Lung Nodules and Prediction Models in Lung Cancer

CONTENTS:

3.2.5 Models for Predicting Malignancy in a Solitary Pulmonary Nodule or lung nodules
i. A Bayesian Model
ii.The Mayo Clinic Model
iii.The Veteran’s Affairs Cooperative Clinical Model
iv. Pan-Canadian Early Detection of Lung Cancer (Brock University) Model
3.2.6 The 2005 Fleischner Society Guidelines for Management of SPNs
3.2.7 Tissue Diagnosis of Focal Lung Abnormalities

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Did you hear about the dyslexic devil worshipper? He sold his soul to Santa!

3.2.5 Models for Predicting Malignancy in a Solitary Pulmonary Nodule

It is likely that clinical assessment of lung nodules and the use of ‘predictive models’ that combine radiological and clinical features will be complementary.

Predictive models may be helpful for solitary lung nodules that are between 8 mm to 30 mm as usually nodules >30 mm are surgically resected. However, in nodules ≤ 8 mm (without documented growth) serial CT scans will follow.

i. A Bayesian Model

In 1986, Cummings and colleagues developed a predictive model that used likelihood ratios (LRs) to estimate the probability of malignancy in a lung nodule. The likelihood ratios (LRs) assessed factors including patient age, nodule size, smoking history and overall prevalence of malignancy in the patient group. The likelihood of malignancy is then calculated by multiplying the LRs, and the probability of malignancy is calculated from the odds.

ii. The Mayo Clinic Model

In 1997, Swensen and colleagues used data from chest radiographic findings to estimate the probability of malignancy in a SPN using the Mayo Clinic model. Six independent predictors of cancer included older age, smoking history, previous history of cancer, nodule diameter, nodule spiculation, and upper lobe location.

iii. The Veteran’s Affairs Cooperative Clinical Model

In 2007, Gould and colleagues developed their clinical predictive model (Veteran’s Administration Cooperative). This model was derived using data from CT and / or PET in 375 veterans who were current or former smokers and lung nodules who had SPNs measuring between 7 mm to 30 mm. They found that predictors of malignant SPNs included older age, smoking history, larger nodule diameter and time since stopping smoking. This model showed good agreement between the predicted probability and the observed frequency of malignant SPNs. The model is considered to be useful in high-risk populations, but has not been validated in non-smoking, low-risk populations.

My doctor told me that, ‘1 out of every 3 people who start smoking will eventually die.’ The other two apparently become immortal!

iv. Pan-Canadian Early Detection of Lung Cancer (Brock University) Model

In 2013, McWilliams and colleagues analyzed the data from two patient groups who were undergoing low-dose CT (LDCT) lung screening. The patients studied included participants in the Pan-Canadian Early Detection of Lung Cancer Study (PanCan) and the chemoprevention trials from the British Columbia Cancer Agency (BCCA), sponsored by the U.S. National Cancer Institute (NCI).

The clinical outcome of all lung nodules of any size were followed, and multivariable logistic-regression models were developed to predict the probability of lung cancer. Predictors of lung cancer identified in 2,961 patients with SPNs included female sex, older age, family history of lung cancer, emphysema, larger nodule size, upper lobe nodule location, part-solid nodule type, lower nodule number and spiculation of the lung nodule edges. The increased incidence of adenocarcinoma, which is more likely to present as a sub-solid and partly solid nodule, gives this model a distinct advantage over the others. The negative predictive value of this model was consistently high (99 %), the sensitivity ranged from 60 % to 86 %. The analysis tools are available on the following sites:

For the Brock University Lung Cancer Risk Calculator click here.

Lot’s of information – time for a coffee and a cheeky check on facebook!

I don’t watch soap operas anymore. I have facebook, there’s a new episode every five minutes.

I’ve changed my name on Facebook to ‘Nobody’ and then I ‘Like’ a lot of posts…work it out people!

3.2.6 The 2005 Fleischner Society Guidelines for Management of SPNs

In 2005, MacMahon and colleagues reported on the Fleischner Society guidelines for the management of small pulmonary nodules detected by CT scan, present in up to 51% of smokers aged 50 years or older.

These are some of the key facts from the Fleischner Society Guidelines:

Approximately half of all smokers over 50 years of age have at least one lung nodule at the time of an initial lung CT screening examination.
Approximately 10% of screening subjects develop a new lung nodule during a 1-year period.
The probability that a given nodule is malignant increases according to its size.
The percentage of all nodules smaller than 4 mm, even in smokers, which will develop into lung cancers is very low (<1%), but for those in the 8-mm size range, the percentage is approximately 10% to 20%.
Cigarette smokers are at greater risk for lung cancers, and malignant nodules in smokers grow faster than do those in non-smokers.
The cancer risk for smokers increases in proportion to the degree and duration of exposure to cigarette smoke.

Features of Lung Nodules

Certain features of lung nodules correlate with risk of developing malignancy and include cell type and growth rate.
Small, ‘ground-glass’ opacity (non-solid) lung nodules that have malignant histopathologic features are those that grow very slowly, with a mean volume doubling-time of the order of 2 years.
Solid lung cancers, tend to grow more rapidly, with a mean volume doubling time on the order of 6 months.
The growth rate of ‘partly solid’ lung nodules tends to fall between these extremes, and this particular morphologic pattern is highly predictive of adenocarcinoma.
Increasing patient age correlates with increasing likelihood of malignancy.
Lung cancer is uncommon in patients younger than 40 years and is rare in those younger than 35 years.
In an older age group, although the likelihood of lung cancer increases, surgical intervention carries greater risks.
The likelihood of a small nodule evolving into a cancer that will cause premature death is a lesser concern as comorbidity increases and predicted survival decreases with advancing years.

In 2013, Naidich and colleagues updated the Fleischner Society recommendations (for incidentally detected solid nodules) by proposing their recommendations specifically aimed at ‘sub-solid’ nodules. Peripheral lung adenocarcinomas represent the most common type of lung cancer in this group.

So the most important factors in predicting malignancy risk in solitary pulmonary nodules are…..

Larger size, part-solid type and spiculated edges of nodules are the main ones.

..and smoking – try and stop, people – it’s never too late.

Figure 3.6 The 2005 Fleischner Society Guidelines for Management of SPNs

3.2.7 Tissue Diagnosis of Focal Lung Abnormalities

CT-guided fine-needle aspiration cytology (FNAC) has advanced the early diagnosis of small pulmonary nodules larger than 5 mm in diameter. FNAC is of particular value in patients who are not amenable to surgery because of comorbidities. In patients who are candidates for surgery, FNAC may diagnose benign disease and save the patient from surgery.

The technique of FNAC is performed with fluoroscopic, CT, or ultrasonographic (US) guidance. Fluoroscopy allows for the FNAC to be performed quickly and with the patient in a seated position.

Interpretation of the FNAC specimens falls into one of three categories:

malignant,
specific benign, or
non-specific benign.

CT allows for the localization of smaller lung nodules. Ultrasound may localize lung nodules that abut the pleura.

There are some contraindications to the process of FNAC that include the inability of the patient to hold their breath or to lie immobile on the CT table for more than 30 minutes, or to withhold coughing. Other clinical contraindications include bleeding disorders, severe emphysema, having had a previous pneumonectomy, severe hypoxemia, pulmonary hypertension, or nodules that may not be accessed due to their small size or location.

Sensitivity and Specificity of FNAC

In the diagnosis of malignancy in lung nodules, FNAC has a sensitivity of 86.0 % and a specificity of 98.8 %. In nodules between 5 to 7 mm in diameter, sensitivity is only 50%. Sensitivity of FNAC is also lower (12%) in patients with lymphoma and, for this reason, core biopsy (sensitivity, 62%) is recommended if there is the possibility of a lung lymphoma. Core needle biopsy (CNB) is used for cases of benign disease and where FNAC is equivocal.

There are a number of benign conditions that may be detected as lung nodules or lung masses on CT imaging and that may require cytological or histological assessment to exclude lung cancer.

Who are the coolest hospital staff? The Ultrasound people, of course.

References:

Cummings SR, Lillington GA, Richard RJ. (1986). Estimating the probability of malignancy in solitary pulmonary nodules. A Bayesian approach. Am Rev Respir Dis. 134(3), 449. (Retrieved 5^th Feb 2015): http://www.ncbi.nlm.nih.gov/pubmed?term=3752700

Swensen SJ, Silverstein MD, Ilstrup DM, Schleck CD, Edell ES. (1997). The probability of malignancy in solitary pulmonary nodules. Application to small radiologically indeterminate nodules. Arch Intern Med. 157(8),849. (Retrieved 5^th Feb 2015): http://archinte.jamanetwork.com/article.aspx?articleid=623212

More references for this section are on this page.

Patient Information:

Brock University Lung Cancer Risk Calculators (Retrieved 13^th April 2015): http://www.brocku.ca/lung-cancer-risk-calculator

Medscape Solitary Pulmonary Nodule Malignancy Risk Calculator (Mayo Clinic model). (Retrieved 13^th April 2015): http://reference.medscape.com/calculator/solitary-pulmonary-nodule-risk

More patient information for this section is on this page.

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