A retrospective study of volume doubling time in surgically resected non-small cell lung cancer

Lung cancer volume doubling time by computed tomography: A systematic review and meta-analysis

AIM

Lung cancer growth rate influences screening strategies and treatment decisions. This review aims to provide an overview of primary lung cancer growth rate, quantified by volume doubling time (VDT) through computed tomography (CT) measurement.

METHODS

Using PRISMA-DTA guideline, PubMed, EMBASE, and Web of Science were searched until March 2024 for studies reporting CT-measured VDT of pathologically confirmed primary lung cancer before intervention. Summary data were extracted from published reports by two independent researchers. Primary outcomes were pooled mean VDT of lung cancer by nodule type and histology, distribution of indolent lung cancer (defined as VDT>400 days or negative), and correlated factors.

RESULTS

Thirty-three studies were eligible, comprising 3959 patients with primary lung cancer (mean age range:57.6-77.0 years; 60.0 % men). The pooled mean VDT for solid, part-solid, and nonsolid lung cancer were 207, 536, and 669 days, respectively (p < 0.001). When stratified by histology within solid lung cancer, the pooled mean VDT of adenocarcinoma, squamous cell carcinoma, small cell lung cancer, and others were 223, 140, 73, and 178 days, respectively (p < 0.001). Indolent lung cancer was observed in 34.9 % of lung cancer, predominantly in adenocarcinoma (68.9 %). Adenocarcinoma was associated with slower growth, whereas factors such as tumor size, solidity, TNM staging, and smoking history were positively associated with growth rates.

CONCLUSIONS

Pooled mean VDT of solid lung cancer was approximately 207 days, demonstrating significant variability in histology yet remaining under the 400-day referral threshold. Key predictors of growth rate include histology, size, solidity, and smoking history, essential for tailoring early intervention strategies.

TRIAL REGISTRATION NUMBER

CRD42023408069.

Impact on Prognosis of Stage I Non-Small Cell Lung Cancer Secondary to Delays in Diagnostic Workup

Background Diagnostic workup of small pulmonary nodules often requires follow-up CT scans to confirm nodule growth before invasive diagnostics or treatment. Purpose To confirm prior results from the International Early Lung Cancer Action Program (I-ELCAP) on quantifying decreases in lung cancer prognosis by using two large databases, the National Lung Screening Trial (NLST) and International Association for the Study of Lung Cancer (IASLC). Materials and Methods In this retrospective study, a model was developed to predict cure rates based on size of solid nodules using the NLST (August 2002 to summer 2007) and IASLC (January 2011 to December 2019) databases, focusing on stage I non-small cell lung cancer (NSCLC). Kaplan-Meier methods were used to calculate 10-year lung cancer-specific survival and 5-year overall survival rates for different tumor sizes. Tumor diameter increases after 90-, 180-, and 365-day delays were estimated using volume doubling times (VDTs) of 60, 120, and 240 days corresponding to fast, moderate, and slow tumor growth. Initial and delayed lung cancer cure rates were assessed across nine scenarios of time delays and tumor growth rates and compared with the previous results of the I-ELCAP database. Results Using regression models based on 166 NLST and 22 590 IASLC patients with NSCLC, 10-year lung cancer-specific survival and 5-year overall survival, respectively, for tumors 4.0-20.0 mm in diameter were estimated. For a 20.0-mm tumor with a 60-day VDT in the NLST database, the lung cancer-specific survival decreased from 83.4% to 76.5%, 66.8%, and 32.3% after 90, 180, and 365 days, respectively. The IASLC database showed similar decreases in 5-year overall survival, from 81.2% to 73.4%, 62.4%, and 23.3% after 90, 180, and 365 days, respectively. Comparison across NLST, IASLC, and I-ELCAP databases revealed minor variations in lung cancer cure rates between 79.9% and 83.4%, with reductions of 6.9%-8.3% after a 180-day delay with a 120-day VDT. Conclusion The NLST and IASLC databases confirmed prior estimates from the I-ELCAP database for the decrease in lung cancer prognosis due to diagnostic delays. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Park and Lee in this issue.

Predicting Tumor Volume Doubling Time and Progression-Free Survival in Untreated Patients from Patient-Derived-Xenograft (PDX) Models: A Translational Model-Based Approach

Tumor volume doubling time (TVDT) has been shown to be a potential surrogate marker of biological tumor activity. However, its availability in clinics is strongly limited due to ethical and practical reasons, as its assessment requires at least two subsequent tumor volume measurements in untreated patients. Here, a translational modeling framework to predict TVDT distributions in untreated cancer patient populations from tumor growth data in patient-derived xenograft (PDX) mice is proposed. Eleven solid cancer types were considered. For each of them, a set of tumor growth studies in PDX mice was selected and analyzed through a mathematical model to characterize the distribution of the exponential tumor growth rate in mice. Then, assuming an exponential growth of the tumor mass in humans, the growth rates were scaled from PDX mice to humans through an allometric scaling approach and used to predict TVDTs in untreated patients. A very good agreement was found between model predicted and clinically observed TVDTs, with 91% of the predicted TVDT medians fell within 1.5-fold of observations. Further, exploiting the intrinsic relationship between tumor growth dynamics and progression free survival (PFS), the exponential growth rates in humans were used to generate the expected PFS curves in absence of anticancer treatment. Predicted curves were extremely close to published PFS data from studies involving patient cohorts treated with supportive care or low effective therapies. The proposed approach shows promise as a potential tool to increase knowledge about TVDT in humans without the need of directly measuring tumor dimensions in untreated patients, and to predict PFS curves in untreated patients, that could fill the absence of placebo-controlled arms against which to compare treaded arms during clinical trials. However, further validation and refinement are needed to fully assess its effectiveness in this regard.

Barriers to Timely Lung Cancer Care in Early Stage Non-Small Cell Lung Cancer and Impact on Patient Outcomes

BACKGROUND

Optimal time to treatment for early-stage lung cancer is uncertain. We examined causes of delays in care for Veterans who presented with early-stage non-small cell lung cancer (NSCLC) and whether workup time was associated with increased upstaging or all-cause mortality.

METHODS

We performed a retrospective analysis of Veterans referred to our facility with radiographic stage I or II NSCLC between January 2013 to December 2017, with follow-up through October 2021. Patient demographics, tumor characteristics, time intervals of care, and reasons for delays were collected. Guideline concordance (GC) was defined as treatment within 14 weeks of abnormal image. Multivariable analyses were performed to determine association between delays in care, survival, and upstaging.

RESULTS

Data from 203 Veterans were analyzed. Median time between abnormal imaging to treatment was 17.7 weeks (IQR 12.7-26.6). Only 33% of Veterans received GC care. Most common patient-related delays were: intercurrent hospitalization/comorbidity (23%), no-shows (16%) and inability to reach Veteran (17%). Most common system-related delay: lack of scheduling availability (25%). Delays associated with upstaging: transportation issues, request for coordination of appointments, and unforeseen appointment changes. Rates of upstaging did not differ between GC and discordant groups (P = .6). GC care was not an independent predictor of mortality. Post-hoc, treatment within 8 weeks was associated with lower rates of upstaging (P = .05).

CONCLUSION

Although GC care did not impact survival or upstaging for early-stage NSCLC, shorter timeframes may be beneficial. Modifiable delays in care exist which may be addressed at an institutional level to improve timeliness of care.

Observational Study of the Natural Growth History of Peripheral Small-Cell Lung Cancer on CT Imaging

BACKGROUND

This study aimed to investigate the natural growth history of peripheral small-cell lung cancer (SCLC) using CT imaging.

METHODS

A retrospective study was conducted on 27 patients with peripheral SCLC who underwent at least two CT scans. Two methods were used: Method 1 involved direct measurement of nodule dimensions using a calliper, while Method 2 involved tumour lesion segmentation and voxel volume calculation using the "py-radiomics" package in Python. Agreement between the two methods was assessed using the intraclass correlation coefficient (ICC). Volume doubling time (VDT) and growth rate (GR) were used as evaluation indices for SCLC growth, and growth distribution based on GR and volume measurements were depicted. We collected potential factors related to imaging VDT and performed a differential analysis. Patients were classified into slow-growing and fast-growing groups based on a VDT cut-off point of 60 days, and univariate analysis was used to identify factors influencing VDT.

RESULTS

Median VDT calculated by the two methods were 61 days and 71 days, respectively, with strong agreement. All patients had continuously growing tumours, and none had tumours that decreased in size or remained unchanged. Eight patients showed possible growth patterns, with six possibly exhibiting exponential growth and two possibly showing Gompertzian growth. Tumours deeper in the lung grew faster than those adjacent to the pleura.

CONCLUSIONS

Peripheral SCLC tumours grow rapidly and continuously without periods of nongrowth or regression. Tumours located deeper in the lung tend to grow faster, but further research is needed to confirm this finding.

Radiological evidence of rapid growth acceleration of a small part solid nodule found to be large-cell carcinoma of the lung

BACKGROUND

With the widespread use of low-dose computed tomography for lung cancer screening, the detection rate of pulmonary lesions manifesting as ground-glass opacities (GGOs) has been increasing dramatically. The volume doubling time (VDT) has been introduced in clinical practice to monitor the potential growth rate of GGOs during long-term follow-up periods.

CASE PRESENTATION

A 72-year-old never-smoker female diagnosed with mixed GGO manifested abruptly accelerated growth with sudden decreased VDT from 400 to 36 days. A thoracoscopic left lower lobectomy with mediastinal lymph node dissection was performed, and the diagnosis was stage IB large-cell neuroendocrine carcinoma (LCNEC). Next-generation sequencing of the tumor highlights an EML4-ALK gene fusion.

CONCLUSIONS

The LCNEC may present as GGO with longer VDT in the early stage. VDT should calculate by the whole size either on the entire tumor diameter or on consolidation diameter. It is recommended that meticulous long-term follow-up with dynamic VDT monitoring may help select high-risk GGOs performing timely semi-elective surgical resection in clinical practice.

Growth Rates of Pulmonary Carcinoid Tumors and Hamartomas

BACKGROUND

Pulmonary nodule growth is often measured by volume doubling time (VDT), which may guide management. Most malignant nodules have a VDT of 20 to 400 days, with longer VDTs typically observed in indolent nodules. We assessed the utility of VDT in differentiating pulmonary carcinoids and hamartomas.

METHODS

A review was performed from January 2012 to October 2021 to identify patients with pathologic diagnoses and at least 2 chest computed tomography scans obtained 6 or more months apart. Visualization software was used to segment nodules and calculate diameter and volume. Volume doubling time was calculated for scans with 1-mm slices. For the remainder, estimated nodule volume doubling time (eVDT) was calculated using nodule diameter. Volume doubling times/eVDTs were placed into growth categories: less than 400 days; 400-600 days; and more than 600 days.

RESULTS

Sixty nodules were identified, 35 carcinoids and 25 hamartomas. Carcinoids were larger than hamartomas (median diameter, 13.5 vs 11.5 mm; P = 0.05). For carcinoid tumors, median VDT (n = 15) was 1485 days, and median eVDT (n = 32) was 1309 days; for hamartomas, median VDT (n = 8) was 2040 days and median eVDT (n = 25) was 2253 days. Carcinoid tumor eVDT was significantly shorter than hamartomas ( P = 0.03). By growth category, 1 of 25 hamartomas and 5 of 35 carcinoids had eVDT less than 400 days and 24 of 25 hamartomas and 27 of 35 carcinoids had eVDT more than 600 days. Of 4 carcinoid tumors with metastases, 2 had eVDT less than 400 days and 2 had eVDT more than 600 days.

CONCLUSIONS

Growth rate was not a reliable differentiator of pulmonary hamartomas and carcinoids. Slow growing carcinoids can metastasize. Radiologists should be cautious when discontinuing computed tomography follow-up based on growth rates alone.

[Lung Imaging Reporting and Data System (Lung-RADS) in Radiology: Strengths, Weaknesses and Improvement]

In 2019, the American College of Radiology announced Lung CT Screening Reporting & Data System (Lung-RADS) 1.1 to reduce lung cancer false positivity compared to that of Lung-RADS 1.0 for effective national lung cancer screening, and in December 2022, announced the new Lung-RADS 1.1, Lung-RADS^® 2022 improvement. The Lung-RADS^® 2022 measures the nodule size to the first decimal place compared to that of the Lung-RADS 1.0, to category 2 until the juxtapleural nodule size is < 10 mm, increases the size criterion of the ground glass nodule to 30 mm in category 2, and changes categories 4B and 4X to extremely suspicious. The category was divided according to the airway nodules location and shape or wall thickness of atypical pulmonary cysts. Herein, to help radiologists understand the Lung-RADS^® 2022, this review will describe its advantages, disadvantages, and future improvements.

Paraneoplastic Hypereosinophilia in Poorly Differentiated Adenocarcinoma of the Lung

It is well-documented that lung and bronchus cancers are the leading cause of cancer death in the United States in both male and female patients, with lung adenocarcinoma accounting for the highest prevalence of lung cancers. Significant eosinophilia in the setting of lung adenocarcinoma has been documented in a few reports, being described as a rare paraneoplastic syndrome. We report on an 81-year-old female with hypereosinophilia-associated lung adenocarcinoma. A chest film showed a right lung mass, which was not apparent on a chest film 1 year prior, in the setting of significant leukocytosis of 27.90 x 10³/mm³ with eosinophilia of 6.40 x 10³/mm³. A computed tomography (CT) chest, obtained during admission, demonstrated significant right lower lobe mass enlargement since the previous study completed 5 months prior, with new occlusion of bronchi and pulmonary vessels to the region of the mass. Our observations are consistent with prior reports showing that the presence of eosinophilia in lung cancers may indicate rapid disease progression.

Clinical Non-Small Cell Lung Cancer Staging and Tumor Length Measurement Results From U.S. Cancer Hospitals

RATIONALE AND OBJECTIVES

Examine the accuracy of clinical non-small cell lung cancer staging and tumor length measurements, which are critical to prognosis and treatment planning.

MATERIALS AND METHODS

Compare clinical and pathological staging and lengths using 10,320 2016 National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) and 559 2010-2018 non-SEER single-institute surgically-treated cases, and analyze modifiable causes of disagreement.

RESULTS

The SEER clinical and pathological group-stages agree only 62.3% ± 0.9% over all stage categories. The lymph node N-stage agrees much better at 83.0% ± 1.0%, but the tumor length-location T-stage agrees only 57.7% ± 0.8% with approximately 29% of the cases having a greater pathology than clinical T-stage. Individual T-stage category agreements with respect to the number of pathology cases are Tis, T1a, T1b, T2a, T2b, T3, T4: 89.9% ± 10.0%; 78.7% ± 1.7%; 51.8% ± 1.9%; 46.1% ± 1.3%; 40.5% ± 3.1%; 44.1% ± 2.2%; 56.4% ± 4.7%, respectively. Most of the single-institute results statistically agree with SEER's. Excluding Tis cases, the mean difference in SEER tumor length is ∼1.18 ± 9.26 mm (confidence interval: 0.97-1.39 mm) with pathological lengths being longer than clinical lengths except for small tumors; the two measurements correlate well (Pearson-r >0.87, confidence interval: 0.86-0.87). Reasons for disagreement include the use of family-category descriptors (e.g., T1) instead of their subcategories (e.g., T1a and T1b), which worsens the T-stage agreement by over 15%. Disagreement is also associated with higher tumor grade, larger resected specimens, higher N-stage, patient age, and periodic biases in clinical and pathological tumor size measurements.

CONCLUSIONS

By including preliminary non-small cell lung cancer clinical stage values in their evaluation, diagnostic radiologists can improve the accuracy of staging and standardize tumor-size measurements, which improves patient care.

Prediction of Microscopic Metastases in Patients with Metachronous Oligo-Metastases after Curative Treatment of Non-Small Cell Lung Cancer: A Microsimulation Study

Simple Summary

Many patients with metachronous oligo-metastases in non-small cell lung cancer have their recurrences surgically removed, although the 5-year recurrence-free survival of this group is 16%. This does not provide any benefit for patients with additional undetected metastases. Therefore, we aim to find patient characteristics that are predictive for having additional undetected microscopic metastases. Based on a theoretical approach, we identified the size and number of detected oligo-metastases, as well as the presence of symptoms that are the most important risk predictors.

Abstract

Metachronous oligo-metastatic disease is variably defined as one to five metastases detected after a disease-free interval and treatment of the primary tumour with curative intent. Oligo-metastases in non-small cell lung cancer (NSCLC) are often treated with curative intent. However additional metastases are often detected later in time, and the 5-year survival is low. Burdensome surgical treatment in patients with undetected metastases may be avoided if patients with a high versus low risk of undetected metastases can be separated. Because there is no clinical data on undetected metastases available, a microsimulation model of the development and detection of metastases in 100,000 hypothetical stage I NSCLC patients with a controlled primary tumour was constructed. The model uses data from the literature as well as patient-level data. Calibration was used for the unobservable model parameters. Metastases can be detected by a scheduled scan, or an unplanned scan when the patient develops symptoms. The observable information at time of detection is used to identify subgroups of patients with a different risk of undetectable metastases. We identified the size and number of detected oligo-metastases, as well as the presence of symptoms that are the most important risk predictors. Based on these predictors, patients could be divided into a low-risk and a high-risk group, having a model-based predicted probability of 8.1% and 89.3% to have undetected metastases, respectively. Currently, the model is based on a synthesis of the literature data and individual patient-level data that were not collected for the purpose of this study. Optimization and validation of the model is necessary to allow clinical usability. We describe the type of data that needs to be collected to update our model, as well as the design of such a validation study.

Lung-RADS Version 1.1: Challenges and a Look Ahead, From the AJR Special Series on Radiology Reporting and Data Systems

In 2014, the American College of Radiology (ACR) created Lung-RADS 1.0. The system was updated to Lung-RADS 1.1 in 2019, and further updates are anticipated as additional data become available. Lung-RADS provides a common lexicon and standardized nodule follow-up management paradigm for use when reporting lung cancer screening (LCS) low-dose CT (LDCT) chest examinations and serves as a quality assurance and outcome monitoring tool. The use of Lung-RADS is intended to improve LCS performance and lead to better patient outcomes. To date, the ACR's Lung Cancer Screening Registry is the only LCS registry approved by the Centers for Medicare & Medicaid Services and requires the use of Lung-RADS categories for reimbursement. Numerous challenges have emerged regarding the use of Lung-RADS in clinical practice, including the timing of return to LCS after planned follow-up diagnostic evaluation; potential substitution of interval diagnostic CT for future LDCT; role of volumetric analysis in assessing nodule size; assessment of nodule growth; assessment of cavitary, subpleural, and category 4X nodules; and variability in reporting of the S modifier. This article highlights the major updates between versions 1.0 and 1.1 of Lung-RADS, describes the system's ongoing challenges, and summarizes current evidence and recommendations.

Volume and Mass Doubling Time of Lung Adenocarcinoma according to WHO Histologic Classification

Objective

This study aimed to evaluate the tumor doubling time of invasive lung adenocarcinoma according to the International Association of the Study for Lung Cancer (IASLC)/American Thoracic Society (ATS)/European Respiratory Society (ERS) histologic classification.

Materials and Methods

Among the 2905 patients with surgically resected lung adenocarcinoma, we retrospectively included 172 patients (mean age, 65.6 ± 9.0 years) who had paired thin-section non-contrast chest computed tomography (CT) scans at least 84 days apart with the same CT parameters, along with 10 patients with squamous cell carcinoma (mean age, 70.9 ± 7.4 years) for comparison. Three-dimensional semiautomatic segmentation of nodules was performed to calculate the volume doubling time (VDT), mass doubling time (MDT), and specific growth rate (SGR) of volume and mass. Multivariate linear regression, one-way analysis of variance, and receiver operating characteristic curve analyses were performed.

Results

The median VDT and MDT of lung cancers were as follows: acinar, 603.2 and 639.5 days; lepidic, 1140.6 and 970.1 days; solid/micropapillary, 232.7 and 221.8 days; papillary, 599.0 and 624.3 days; invasive mucinous, 440.7 and 438.2 days; and squamous cell carcinoma, 149.1 and 146.1 days, respectively. The adjusted SGR of volume and mass of the solid-/micropapillary-predominant subtypes were significantly shorter than those of the acinar-, lepidic-, and papillary-predominant subtypes. The histologic subtype was independently associated with tumor doubling time. A VDT of 465.2 days and an MDT of 437.5 days yielded areas under the curve of 0.791 and 0.795, respectively, for distinguishing solid-/micropapillary-predominant subtypes from other subtypes of lung adenocarcinoma.

Conclusion

The tumor doubling time of invasive lung adenocarcinoma differed according to the IASCL/ATS/ERS histologic classification.

Prediction of tumor doubling time of lung adenocarcinoma using radiomic margin characteristics

Background

Because shape or irregularity along the tumor perimeter can result from interactions between the tumor and the surrounding parenchyma, there could be a difference in tumor growth rate according to tumor margin or shape. However, no attempt has been made to evaluate the correlation between margin or shape features and tumor growth.

Methods

We evaluated 52 lung adenocarcinoma (ADC) patients who had at least two computed tomographic (CT) examinations before curative resection. Volume‐based doubling times (DTs) were calculated based on CT scans, and patients were divided into two groups according to the growth pattern (GP) of their ADCs (gradually growing tumors [GP I] vs. growing tumors with a temporary decrease in DT [GP II]). CT radiomic features reflecting margin characteristics were extracted, and radiomic features reflective of tumor DT were selected.

Results

Among the 52 patients, 41 (78.8%) were assigned to GP I and 11 (21.2%) to GP II. Of the 94 radiomic features extracted, eccentricity, surface‐to‐volume ratio, LoG uniformity (σ = 3.5), and LoG skewness (σ = 0.5) were ultimately selected for tumor DT prediction. Selected radiomic features in GP I were surface‐to‐volume ratio, contrast, LoG uniformity (σ = 3.5), and LoG skewness (σ = 0.5), similar to those for total subjects, whereas the radiomic features in GP II were solidity, energy, and busyness.

Conclusions

This study demonstrated the potential of margin‐related radiomic features to predict tumor DT in lung ADCs.

Key points

Significant findings of the study

We found a relationship between margin‐related radiomic features and tumor doubling time.

What this study adds

Margin‐related radiomic features can potentially be used as noninvasive biomarkers to predict tumor doubling time in lung adenocarcinoma and inform treatment strategies.

Effect of time interval from diagnosis to treatment for non-small cell lung cancer on survival: a national cohort study in Taiwan

OBJECTIVES

This study aimed to determine if treatment delay after non-small cell lung cancer (NSCLC) diagnosis impacts patient survival rate.

STUDY DESIGN

This study is a natural experiment in Taiwan. A retrospective cohort investigation was conducted from 2004 to 2010, which included 42 962 patients with newly diagnosed NSCLC.

METHODS

We identified 42 962 patients with newly diagnosed NSCLC in the Taiwan Cancer Registry from 2004 to 2010. We calculated the time interval between diagnosis and treatment initiation. All patients were followed from the index date to death or the end of 2012. Cox proportional hazard models were used to examine the relationship between mortality and time interval.

RESULTS

We included 42 962 patients (15 799 men and 27 163 women) with newly diagnosed NSCLC. The mortality rate exhibited a significantly positive correlation to time interval from cancer diagnosis to treatment initiation. The adjusted HRs ranged from 1.04 to 1.08 in all subgroups time interval more than 7 days compared with the counterpart subgroup of the interval from cancer diagnosis to treatment ≤7 days. The trend was also noted regardless of the patients with lung cancer in stage I, stage II and stage III.

CONCLUSIONS

There is a major association between time to treat and mortality of patients with NSCLC, especially in stages I and II. We suggest that efforts should be made to minimise the interval from diagnosis to treatment while further study is ongoing to determine causation.

Thymidine phosphorylase affects clinical outcome following surgery and mRNA expression levels of four key enzymes for 5-fluorouracil metabolism in patients with stage I and II non-small cell lung cancer

The expression levels of thymidine phosphorylase (TP), dihydropyrimidine dehydrogenase (DPD), thymidylate synthase (TS) and orotate phosphoribosyltransferase (OPRT) may predict the clinical efficacy of 5-fluorouracil-based chemotherapy in patients with cancer. We herein investigated the differences in the mRNA levels of these enzymes in non-small-cell lung cancer (NSCLC) and evaluated their prognostic value for NSCLC treated by surgical resection. The intratumoral mRNA levels of TP, DPD, TS, and OPRT were quantified in 66 patients with pathological stage I and II NSCLC (adenocarcinoma or squamous cell carcinoma) following complete resection according to the Danenberg Tumor Profile method. The TP level was the only significant prognostic factor for disease-specific survival (DSS) following complete resection; the mean TP mRNA level differed significantly between the high and low mRNA expression groups. The DSS at 5 years was significantly higher in the low TP mRNA compared with that in the high TP mRNA expression group (83.4 vs. 58.6%, respectively; P=0.005). A Cox proportional hazards model revealed that pathological stage, sex, and TP expression were independent prognostic factors for DSS in patients with stage I and II NSCLC following complete resection. Thus, TP level may be used to monitor treatment efficacy and predict the outcome of NSCLC patients.

The impact of histology and ground-glass opacity component on volume doubling time in primary lung cancer

Background

Correlations between volume doubling time (VDT) of primary lung cancer (PLC), histology, and ground glass opacity (GGO) components remain unclear. The purpose of this study was to evaluate and compare VDT of PLC in terms of histology and presence or absence of GGO components.

Methods

A total of 371 surgically resected PLCs from 2003 to 2015 in our institute were retrospectively reviewed. The VDT was calculated both from the diameters of the entire tumor and of consolidation by using the approximation formula of Schwartz.

Results

The median VDTs of adenocarcinoma, squamous cell carcinoma, and others (large cell neuroendocrine carcinomas, small cell lung carcinomas, pulmonary pleomorphic carcinomas, and large cell carcinomas combined) were 261, 70, and 70 days, respectively; these differ significantly (P<0.001). All PLCs with GGO were adenocarcinomas. The VDT of adenocarcinomas with GGO was significantly longer than that of those without GGO (median VDT: 725 and 177 days, respectively), squamous cell carcinomas, and others. When the VDT calculated from the maximum diameter of consolidation component was compared, adenocarcinomas with GGO also showed significantly slower growth than those without GGO (median VDT: 248 versus 177 days, respectively, P=0.040).

Conclusions

The VDT of PLCs is longest for adenocarcinomas. VDT was significantly longer in adenocarcinomas with GGO components than in those without such components, irrespective of VDT calculated on the basis of either the entire tumor diameter or consolidation diameter.

A case of pulmonary adenocarcinoma showing rapid progression of peritoneal dissemination after immune checkpoint inhibitor therapy

Background

Immune checkpoint inhibitors are standard treatments for non-small cell lung cancer. Unique cases with paradoxical acceleration of the disease after immunotherapy have been reported. These have been described as cases of hyperprogressive disease.

Case presentation

A 76-year-old man was diagnosed with pulmonary adenocarcinoma with pleural dissemination and liver and adrenal metastases. Genomic analysis revealed neither EGFR mutations nor ALK translocations. Immunohistochemical analysis revealed a programmed death-ligand 1 tumor proportion score of 23%. Chemotherapy with carboplatin, paclitaxel, and bevacizumab resulted in Grade 3 skin eruption and disease progression. Pembrolizumab was initiated as a second-line treatment. However, peritoneal dissemination and ascites developed. The patient died 2 weeks later. The autopsy revealed widespread peritoneal dissemination and an extensive hemorrhagic infarction.

Conclusion

This was a rare case of hyperprogressive disease with rapid progression of peritoneal dissemination after pembrolizumab treatment.

Malignancy risk estimation of pulmonary nodules in screening CTs: Comparison between a computer model and human observers

Purpose

To compare human observers to a mathematically derived computer model for differentiation between malignant and benign pulmonary nodules detected on baseline screening computed tomography (CT) scans.

Methods

A case-cohort study design was chosen. The study group consisted of 300 chest CT scans from the Danish Lung Cancer Screening Trial (DLCST). It included all scans with proven malignancies (n = 62) and two subsets of randomly selected baseline scans with benign nodules of all sizes (n = 120) and matched in size to the cancers, respectively (n = 118). Eleven observers and the computer model (PanCan) assigned a malignancy probability score to each nodule. Performances were expressed by area under the ROC curve (AUC). Performance differences were tested using the Dorfman, Berbaum and Metz method. Seven observers assessed morphological nodule characteristics using a predefined list. Differences in morphological features between malignant and size-matched benign nodules were analyzed using chi-square analysis with Bonferroni correction. A significant difference was defined at p < 0.004.

Results

Performances of the model and observers were equivalent (AUC 0.932 versus 0.910, p = 0.184) for risk-assessment of malignant and benign nodules of all sizes. However, human readers performed superior to the computer model for differentiating malignant nodules from size-matched benign nodules (AUC 0.819 versus 0.706, p < 0.001). Large variations between observers were seen for ROC areas and ranges of risk scores. Morphological findings indicative of malignancy referred to border characteristics (spiculation, p < 0.001) and perinodular architectural deformation (distortion of surrounding lung parenchyma architecture, p < 0.001; pleural retraction, p = 0.002).

Conclusions

Computer model and human observers perform equivalent for differentiating malignant from randomly selected benign nodules, confirming the high potential of computer models for nodule risk estimation in population based screening studies. However, computer models highly rely on size as discriminator. Incorporation of other morphological criteria used by human observers to superiorly discriminate size-matched malignant from benign nodules, will further improve computer performance.

Volume doubling time of lung adenocarcinomas considering epidermal growth factor receptor mutation status of exon 19 and 21: three-dimensional volumetric evaluation

Background

The current study was to investigate the volume doubling time (VDT) of lung adenocarcinomas considering epidermal growth factor receptor (EGFR) mutation status of exon 19 and 21, when compared with EGFR wide type.

Methods

Eighty-eight patients with pathologically proven adenocarcinomas, which underwent two or more computed tomography (CT) scans spared by 25 or more days, were included. EGFR mutations at exons 19 and 21 were determined using amplification refractory mutation system and all patients were divided into three groups-EGFR wide type group, EGFR mutation in exon 19 and 21 groups. Three-dimensional manual segmentations for all tumors were performed on first and latest follow-up CT scans; subsequently, VDTs were calculated and compared among three groups. Clinicopathoradiologic characters were also collected for subgroup analysis.

Results

EGFR mutations occurred in 49 (55.7%) patients, 19 in exon 19 and 30 in exon 21, respectively. The median VDT of all patients (33 men, 55 women; median age, 62 years) was 214 days (range, -4,092 to 10,920 days). Highly differentiated adenocarcinomas (median, 408 days) demonstrated longer VDT than those moderately (median, 172 days) or poorly (median, 144 days) differentiated (P=0.04). The VDT distribution was similar among EGFR wide type group (median, 207 days), EGFR mutation in exon 19 group (median, 288 days) and exon 21 group (median, 144 days) (P=0.21). In subgroup analysis, the median VDT of adenocarcinomas with EGFR mutation in exon 19 was longer than that of EGFR wide type for males (P=0.03) or patients without spiculation sign in chest CT (P=0.04). Totally 24 adenocarcinomas presented negative VDTs, most of which tended to be stable. Positive VDT values were used for all median description.

Conclusions

Overall VDT of lung adenocarcinomas seems not affected by EGFR mutation status. Researches with large population are warranted for further study.

Does timeliness of care in Non-Small Cell Lung Cancer impact on survival?

OBJECTIVES

To measure time intervals in the management of Non-Small Cell Lung Cancer (NSCLC) patients, identify factors associated with this and evaluate the impact of timeliness of care on survival.

MATERIALS AND METHODS

A retrospective cohort of South Western Sydney (SWS) patients with newly diagnosed NSCLC from 2006 to 2012 was identified from the SWSLHD Clinical Cancer Registry. Time intervals evaluated in days were "Diagnosis to Initial Treatment" and "Referral to Initial Treatment". Treatment included surgery, radiotherapy, systemic therapy and palliative care. Negative binomial regression and Cox regression were used to identify factors associated with timeliness of care and survival respectively.

RESULTS

1926 NSCLC patients were identified of whom 1729 had initial treatment recorded. Initial treatment was palliative care in 35% (n=611), radiotherapy in 29% (n=498), surgery in 18% (n=314) and systemic therapy in 18% (n=306). Median time from diagnosis to treatment was 32days (IQR 15-58). Median time from specialist referral to treatment was 35days for surgery (IQR 21-49), 21days for radiotherapy (IQR 13-32) and 25days (IQR 15-35) for systemic therapy. On multivariable analysis, age between 70 and 79 years, ECOG performance status 0-1, Stage I-III NSCLC and systemic treatment were associated with longer Diagnosis to Treatment: intervals. Diagnosis to Treatment: interval was not associated with mortality in Stage I & II NSCLC. A longer interval was associated with reduced mortality in Stage III (HR 0.99, 95%CI 0.99-1.0, p=0.03) and Stage IV NSCLC (HR=0.99, 95% CI 0.99-0.99, p=0.0008).

CONCLUSIONS

At the population level, longer Diagnosis to Treatment: time intervals were not associated with adverse survival outcomes in NSCLC. However, delays to treatment may impact on other outcomes such as patient's psychological wellbeing and quality of life which were not measured in this study.

Correlation Factors Analysis of Breast Cancer Tumor Volume Doubling Time Measured by 3D-Ultrasound

BACKGROUND Tumor volume doubling time (TVDT) is relatively important for breast cancer diagnosis and prognosis evaluation. This study aimed to analyze the related factors that may affect the TVDT of breast cancer by three-dimensional ultrasound (3D-US). MATERIAL AND METHODS A total of 69 breast cancer patients were selected. 3D-US was applied to measure the volume of breast lumps diagnosed as BI-RADS-US 4A by conventional ultrasound. TVDT was calculated according to the formula TVDT=DT×log2/log(V2/V1). Multiple linear regression analysis was performed to analyze the factors influencing breast cancer TVDT. RESULTS The mean and median TVDT were 185±126 (range 66-521) and 164 days, respectively. TVDT showed no statistical significance according to regular shape, coarse margin, spicule sign, peripheral hyperechoic halo, microcalcification, and different posterior echo characteristics (P>0.05). Patients grouped by age, axillary lymphatic metastasis, histological differentiation, and Nottingham prognostic index (NPI) score exhibited significantly different TVDT (P<0.05). On the contrary, patients with different menstrual conditions, breast cancer family history, or pathological types presented similar TVDT (P>0.05). TVDT was obviously different in breast cancer with different ER, PR, Ki-67, and molecular subtyping but not HER2 expression. Multivariate analysis revealed that NPI score, axillary lymphatic metastasis, Ki-67, and molecular subtyping were risk factors of TVDT in breast cancer (P<0.05). CONCLUSIONS Breast cancer TVDT was significantly correlated with NPI score, axillary lymphatic metastasis, Ki-67, and molecular subtyping. Triple-negative breast cancer exhibited the most rapid growth.

Radiation Treatment Time and Overall Survival in Locally Advanced Non-small Cell Lung Cancer

PURPOSE

Prolonged radiation treatment (RT) time (RTT) has been associated with worse survival in several malignancies. The present study investigated whether delays during RT are associated with overall survival (OS) in non-small cell lung cancer (NSCLC).

METHODS AND MATERIALS

The National Cancer Database was queried for patients with stage III NSCLC who had received definitive concurrent chemotherapy and fractionated RT to standard doses (59.4-70.0 Gy) and fractionation from 2004 to 2013. The RTT was classified as standard or prolonged for each treatment regimen according to the radiation dose and number of fractions. Cox proportional hazards models were used to evaluate the association between the following factors and OS: RTT, RT fractionation, demographic and pathologic factors, and chemotherapeutic agents.

RESULTS

Of 14,154 patients, the RTT was prolonged in 6262 (44.2%). Factors associated with prolonged RTT included female sex (odds ratio [OR] 1.21, P<.0001), black race (OR 1.20, P=.001), nonprivate health insurance (OR 1.30, P<.0001), and lower income (<$63,000 annually, OR 1.20, P<.0001). The median OS was significantly worse for patients with prolonged RTT than that for those with standard RTT (18.6 vs 22.7 months, P<.0001). Furthermore, the OS worsened with each cumulative interval of delay (standard RTT vs prolonged 1-2 days, 20.5 months, P=.009; prolonged 3-5 days, 17.9 months, P<.0001; prolonged 6-9 days, 17.7 months, P<.0001; prolonged >9 days, 17.1 months, P<.0001). On multivariable analysis, prolonged RTT was independently associated with inferior OS (hazard ratio 1.21, P<.0001). Prolonged RTT as a continuous variable was also significantly associated with worse OS (hazard ratio 1.001, P=.0007).

CONCLUSIONS

Delays during RT appear to negatively affect survival for patients with locally advanced NSCLC. We have detailed the demographic and socioeconomic barriers influencing prolonged RTT as a method to address the health disparities in this regard. Cumulative interruptions of RT should be minimized.

In Silico Oncology: Quantification of the In Vivo Antitumor Efficacy of Cisplatin-Based Doublet Therapy in Non-Small Cell Lung Cancer (NSCLC) through a Multiscale Mechanistic Model

The 5-year survival of non-small cell lung cancer patients can be as low as 1% in advanced stages. For patients with resectable disease, the successful choice of preoperative chemotherapy is critical to eliminate micrometastasis and improve operability. In silico experimentations can suggest the optimal treatment protocol for each patient based on their own multiscale data. A determinant for reliable predictions is the a priori estimation of the drugs’ cytotoxic efficacy on cancer cells for a given treatment. In the present work a mechanistic model of cancer response to treatment is applied for the estimation of a plausible value range of the cell killing efficacy of various cisplatin-based doublet regimens. Among others, the model incorporates the cancer related mechanism of uncontrolled proliferation, population heterogeneity, hypoxia and treatment resistance. The methodology is based on the provision of tumor volumetric data at two time points, before and after or during treatment. It takes into account the effect of tumor microenvironment and cell repopulation on treatment outcome. A thorough sensitivity analysis based on one-factor-at-a-time and latin hypercube sampling/partial rank correlation coefficient approaches has established the volume growth rate and the growth fraction at diagnosis as key features for more accurate estimates. The methodology is applied on the retrospective data of thirteen patients with non-small cell lung cancer who received cisplatin in combination with gemcitabine, vinorelbine or docetaxel in the neoadjuvant context. The selection of model input values has been guided by a comprehensive literature survey on cancer-specific proliferation kinetics. The latin hypercube sampling has been recruited to compensate for patient-specific uncertainties. Concluding, the present work provides a quantitative framework for the estimation of the in-vivo cell-killing ability of various chemotherapies. Correlation studies of such estimates with the molecular profile of patients could serve as a basis for reliable personalized predictions.

Less than 14% of medically treated patients with locally advanced and metastatic non-small cell lung cancer are expected to be alive 5 years after diagnosis. Standard therapeutic strategies include the administration of two drugs in combination, aiming at shrinking the tumor before surgery and improving overall survival. Knowing the sensitivity profile of each patient to different treatment strategies at diagnosis may help choose the most appropriate ones. We develop a methodology for the quantitative estimation of the cytotoxic efficacy of cisplatin-based doublets on cancer cells by applying a simulation model of cancer progression and response. The model incorporates the proliferation cycle, quiescence, differentiation and loss of tumor cells. We evaluate the effect of in vivo microenvironment of real tumors, as expressed by measurable tumor proliferation kinetics, such as how fast the tumor grows, the percentage of cells that are actively dividing, the resistance of stem cells, etc. on treatment outcome so as to derive more accurate estimates. A literature survey guides the selection of values. The methodology is applied to a real clinical dataset of patients. Correlation studies between the derived cytotoxicities and the patients’ molecular profile could lead to predictions of treatment response at the time of diagnosis.