renal function, absence of significant perioperative adverse events, and absence of early tumor recurrence or other prespecified unfavorable outcomes. Patients who do not meet all criteria will be classified as modified pentafecta failure.	From the date of partial nephrectomy to the last available postoperative follow-up, up to 12 months after surgery.

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Postoperative eGFR Decline Greater Than 20%	A clinically significant decline in renal function will be defined as a decrease in estimated glomerular filtration rate greater than 20% compared with the preoperative baseline value.	From baseline to 3-12 months after partial nephrectomy
Major Postoperative Complications	Major postoperative complications will be defined as Clavien-Dindo grade III or higher complications occurring within the predefined postoperative period.	Within 30 or 90 days after partial nephrectomy
Positive Surgical Margin	Positive surgical margin will be determined according to the postoperative pathological report.	At final pathological evaluation after partial nephrectomy
Area Under the Receiver Operating Characteristic Curve of the Multimodal Model	The discriminatory performance of the multimodal model for predicting modified pentafecta achievement after partial nephrectomy will be evaluated using the area under the receiver operating characteristic curve.	At completion of model development and external validation, using postoperative outcome data up to 12 months after surgery.

Collaborators and Investigators

• Sponsor: Tianjin Medical University Second Hospital

Study record dates

Study Major Dates

• Study Start (Actual): January 1, 2026
• Primary Completion (Actual): May 30, 2026
• Study Completion (Estimated): December 1, 2026

Study Registration Dates

• First Submitted: July 4, 2026
• First Submitted That Met QC Criteria: July 10, 2026
• First Posted (Actual): July 13, 2026

Study Record Updates

• Last Update Posted (Actual): July 13, 2026
• Last Update Submitted That Met QC Criteria: July 10, 2026
• Last Verified: July 1, 2026

More Information

Terms related to this study

• Keywords: Partial nephrectomy; External validation; Deep learning; Renal function; Pentafecta; Radiomics; Three-dimensional reconstruction; Endophytic renal cell carcinoma; Multimodal prediction model; Postoperative prognosis
• Additional Relevant MeSH Terms: Urogenital Diseases; Urogenital Neoplasms; Neoplasms by Site; Neoplasms; Male Urogenital Diseases; Kidney Diseases; Urologic Diseases; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Neoplasms by Histologic Type; Neoplasms, Glandular and Epithelial; Adenocarcinoma; Urologic Neoplasms; Carcinoma; Carcinoma, Renal Cell; Kidney Neoplasms
• Other Study ID Numbers: PN-ProMM-KY2025391

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: Individual participant data will not be publicly shared because of privacy, ethical, and institutional data-use restrictions. De-identified data may be made available from the corresponding investigator upon reasonable request and with appropriate institutional approval, where applicable.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No