Using Clinical Risk Models for Lung Nodule Classification

Deppen, Stephen A.; Grogan, Eric L.

doi:10.1053/j.semtcvs.2015.04.001

Cited by 11 publications

(8 citation statements)

References 21 publications

(24 reference statements)

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“…The model that combined numerical CACs and clinical factors (gender, type of the maximum nodule, location of the maximum nodule) exhibited the highest AUC in our study (AUC = 0.913). The Mayo model is a well-recognized model that was commonly used in the screening of lung cancer for patients who had an uncertain pulmonary nodule under 3 cm found by radiographic approach without tissue diagnosis ( 24 ). This model included smoking history, age, nodule size, and the time from quit smoking, has achieved an AUC of 0.79 ( 25 ).…”

Section: Discussionmentioning

confidence: 99%

Circulating Genetically Abnormal Cells Add Non-Invasive Diagnosis Value to Discriminate Lung Cancer in Patients With Pulmonary Nodules ≤10 mm

Zheng

et al. 2021

Front. Oncol.

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BackgroundLung cancer screening using low-dose computed tomography (LDCT) often leads to unnecessary biopsy because of the low specificity among patients with pulmonary nodules ≤10 mm. Circulating genetically abnormal cells (CACs) can be used to discriminate lung cancer from benign lung disease. To examine the diagnostic value of CACs in detecting lung cancer for patients with malignant pulmonary nodules ≤10 mm.MethodsIn this prospective study, patients with pulmonary nodules ≤10 mm who were detected at four hospitals in China from January 2019 to January 2020 were included. CACs were detected using fluorescence in-situ hybridization. All patients were confirmed as lung cancer or benign disease by further histopathological examination. Multivariable logistic regression models were established to detect the presence of lung cancer using CACs and other associated characteristics. Receiver operating characteristic analysis was used to evaluate the performance of CACs for lung cancer diagnosis.ResultsOverall, 125 patients were included and analyzed. When the cutoff value of CACs was >2, the sensitivity and specificity for lung cancer were 70.5 and 86.4%. Male (OR = 0.330, P = 0.005), maximum solid nodule (OR = 2.362, P = 0.089), maximum nodule located in upper lobe (OR = 3.867, P = 0.001), and CACs >2 (OR = 18.525, P < 0.001) met the P < 0.10 criterion for inclusion in the multivariable models. The multivariable logistic regression model that included the dichotomized CACs (>2 vs. ≤2) and other clinical factors (AUC = 0.907, 95% CI = 0.842–0.951) was superior to the models that only considered dichotomized CACs or other clinical factors and similar to the model with numerical CACs and other clinical factors (AUC = 0.913, 95% CI = 0.850–0.956).ConclusionCACs presented a significant diagnostic value in detecting lung cancer for patients with pulmonary nodules ≤10 mm.

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Section: Discussionmentioning

confidence: 99%

Circulating Genetically Abnormal Cells Add Non-Invasive Diagnosis Value to Discriminate Lung Cancer in Patients With Pulmonary Nodules ≤10 mm

Zheng

et al. 2021

Front. Oncol.

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“…3 Noninvasive biomarkers are urgently needed to reduce false positives with screening LDCT and to improve risk stratification in those identified to have indeterminate nodules. Biofluids (sputum, blood, urine) have also been considered to help identify subjects who should undergo LDCT.…”

Section: Introductionmentioning

confidence: 99%

Clinical Utility of Chromosomal Aneusomy in Individuals at High Risk of Lung Cancer

Barón

Kako

Feser

et al. 2017

Journal of Thoracic Oncology

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Introduction Low dose CT screening for lung cancer has a high false positive rate with frequent discovery of indeterminate pulmonary nodules. Noninvasive biomarkers are needed to reduce false positives and improve risk stratification. A retrospective longitudinal evaluation was performed to assess chromosomal aneusomy in sputum via fluorescence in situ hybridization (CA-FISH) in four nested case-control studies. Methods ROC analysis resulted in two grouped cohorts: High Risk (CO High Risk and CO Nodule; 68 Cases, 69 controls) and Screening (ACRIN/NLST and PLuSS; 97 Cases, 185 controls). The CA-FISH assay was a 4-target DNA panel encompassing EGFR and MYC genes, and the 5p15 and centromere 6 regions or the FGFR1 and PIK3CA genes. A 4-category scale: normal, probably normal, probably abnormal and abnormal was applied. Sensitivity, specificity, and positive and negative likelihood ratios (LR+, LR−) (with 95% CI) were estimated for each cohort. Results Sensitivity and specificity were, respectively, 0.67 (0.55, 0.78) and 0.94 (0.85, 0.98) for High Risk subjects and 0.20 (0.13, 0.30) and 0.84 (0.78, 0.89) for Screening subjects. LR+ and LR− were, respectively, 11.66 (4.44, 30.63) and 0.34 (0.24, 0.48) for High Risk; and 1.36 (0.81, 2.28) and 0.93 (0.83, 1.05) for Screening subjects. Conclusion The high positive likelihood ratio of sputum CA-FISH indicates it could be a useful adjunct to LDCT for lung cancer in high risk settings. For screening, however, its low positive likelihood ratio limits clinical utility. Prospective assessment of CA-FISH in the incidentally-identified indeterminate nodule setting is ongoing in the Colorado Pulmonary Nodule Biomarker Trial.

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“…Next, we limited the analysis to individuals presenting with IPNs nodules between 6 and 30 mm in diameter. In this more clinically relevant patient population 38 the AUC for the Mayo model was 0.567, improving to 0.943 when combining Mayo with CYFRA 21−1 measured by FSA-CIR. Here, the PPV by the FSA-CYFRA 21−1 is 99%.…”

Section: Resultsmentioning

confidence: 87%

Compensated Interferometry Measures of CYFRA 21–1 Improve Diagnosis of Lung Cancer

et al. 2019

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Diagnosis of lung cancer patients with indeterminate pulmonary nodules (IPNs) presents a significant clinical challenge, with morbidity and management costs of $28 billion/year. We show that a quantitative free-solution assay (FSA), coupled with a compensated interferometric reader (CIR), improves the diagnostic performance of CYFRA 21–1 as a lung cancer biomarker. FSA-CIR is a rapid, mix-and-read, isothermal, label- and enzyme-free, matrix-insensitive, and target and probe-agnostic assay. Operating FSA-CIR at ∼40, 0.75 μL samples/day delivered a serum CYFRA 21–1 limit of quantification (LOQ) of 81 pg/mL with intra-assay and interassay CVs of 4.9% and 9.6% for four-day replicate determinations. Blinded analysis of a 225 patient cohort, consisting of 75 nonmalignant nodules, 45 adenocarcinomas, 44 squamous cell carcinomas, and 61 small cell lung cancers, gave a clear separation of cases and controls, not observed in the Cobas ECL analysis. The area under the curve (AUC) for the Mayo model increased from 0.595 to 0.923 when combined with the FSA-CIR CYFRA 21–1 measurements. In a population with nodules between 6 and 30 mm, the AUC increased from 0.567 to 0.943. In this subgroup, the positive predictive value (PPV) for all tumors by the CYFRA 21–1 assay was 98.7%. Our results demonstrate increased performance of the CYFRA 21–1 assay using FSA-CIR and represents a proof of concept for redefining the performance characteristics of this important candidate biomarker.

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Using Clinical Risk Models for Lung Nodule Classification

Cited by 11 publications

References 21 publications

Circulating Genetically Abnormal Cells Add Non-Invasive Diagnosis Value to Discriminate Lung Cancer in Patients With Pulmonary Nodules ≤10 mm

Circulating Genetically Abnormal Cells Add Non-Invasive Diagnosis Value to Discriminate Lung Cancer in Patients With Pulmonary Nodules ≤10 mm

Clinical Utility of Chromosomal Aneusomy in Individuals at High Risk of Lung Cancer

Compensated Interferometry Measures of CYFRA 21–1 Improve Diagnosis of Lung Cancer

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