Prediction Model for Multiple Pulmonary Nodules

Status

Completed

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT03795181

Enrollment

Registered

2019-01-07

Start date

2019-01-01

Completion date

2019-03-30

Last updated

2019-08-28

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Multiple Pulmonary Nodules

Keywords

multiple pulmonary nodules; predictive model

Brief summary

This study compares the sensitivity, specificity and accuracy of radiologists, thoracic surgeons and a predictive model (PKUM model) to discriminate malignancy from benign nodules in patients with multiple pulmonary nodules.

Detailed description

It is clinically difficult to diagnose and manage patients with multiple pulmonary nodules (MPNs). We have developed a web-based mathematic model (PKUM model) by using a multi-centric database from three institutions (Peking University People's Hospital, Haidian Section of Peking University Third Hospital, People's Hospital Affiliated to Hebei Medical University) to predict the probability of a nodule to be malignant in patients with MPNs. This prospectively observational study will recruit patients with MPNs between January 2019 and March 2019, allowing radiologists, surgeons, and a predictive model (PKUM model) to discriminate malignancy from benign nodules, and compare their sensitivity, specificity, and accuracy.

Interventions

None listed

Study design

Observational model

COHORT

Time perspective

PROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

18 Years to 90 Years

Healthy volunteers

Inclusion criteria

* Patients with newly discovered, 4-30 mm multiple pulmonary nodules shown on thoracic CT scans * Patients with at least two nodules resected for pathological evaluation

Exclusion criteria

* History of malignancy within 5 years * Presence of pneumonia or pleural effusion on thoracic CT scans * Patients with none or only one nodule resected * Patients with initial chemo-radiation therapy

Design outcomes

Primary

Measure	Time frame	Description
Performance of PKUM model	3 months	Area under receiver operating characteristic curve (AUC) of PKUM model in predicting the probability of a nodule to be malignant in patients with multiple pulmonary nodules.

Secondary

Measure	Time frame	Description
Comparison between PKUM model and clinicians	3 months	Comparison of sensitivity and specificity of radiologists, thoracic surgeons, and PKUM model in predicting the probability of a nodule to be malignant in patients with multiple pulmonary nodules.
Performance of PKUM model in equivocal nodules which is difficult to judge by clinicians	3 months	Sensitivity and specificity of PKUM model in predicting malignant probability of equivocal nodules judged by radiologists and thoracic surgeons.

Countries

China

Outcome results