Skip to content

Derivation and Validation of a Scoring System to Distinguish Cryptococcosis and Adenocarcinoma in Pulmonary Nodules

Derivation and Validation of a Scoring System to Distinguish Cryptococcosis and Adenocarcinoma in Pulmonary Nodules: a Multicenter Observational Study.

Status
UNKNOWN
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT04554875
Enrollment
1000
Registered
2020-09-18
Start date
2019-01-01
Completion date
2021-07-01
Last updated
2020-09-18

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

Conditions

Cryptococcosis, Lung Adenocarcinoma

Brief summary

Pulmonary cryptococcosis often manifests as isolated or multiple nodules, easily mimicking lung cancer clinically and radiologically, which ascribes the poor sensitivity of Cryptococcus culture and rarely positive of Cryptococcal antigen test in the absence of disseminated disease. Therefore, the aim of this study was to develop a predictive scoring system from the perspective of available clinical indicators, to differentiate cryptococcosis from adenocarcinoma in pulmonary nodules, which might be beneficial for the delicacy management of pulmonary nodules.

Detailed description

Nodule is generally defined as a small, approximately spherical in morphology, circumscribed focus of abnormal tissue on computed tomography (CT) and no greater than 3cm in maximum diameter. Pulmonary nodules are not uncommon. A systematic review of CT screening lung cancer trials noted that a lung nodule was detected in up to 51% of study participants. More than 95% of detected nodules are benign and have a wide variety of causes, including infections, granulomatous disease, hamartomas, arteriovenous malformations, round atelectasis, and lymph nodes. Pulmonary cryptococcosis is caused by Cryptococcus spp., a ubiquitous budding yeast-like basidiomycete that is endemic in many countries. Previously, Pulmonary cryptococcosis was thought to be an important opportunistic invasive mycosis in immunocompromised patients, such as AIDS, immunosuppressor used after organ transplantation, but it is also common in immunocompetent patients. Pulmonary cryptococcosis often manifests as isolated or multiple nodules, easily mimicking lung cancer clinically and radiologically, which ascribes the poor sensitivity of Cryptococcus culture and rarely positive of Cryptococcal antigen test in the absence of disseminated disease. Therefore, the aim of this multicenter observational study was to develop a predictive scoring system from the perspective of available clinical indicators, to differentiate cryptococcosis from adenocarcinoma in pulmonary nodules, which might be beneficial for the delicacy management of pulmonary nodules.

Interventions

DIAGNOSTIC_TESTA scoring system

The scoring system was used to rate score patients.

Sponsors

Shanghai Pulmonary Hospital, Shanghai, China
Lead SponsorOTHER

Study design

Observational model
CASE_CONTROL
Time perspective
RETROSPECTIVE

Eligibility

Sex/Gender
ALL

Inclusion criteria

* Patients with pulmonary nodules * Evidence of pathological diagnosis for cryptococcosis or adenocarcinoma * Data on high-resolution computed tomography (HRCT)

Exclusion criteria

* Pulmonary nodules greater than 3cm in maximum diameter * Lack of data on HRCT

Design outcomes

Primary

MeasureTime frameDescription
Area under receiver operating characteristic curveup to 24 weeksArea under Receiver Operating Characteristic (ROC) curve was used to identify the diagnostic value of the scoring system.

Secondary

MeasureTime frameDescription
Sensitivity of the scoring systemup to 24 weeksSensitivity of the scoring system was used to assess the true positive rate of pulmonary cryptococcosis
Specificity of the scoring systemup to 24 weeksSpecificity of the scoring system was used to assess the true negative rate of pulmonary cryptococcosis

Countries

China

Contacts

Primary ContactJin-fu Xu, MD
jfxucn@163.com+86 13321922898

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026