Tumor Volume Doubling Time Research Articles

Tumor Volume Doubling Time of Less Than One Year is Associated with a Higher Risk of Death from Medullary Thyroid Cancer.

Tumor volume doubling time (TVDT) is emerging as a useful tool in predicting oncologic outcomes. There is limited data on the prognostic role of TVDT in metastatic medullary thyroid cancer (MTC). The goal of this study was to assess the value of TVDT in predicting disease-specific survival (DSS) in patients with hereditary and sporadic MTC. This was an Institutional Review Board-approved cohort study including patients with metastatic MTC having at least 3 consecutive imaging studies. TVDT of up to the five largest lesions per organ was calculated using a standardized formula. The association between TVDT and DSS was analyzed using Kaplan-Meier survival curves. Cox proportional regression model was used to account for confounding factors. The study sample consisted of 51 patients presenting with 286 metastatic lesions measured with 457 scans during the follow-up of 51 (IQR 25-102) months. Median age was 19 years (IQR 15-41), 53% female patients. Cumulative volumes of all metastatic lesions and proportion of patients with TVDT of <1 year were higher in patients with sporadic as compared with hereditary MTC (p<0.01). Factors independently associated with shorter DSS were TVDT of <1 year based on 3 initial and 3 last scans as well as lung, brain and prostate as the organs with the fastest growing tumor. TVDT based on 2-dimentional and 3-dimentional measurements showed strong correlation (r=0.94, p<0.05). Three baseline and three most recent scans preceding follow-up visit enable calculation of TVDT and can be used as predictors of mortality from MTC.

BRAF mutation is associated with tumor volume doubling time of thyroid microcarcinoma during active surveillance

BRAF mutation is associated with tumor volume doubling time of thyroid microcarcinoma during active surveillance

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.

Tracking Ovine Pulmonary Adenocarcinoma Development Using an Experimental Jaagsiekte Sheep Retrovirus Infection Model.

Ovine pulmonary adenocarcinoma (OPA) is an infectious, neoplastic lung disease of sheep that causes significant animal welfare and economic issues throughout the world. Understanding OPA pathogenesis is key to developing tools to control its impact. Central to this need is the availability of model systems that can monitor and track events after Jaagsiekte sheep retrovirus (JSRV) infection. Here, we report the development of an experimentally induced OPA model intended for this purpose. Using three different viral dose groups (low, intermediate and high), localised OPA tumour development was induced by bronchoscopic JSRV instillation into the segmental bronchus of the right cardiac lung lobe. Pre-clinical OPA diagnosis and tumour progression were monitored by monthly computed tomography (CT) imaging and trans-thoracic ultrasound scanning. Post mortem examination and immunohistochemistry confirmed OPA development in 89% of the JSRV-instilled animals. All three viral doses produced a range of OPA lesion types, including microscopic disease and gross tumours; however, larger lesions were more frequently identified in the low and intermediate viral groups. Overall, 31% of JSRV-infected sheep developed localised advanced lesions. Of the sheep that developed localised advanced lesions, tumour volume doubling times (calculated using thoracic CT 3D reconstructions) were 14.8 ± 2.1 days. The ability of ultrasound to track tumour development was compared against CT; the results indicated a strong significant association between paired CT and ultrasound measurements at each time point (R2 = 0.799, p < 0.0001). We believe that the range of OPA lesion types induced by this model replicates aspects of naturally occurring disease and will improve OPA research by providing novel insights into JSRV infectivity and OPA disease progression.

Quantifying the natural growth rate of hepatocellular carcinoma: A real-world retrospective study in southwestern China.

In recent years, approximately half of the newly diagnosed cases and mortalities attributed to hepatocellular carcinoma (HCC) have been reported in China. Despite the high incidence of HCC, there remains a paucity of data regarding the natural growth pattern and the determination of optimal surveillance intervals specific to the Chinese population. To quantify the natural tumor growth pattern of HCC in regional China. A retrospective analysis was performed on patients from a single institution in Southwest China who had undergone two or more serial dynamic computed tomography or magnetic resonance imaging scans between 2014 and 2020, without having received any anti-cancer therapy. Tumor growth was assessed using tumor volume doubling time (TVDT) and tumor growth rate (TGR), with volumes measured manually by experienced radiologists. Simple univariate linear regression and descriptive analysis were applied to explore associations between growth rates and clinical factors. This study identifies the median TVDT for HCC as 163.4 d, interquartile range (IQR) 72.1 to 302.3 d, with a daily TGR of 0.42% (IQR 0.206%-0.97%). HCC growth patterns reveal that about one-third of tumors grow indolently with TVDT exceeding 270 d, another one-third of tumors exhibit rapid growth with TVDT under 90 d, and the remaining tumors show intermediate growth rates, with TVDT ranging between 3 to 9 months. The identified TGRs support biannual surveillance and follow-up for HCC patients in certain regions of China. Given the observed heterogeneity in HCC growth, further investigation is warranted.

Tumor Growth Kinetics Based on Initial Tumor Volume Doubling Time in Active Surveillance of Low-Risk Papillary Thyroid Carcinoma.

Background: During active surveillance (AS) of low-risk papillary thyroid carcinomas (PTCs), the majority remain stable, while some exhibit either an increase or a decrease in tumor diameter or tumor volume (TV). We aimed to evaluate the clinical outcomes and relevant parameters influencing tumor growth kinetics of low-risk PTCs. Methods: This retrospective cohort study evaluated clinical parameters of 402 patients with low-risk PTC sized <2 cm, with a follow-up duration over 3 years. Changes in maximum tumor diameter, TV, and initial TV doubling time (i-TVDT) calculated within 3 years were assessed. A significant change in TV was defined as a change of 75% or more. Results: Of the 402 patients with low-risk PTC, 93.3% (375/402) were diagnosed with papillary thyroid microcarcinoma. During a median follow-up of 5 years, 3.4% (14/402) of patients developed new cervical lymph node (LN) metastasis, and 8.2% (33/402) experienced a maximal diameter increase of ≥3 mm. The i-TVDT of <5 years emerged as an independent risk factor for both maximal diameter growth and new LN metastasis (p < 0.001 and p = 0.04, respectively). Based on TV changes and i-TVDT during AS, we identified four statistically significant tumor kinetic patterns (p < 0.001): Stable (±75% change in TV), Rapid growth (TV increase >75% and i-TVDT <5 years), Slow growth (TV increase >75% and i-TVDT ≥5 years), and Shrinkage (TV decrease >75%). Most of the PTCs remained stable (67.7%), but 17.2% were rapidly growing, with a median onset of growth of 2.0 years. Slowly growing PTCs, comprising 10.9%, grew at a median of 4.3 years. A minority, 4.2%, exhibited shrinkage. In total, 115 (28.6%) patients underwent delayed surgery >12 months after initiating AS. The reasons for delayed surgery included patient preference (51/115, 44.3%), disease progression (31/115, 27.0%), and suspected disease progression, which was referred to as tumor growth not meeting the criteria of an increase of ≥3 mm in maximal tumor diameter (17/115, 14.8%). Conclusion: An i-TVDT of <5 years serves as an important prognostic indicator for disease progression, including tumor growth and new LN metastasis. The four tumor kinetic patterns based on TV changes and i-TVDT assist in guiding personalized decisions early in AS.

Prognostic value of tumor volume doubling time in lung-metastatic adenoid cystic carcinoma

ObjectivesLung metastases in adenoid cystic carcinoma (ACC) usually have indolent growth and the optimal timing to start systemic therapy is not established. We assessed ACC lung metastasis tumor growth dynamics and compared the prognostic value of time to progression (TTP) and tumor volume doubling time (TVDT). MethodsThe study included ACC patients with ≥1 pulmonary metastasis (≥5 mm) and at least 2 chest computed tomography scans. Radiology assessment was performed from the first scan showing metastasis until treatment initiation or death. Up to 5 lung nodules per patient were segmented for TVDT calculation. To assess tumor growth rate (TGR), the correlation coefficient (r) and coefficient of determination (R2) were calculated for measured lung nodules. TTP was assessed per RECIST 1.1; TVDT was calculated using the Schwartz formula. Overall survival was analyzed using the Kaplan-Meier method. ResultsThe study included 75 patients. Sixty-seven patients (89%) had lung-only metastasis on first CT scan. The TGR was overall constant (median R2 = 0.974). Median TTP and TVDT were 11.2 months and 7.5 months. Shorter TVDT (<6 months) was associated with poor overall survival (HR = 0.48; p = 0.037), but TTP was not associated with survival (HR = 1.02; p = 0.96). Cox regression showed that TVDT but not TTP significantly correlated with OS. TVDT calculated using estimated tumor volume correlated with TVDT obtained by segmentation. ConclusionMost ACC lung metastases have a constant TGR. TVDT may be a better prognostic indicator than TTP in lung-metastatic ACC. TVDT can be estimated by single longitudinal measurement in clinical practice.

Prognostic Value of Time To Progression vs. Tumor Volume Doubling Time in Patients with Adenoid Cystic Carcinoma Metastatic To The Lung

Prognostic Value of Time To Progression vs. Tumor Volume Doubling Time in Patients with Adenoid Cystic Carcinoma Metastatic To The Lung

Effectiveness and safety of lenvatinib in a series of advanced well-differentiated thyroid carcinomas from a single tertiary cancer center and literature review.

Treatment of advanced differentiated thyroid carcinoma (DTC) remains a challenge as 25-50% of patients with locally invasive or distant metastatic disease become refractory to radioiodine (RAI) therapy. Tyrosine kinase inhibitors (TKI) are increasingly used in this setting. The SELECT trial demonstrated that lenvatinib, a multikinase inhibitor, significantly improved progression free survival (PFS) compared to placebo. Our aim was to report the effectiveness and safety of lenvatinib in our series of patients with advanced DTC. A total of 25 patients with advanced DTC followed at a single tertiary center from January of 2016 to January of 2022 were retrospectively reviewed. Patients were treated with a mean daily dose of lenvatinib of 16.9 mg for a mean of 9.1 months. Median estimated PFS was 31.3 months. One patient achieved complete response. The objective response rate (ORR) was 40% and the disease control rate was 84%. The mean change in summed longest diameter of target lesions from baseline to nadir was -36.9%. Lenvatinib prolonged the tumor volume doubling time in 86.7% patients. Interestingly, we found that patients treated with a lower dose of lenvatinib (<16.9 mg daily) had a significantly higher PFS and ORR than patients treated with higher dosages (>16.9 mg). Adverse events were frequently reported. Our results confirm the effectiveness of lenvatinib in the management of patients with advanced DTC and support the need to adjust the dosage of lenvatinib to patient´s performance status and comorbidities.

The value of diffusion-weighted imaging in the natural history of meningiomas: a predictor of tumor growth.

The general trend in meningioma treatment is shifting from surgery to active surveillance. However, the natural history of meningioma still needs to be clarified, and a simple, practical method is needed to identify fast-growing tumors. The authors aimed to determine whether diffusion-weighted imaging (DWI) could be a valuable imaging modality for predicting meningioma growth. Consecutive asymptomatic patients with a meningioma diagnosed on MRI and followed up at the authors' institution between July 2011 and July 2019 were eligible for inclusion in this retrospective study. Univariable and multivariable Cox regression analyses were used to explore whether the relative apparent diffusion coefficient (rADC) was an independent predictor of meningioma growth. Correlations between tumor growth rate (TGR), tumor volume doubling time (VDT), Ki-67, and rADC were assessed using the Pearson correlation coefficient. The predictive ability of rADC was evaluated using receiver operating characteristic (ROC) curves and validated with internal validation data. Sixty-four patients (47 females, 17 males) with a mean age of 62.2 ± 1.4 years were included in this study. Univariable and multivariable analyses revealed that rADC was an independent predictor of meningioma growth (p < 0.05). ROC curve analysis showed that baseline rADC had good predictive power for growing meningiomas (AUC = 0.88, 95% CI 0.78-0.96), as well as slow- or fast-growing meningiomas (AUC = 0.83, 95% CI 0.59-0.98). Moreover, rADC still had a good ability to discriminate between growing and nongrowing meningiomas in the validation set (AUC = 0.85, 95% CI 0.64-1.00). In the 20 patients with tumor growth, baseline rADC was moderately negatively correlated with TGR (r = -0.50, p = 0.02) and strongly positively correlated with VDT (r = 0.63, p = 0.003). Moreover, Ki-67 was significantly associated with rADC in 8 patients who had undergone surgery (r = -0.75, p = 0.03). In asymptomatic meningiomas, the lower the rADC at baseline, the faster the TGR and the shorter the VDT. DWI could be a valuable tool in predicting meningioma growth in asymptomatic patients.

Preoperative growth dynamics of untreated glioblastoma: Description of an exponential growth type, correlating factors, and association with postoperative survival.

Little is known about the growth dynamics of untreated glioblastoma and its possible influence on postoperative survival. Our aim was to analyze a possible association of preoperative growth dynamics with postoperative survival. We performed a retrospective analysis of all adult patients surgically treated for newly diagnosed glioblastoma at our center between 2010 and 2020. By volumetric analysis of data of patients with availability of ≥3 preoperative sequential MRI, a growth pattern was aimed to be identified. Main inclusion criterion for further analysis was the availability of two preoperative MRI scans with a slice thickness of 1mm, at least 7 days apart. Individual growth rates were calculated. Association with overall survival (OS) was examined by multivariable. Out of 749 patients screened, 13 had ≥3 preoperative MRI, 70 had 2 MRI and met the inclusion criteria. A curve estimation regression model showed the best fit for exponential tumor growth. Median tumor volume doubling time (VDT) was 31 days, median specific growth rate (SGR) was 2.2% growth per day. SGR showed negative correlation with tumor size (rho = -0.59, P < .001). Growth rates were dichotomized according to the median SGR.OS was significantly longer in the group with slow growth (log-rank: P = .010). Slower preoperative growth was independently associated with longer overall survival in a multivariable Cox regression model for patients after tumor resection. Especially small lesions suggestive of glioblastoma showed exponential tumor growth with variable growth rates and a median VDT of 31 days. SGR was significantly associated with OS in patients with tumor resection in our sample.

Solitary lung adenocarcinoma: follow-up CT, pathological-molecular characteristics, and surgical prognosis for different morphological classifications

ObjectiveTo investigate the dynamic changes during follow-up computed tomography (CT), histological subtypes, gene mutation status, and surgical prognosis for different morphological presentations of solitary lung adenocarcinomas (SLADC).Materials and methodsThis retrospective study compared dynamic tumor changes and volume doubling time (VDT) in 228 patients with SLADC (morphological types I–IV) who had intermittent growth during follow-ups. The correlation between the morphological classification and histological subtypes, gene mutation status, and surgical prognosis was evaluated.ResultsAmong the 228 patients, 66 (28.9%) were classified as type I, 123 (53.9%) as type II, 16 (7%) as type III, and 23 (10.1%) as type IV. Type I had the shortest VDT (254 days), followed by types IV (381 days) and III (501 days), and then type II (993 days) (p < 0.05 each). Type I had a greater proportion of solid/micropapillary-predominant pattern than type II, and the lepidic-predominant pattern was more common in type II and III than in type I (p < 0.05 each). Furthermore, type II and IV SLADCs were correlated with positive epidermal growth factor receptor mutation (p < 0.05 each). Lastly, the Kaplan–Meier curves showed that the disease-free survival was longest for patients with type II tumors, followed by those with type III and IV tumors, and then those with type I tumors (p < 0.001 each).ConclusionA good understanding of the natural progression and pathological-molecular characteristics of different morphological SLADC types can help make accurate diagnoses, develop individual treatment strategies, and predict patient outcomes.Critical relevance statementA good understanding of the natural progression and pathological-molecular characteristics of different morphological solitary lung adenocarcinoma types can help make accurate diagnoses, develop individual treatment strategies, and predict patient outcomes.Key points• Type I–IV solitary lung adenocarcinomas exhibit varying natural progression on serial CT scans.• Morphological classification of solitary lung adenocarcinomas predicts histological subtype, gene status, and surgical prognosis.• This classification of solitary lung adenocarcinomas may help improve diagnostic, therapeutic, and prognosticating abilities.Graphical

Multi-cohort validation study of a four-gene signature for risk stratification and treatment response prediction in hepatocellular carcinoma

BackgroundThe intricate molecular landscape of hepatocellular carcinoma (HCC) presents a significant challenge to achieving precise risk stratification through clinical genetic testing. At present, there is a paucity of robust gene signatures that could assist clinicians in making clinical decisions for patients with HCC. MethodsWe obtained gene expression profiles of patients with HCC from 20 independent cohorts available in public databases. A gene signature was developed by employing two machine learning algorithms. In addition to validating the signature with high-throughput data in public cohorts, we external validated the signature in 64 HCC cases by RT-PCR method. We compared genomic, transcriptomic and proteomic features between different subgroups. We also compared our signature to 130 gene signatures that have already been published. ResultsWe developed a novel four-gene signature, designated as HCC4, that demonstrates significant potential for the prediction of survival outcomes in more than 1300 patients with HCC. The HCC4 also has potential for predicting recurrence and tumor volume doubling time, assessing transcatheter arterial chemoembolization and immunotherapy responses, and non-invasive detection of HCC. The high HCC4 score group shows a higher frequency of mutations in genes TP53, RB1 and TSC1/2, as well as increased activity of cell-cycle, glycolysis and hypoxia signaling pathways, higher cancer stemness score, and lower lipid metabolism activity. In seven HCC cohorts, HCC4 exhibited a higher average C-index in predicting overall survival compared to the 130 signatures previously published. Drug screening indicated that patients with high HCC4 scores were more sensitive to agents targeting AURKA, TUBB, JMJD6 and KIFC1. ConclusionsOur findings demonstrated that HCC4 is a powerful tool for improving risk stratification and for identifying HCC patients who are most likely to benefit from TACE treatment, immunotherapy, and other experimental therapies.

SAT521 Predictive Value of Tumor Volumetrics in Patients with Medullary Thyroid Cancer

Abstract Disclosure: N. Behairy: None. S. Gubbi: None. M.G. Pascoal: None. A. Bharadwaj: None. E.C. Wright: None. T. Abijo: None. N. Uttarkar Vikram: None. P. Veeraraghavan: None. C. Cochran: None. J. Glod: None. J. Klubo-Gwiezdzinska: None. Predictive Value of Tumor Volumetrics in Patients with Medullary Thyroid Cancer Background Medullary thyroid cancer (MTC) is a rare endocrine malignancy that can present either as a sporadic disease or as a part of inherited autosomal dominant multiple endocrine neoplasia type 2A (MEN2A) and 2B (MEN2B) syndromes. There is limited data on the prognostic value of the tumor volume (TV) doubling time (TVDT) in patients with sporadic and familial MTC. Therefore, the goal of this study was to examine the association between TVDT and disease-specific survival (DSS) in patients with metastatic MTC. Material and Methods This cohort study included patients with metastatic MTC for whom at least 3 follow-up CT/MRI scans revealed ≥2 measurable lesions and up to the 5 largest lesions in each affected organ were analyzed. The tumor volumes were measured in 2 dimensions (2D) per standard practice reporting and 3 dimensions (3D) using an ellipsoid formula. The average TVDT of all measured lesions in each organ with metastatic deposits was calculated using a previously reported formula. Calcitonin (Ct-DT) and CEA doubling times (CEA-DT) were assessed using the American Thyroid Association Guidelines calculator. The association between DSS and TVDT, Ct-DT, and CEA-DT was tested using Cox regression. Correlations were assessed using a Spearman correlation coefficient. The study was approved by the Institution Review Board. Results The study cohort consisted of 51 patients (27 women, 53%) with age at the initial scan 24 ± 17 years and an average primary tumor size of 3.3±2.0 cm. Seven patients presented with sporadic MTC, 12 with MEN2A and 32 with MEN2B. During a follow-up of 8.0±4.3 years, 28/51 (55%) patients had disease progression and required systemic or local therapies and 9/51 (18%) patients died. A total of 456 scans were analyzed documenting that the organs with the most rapid TVDT were neck masses in 25/51 (49%), liver metastases in 16/51 (31%), lung nodules in 7/51 (14%) and prostate lesions in 3/51 (6%) patients. There was a strong correlation between 2D and 3D TVDT (r = 0.96) as well as between Ct-DT and CEA-DT (r = 0.82). However, the correlation between 2D TVDT and Ct-DT and CEA-DT were low (r = 0.45 for both). The DSS hazard ratios (HR) for DT &amp;lt;1 year compared to ≥3 years were 8.2 (1.5-45.4) for 2D TVDT, 8.7 (1.6-48.2) for 3D TVDT, 15.9 (1.72-146.7) for Ct-DT, and 11.72 (2.0-68.7) for CEA-DT. DSS was not associated with either familial or sporadic etiology of MTC (p = 0.38), gender (p = 0.12), or age at initial scan (p = 0.85). Conclusions Apart from Ct-DT and CEA-DT, TVDT is a valuable prognostic factor in metastatic MTC. Given a strong correlation between 2D and 3D TVDT, standard 2D-based TVDT measurements might be used as an easily obtained and clinically feasible prognostic marker of DSS in MTC patients. Presentation Date: Saturday, June 17, 2023

A Novel Magnetic Resonance Imaging-Based Radiomics and Clinical Predictive Model for the Regrowth of Postoperative Residual Tumor in Non-Functioning Pituitary Neuroendocrine Tumor.

Background and Objectives: To develop a novel magnetic resonance imaging (MRI)-based radiomics-clinical risk stratification model to predict the regrowth of postoperative residual tumors in patients with non-functioning pituitary neuroendocrine tumors (NF-PitNETs). Materials and Methods: We retrospectively enrolled 114 patients diagnosed as NF-PitNET with postoperative residual tumors after the first operation, and the diameter of the tumors was greater than 10 mm. Univariate and multivariate analyses were conducted to identify independent clinical risk factors. We identified the optimal sequence to generate an appropriate radiomic score (Rscore) that combined pre- and postoperative radiomic features. Three models were established by logistic regression analysis that combined clinical risk factors and radiomic features (Model 1), single clinical risk factors (Model 2) and single radiomic features (Model 3). The models' predictive performances were evaluated using receiver operator characteristic (ROC) curve analysis and area under curve (AUC) values. A nomogram was developed and evaluated using decision curve analysis. Results: Knosp classification and preoperative tumor volume doubling time (TVDT) were high-risk factors (p < 0.05) with odds ratios (ORs) of 2.255 and 0.173. T1WI&T1CE had a higher AUC value (0.954) and generated an Rscore. Ultimately, the AUC of Model 1 {0.929 [95% Confidence interval (CI), 0.865-0.993]} was superior to Model 2 [0.811 (95% CI, 0.704-0.918)] and Model 3 [0.844 (95% CI, 0.748-0.941)] in the training set, which were 0.882 (95% CI, 0.735-1.000), 0.834 (95% CI, 0.676-0.992) and 0.763 (95% CI, 0.569-0.958) in the test set, respectively. Conclusions: We trained a novel radiomics-clinical predictive model for identifying patients with NF-PitNETs at increased risk of postoperative residual tumor regrowth. This model may help optimize individualized and stratified clinical treatment decisions.

Prediction of Surgical Outcome by Tumor Volume Doubling Time via Stereo Imaging Software in Early Non-Small Cell Lung Cancer.

Volume doubling time (VDT) has been proven to be a powerful predictor of lung cancer progression. In non-small cell lung cancer patients receiving sublobar resection, the discussion of correlation between VDT and surgery was absent. We proposed to investigate the surgical outcomes according to VDT. We retrospectively studied 96 cases post sublobar resection from 2012 to 2018, collecting two chest CT scans preoperatively of each case and calculating the VDT. The receiver operating characteristic curve was constructed to identify the optimal cut-off point of VDTs as 133 days. We divided patients into two groups: VDT < 133 days and VDT ≥ 133 days. Univariable and multivariable analyses were performed for comparative purposes. Univariable and multivariable analyses revealed that the consolidation and tumor diameter ratio was the factor of overall survival (OS), and VDT was the only factor of disease-free survival (DFS). The five year OS rates of patients with VDTs ≥ 133 days and VDTs < 133 days, respectively, were 89.9% and 71.9%, and the five year DFS rates were 95.9% and 61.5%. As VDT serves as a powerful prognostic predictor and provides an essential role in planning surgical procedures, the evaluation of VDT preoperatively is highly suggested.

A two-stages global sensitivity analysis by using the δ sensitivity index in presence of correlated inputs: application on a tumor growth inhibition model based on the dynamic energy budget theory

Global sensitivity analysis (GSA) evaluates the impact of variability and/or uncertainty of the model parameters on given model outputs. GSA is useful for assessing the quality of Pharmacometric model inference. Indeed, model parameters can be affected by high (estimation) uncertainty due to the sparsity of data. Independence between model parameters is a common assumption of GSA methods. However, ignoring (known) correlations between parameters may alter model predictions and, then, GSA results. To address this issue, a novel two-stages GSA technique based on the δ index, which is well-defined also in presence of correlated parameters, is here proposed. In the first step, statistical dependencies are neglected to identify parameters exerting causal effects. Correlations are introduced in the second step to consider the real distribution of the model output and investigate also the ‘indirect’ effects due to the correlation structure. The proposed two-stages GSA strategy was applied, as case study, to a preclinical tumor-in-host-growth inhibition model based on the Dynamic Energy Budget theory. The aim is to evaluate the impact of the model parameter estimate uncertainty (including correlations) on key model-derived metrics: the drug threshold concentration for tumor eradication, the tumor volume doubling time and a new index evaluating the drug efficacy-toxicity trade-off. This approach allowed to rank parameters according to their impact on the output, discerning whether a parameter mainly exerts a causal or ‘indirect’ effect. Thus, it was possible to identify uncertainties that should be necessarily reduced to obtain robust predictions for the outputs of interest.

Tumor volume doubling time as a potential predictor of prognosis in clinical stage I lung squamous cell carcinoma.

Tumor volume doubling time (VDT) has been shown to predict prognosis in various non-small cell lung carcinoma with scant evidence for lung squamous cell carcinoma (SCC). The purpose of this study was to investigate the prognostic value of tumor VDT in resected lung SCCs. In this study, subjects were 51 patients who underwent lobectomy for clinical stage I SCC of the peripheral lung at our institution between January 2006 and April 2020. Univariable and multivariable analyses of overall survival (OS) and recurrence-free survival (RFS) were performed using the Cox proportional hazards model. The Kaplan-Meier method was used to create OS and RFS curves and to determine statistical significance. The cut-off value of VDT was defined by receiver operating characteristic (ROC) curve analysis on survival. Multivariable analysis found only VDT (HR, 0.990; 95% CI: 0.979-0.997) to be an independent predictor of OS. Also, only VDT (HR, 0.989; 95% CI: 0.978-0.995) was an independent predictor of RFS. The 5-year OS rates were 88.4% and 30.4% in the long (≥150 days) and short (<150 days) VDT groups, respectively (P=0.002). The 5-year RFS rates were 88.8% and 26.5% in the long (≥150 days) and short (<150 days) VDT groups, respectively (P<0.001). Tumor VDT was found to be a useful prognostic predictor in clinical stage I lung SCC in this study.

Recurrence rate-based strategy to tailor surveillance scheduling in single hepatocellular carcinoma ≤2 cm after curative therapy: Analysis of 6,105 global patients.

e16225 Background: For initially diagnosed very early-stage hepatocellular carcinoma (HCC, VEH, i.e. single Hepatocellular Carcinoma ≤2 cm), surveillance after surgical resection (SR) or radiofrequency ablation (RFA) remains largely unclear. We conducted this multicenter study to explore optimal surveillance strategies and evaluate the current surveillance strategies for initially diagnosed VEH after SR/RFA to support the clinical follow-up schedule. Methods: A total of 6,105 initially diagnosed VEH patients who received SR/RFA from global centers were included. After the measurement of the recurrence rate of each month, delayed detection times for tumor recurrence of various follow-up strategies were calculated. The candidate strategies were evaluated according to the delayed detection times and the tumor volume doubling time (TVDT), and a preferable surveillance strategy was recommended. Results: The cumulative 1-, 2-, 3-, 4-, and 5-year recurrence probabilities were 12.7%, 25.9%, 35.7%, 43.7%, and 49.3%, respectively. Based on the monthly recurrence rate, programing surveillance schedules were tailored, which were more effective than current surveillance strategies under the same visits. When patients were followed up every 6 months, the delayed recurrence detection after curative treatment was expected to be 2.35 to 2.57 months. Given that 93.3% of patients did not have &gt;TVDT with a rapid growth subtype when recurrent nodules were detected, a surveillance strategy with a 6-month interval was recommended. Conclusions: Six months of interval surveillance was conservatively supported in patients with VEH after curative therapy.

Abstract 41: Subcutaneous growth and immune cell profiling of BT-474 human breast carcinoma in four strains of triple immunodeficient mice

Abstract Triple immunodeficient mouse models, that lack functional T cells, B cells, and natural killer cells, are necessary when evaluating human cancer cell growth and cell-based therapy activity, allowing for assessment without innate mouse immune system involvement. Due to limited colony sizes at any given vendor, study timelines can sometimes become compromised unless a sufficient alternative is validated. Site location can also be a factor, as licensing restrictions may be an issue for international corporations. In an effort to prove overall similarities across four strains of triple immunodeficient mice, the growth characteristics of BT-474 were compared in female NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ (NSG) mice, NOD.CB17-Prkdcscid IL2rgtm1/BcgenHsd (B-NDG) mice, NOD-Prkdcem26Cd52Il2rgem26Cd22/NjuCrl (NCG) mice, and NOD.Cg-Prkdcscid Il2rgtm1Sug/JicTac (CIEA NOG) mice. An immune cell profile was also performed across these four mouse strains and evaluated via flow cytometry to observe any immune cell subset differences in blood, spleen, and tumor samples. Samples analyzed post implant were collected when subcutaneous tumors were ~500 mm3. Model development studies were completed previously to optimize tumor growth kinetics. Historic growth conditions were BT-474 cells implanted at 1.0E+07 cells/implant in the presence of an extracellular matrix into the high right axilla of female NSG mice. Using the same optimized growth conditions, NSG, B-NDG, NCG, and CIEA NOG mice were implanted with BT-474 cells. BT-474 grew well in all the tested mouse strains, producing 100% take rate. Compared to NSG mice, median tumor volume doubling times differed by 1-5 days, median times to an evaluation size of 150 mm3 (typical study enrollment tumor volume) differed by +/- ~4 days and median time to an evaluation size of 1250 mm3 (tumor volume at the end of life) differed by +/- ~10 days. BT-474 did not induce body weight loss in any of the tested mouse strains and all clinical observations were similar. Flow cytometry was performed to quantify lymphocyte and myeloid immune subsets in blood, spleen, and tumor. Overall, compared to NSG mice, the absolute counts were similar for all immune subsets measured except for regulatory T cells (Tregs). B-NDG, NCG, and CIEA NOG mice had reduced Treg numbers in the spleen of tumor-bearing mice. In the tumor, Treg numbers were lower in the B-NDG and CIEA NOG mice. No differences were observed for any immune subset in the blood. Overall, the tumor growth kinetics of BT-474 in B-NDG mice was most similar to historical data using NSG mice. The flow data also confirmed that each strain’s immune cell population generally looked very similar, with limited differences between the four strains of triple immunodeficient mice. Citation Format: Justin Snider, Derrik Germain, Lauren Kucharczyk, Anita Zaitouna, Erin Trachet, Scott Wise. Subcutaneous growth and immune cell profiling of BT-474 human breast carcinoma in four strains of triple immunodeficient mice [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 41.