Analysis of inter-patient variations in tumour growth rate

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.

Assessing the impact of COVID-19 on liver cancer management (CERO-19)

Background & Aims

The coronavirus disease 2019 (COVID-19) pandemic has posed unprecedented challenges to healthcare systems and it may have heavily impacted patients with liver cancer (LC). Herein, we evaluated whether the schedule of LC screening or procedures has been interrupted or delayed because of the COVID-19 pandemic.

Methods

An international survey evaluated the impact of the COVID-19 pandemic on clinical practice and clinical trials from March 2020 to June 2020, as the first phase of a multicentre, international, and observational project. The focus was on patients with hepatocellular carcinoma or intrahepatic cholangiocarcinoma, cared for around the world during the first COVID-19 pandemic wave.

Results

Ninety-one centres expressed interest to participate and 76 were included in the analysis, from Europe, South America, North America, Asia, and Africa (73.7%, 17.1%, 5.3%, 2.6%, and 1.3% per continent, respectively). Eighty-seven percent of the centres modified their clinical practice: 40.8% the diagnostic procedures, 80.9% the screening programme, 50% cancelled curative and/or palliative treatments for LC, and 41.7% modified the liver transplantation programme. Forty-five out of 69 (65.2%) centres in which clinical trials were running modified their treatments in that setting, but 58.1% were able to recruit new patients. The phone call service was modified in 51.4% of centres which had this service before the COVID-19 pandemic (n = 19/37).

Conclusions

The first wave of the COVID-19 pandemic had a tremendous impact on the routine care of patients with liver cancer. Modifications in screening, diagnostic, and treatment algorithms may have significantly impaired the outcome of patients. Ongoing data collection and future analyses will report the benefits and disadvantages of the strategies implemented, aiding future decision-making.

Lay summary

The coronavirus disease 2019 (COVID-19) pandemic has posed unprecedented challenges to healthcare systems globally. Herein, we assessed the impact of the first wave pandemic on patients with liver cancer and found that routine care for these patients has been majorly disrupted, which could have a significant impact on outcomes.

Current decision-making in meningiomas

The incidence of meningiomas is rising and the number of incidental cases is increasing steadily. The efficiency and the safety of each treatment strategy are also improving over time. Therefore the indications to treat meningiomas are constantly changing. The aim of meningioma treatment is keeping the patient fully functional while achieving long-term relief or prevention from problems related to intracranial tumor growth. This chapter reviews the natural history and treatment results and aims to put together the information for the most objective decision-making in treating meningiomas. Factors acting on the treatment decision such as anatomical localization, symptomatology, variations in tumor biology, recurrence status, age and co-morbidities, operative gains, and patient preference are individually discussed.

When did the glioblastoma start growing, and how much time can be gained from surgical resection? A model based on the pattern of glioblastoma growth in vivo

OBJECTIVES

Observational data on the natural course of tumor growth in humans is sparse, and mathematical models of tumor growth are often needed to answer questions related to growth. In this study, a theoretical model of glioblastoma growth was used to investigate two questions often asked by patients and clinicians. First, when did the tumor start growing? Second, how much survival time can be gained from various extents of surgical resection (EOR)?.

PATIENTS AND METHODS

A gompertzian growth curve was fitted from observational data of pre-treatment growth from 106 glioblastoma patients based on repeated volume segmentations. The curve was used to find the theoretical time since tumor initiation. In addition, as a proxy for the potential survival gain from surgery, the number of days until re-growth would reach the preoperative tumor volume were calculated for different extents of resection.

RESULTS

The estimated age of the glioblastomas at diagnosis was median 330 days, but ranging from 156 days to 776 days, depending on the tumor volume at diagnosis. The median survival gains from 50%, 75%, 90%, 95% and 99% EOR were, 1.4, 2.5, 3.6, 4.3, and 5.6 months, respectively. However, survival benefit from surgery also depends on lesion volume. In theory, 100 days may be gained from 95% EOR in a 10 mL lesion or a 50% EOR in a 90 ml lesion.

CONCLUSION

In conclusion, we postulate that glioblastoma might originate median 330 days before the diagnosis, assuming the same growth pattern and biology from day one. The theoretical survival benefit of glioblastoma resection is much higher with higher EORs, suggesting that the last milliliters of resection matter the most. Our data also suggest that gain from resection is higher in larger lesions, suggesting that lesion volume may be taken into account in clinical decision-making.

Analysis of volumetric response of pituitary adenomas receiving adjuvant CyberKnife stereotactic radiosurgery with the application of an exponential fitting model

Tumor control rates of pituitary adenomas (PAs) receiving adjuvant CyberKnife stereotactic radiosurgery (CK SRS) are high. However, there is currently no uniform way to estimate the time course of the disease. The aim of this study was to analyze the volumetric responses of PAs after CK SRS and investigate the application of an exponential decay model in calculating an accurate time course and estimation of the eventual outcome.A retrospective review of 34 patients with PAs who received adjuvant CK SRS between 2006 and 2013 was performed. Tumor volume was calculated using the planimetric method. The percent change in tumor volume and tumor volume rate of change were compared at median 4-, 10-, 20-, and 36-month intervals. Tumor responses were classified as: progression for >15% volume increase, regression for ≤15% decrease, and stabilization for ±15% of the baseline volume at the time of last follow-up. For each patient, the volumetric change versus time was fitted with an exponential model.The overall tumor control rate was 94.1% in the 36-month (range 18-87 months) follow-up period (mean volume change of -43.3%). Volume regression (mean decrease of -50.5%) was demonstrated in 27 (79%) patients, tumor stabilization (mean change of -3.7%) in 5 (15%) patients, and tumor progression (mean increase of 28.1%) in 2 (6%) patients (P = 0.001). Tumors that eventually regressed or stabilized had a temporary volume increase of 1.07% and 41.5% at 4 months after CK SRS, respectively (P = 0.017). The tumor volume estimated using the exponential fitting equation demonstrated high positive correlation with the actual volume calculated by magnetic resonance imaging (MRI) as tested by Pearson correlation coefficient (0.9).Transient progression of PAs post-CK SRS was seen in 62.5% of the patients receiving CK SRS, and it was not predictive of eventual volume regression or progression. A three-point exponential model is of potential predictive value according to relative distribution. An exponential decay model can be used to calculate the time course of tumors that are ultimately controlled.

Rapid Recurrence of a Benign Meningial Perineurioma

BACKGROUND

We describe a rare case of a rapidly recurring benign meningial-based perineurioma. Clinical, radiologic, and pathologic features of a rapidly recurring falxial perineurioma are described; the perineurioma was discovered incidentally in an 86-year-old woman.

CASE DESCRIPTION

Due to progressive gait disturbances and radiologically proven progression after a 3-year symptom-free interval, subtotal resection of a large falxial-based meningeal tumor was performed.

CONCLUSIONS

The pathologic examination confirmed the diagnosis of a perineurioma (World Health Organization grade I). Follow-up magnetic resonance tomography 5 months later due to neurologic deterioration revealed an abnormally rapidly growing and extensive local tumor recurrence. Due to the mass effect, reoperation was performed and adjuvant radiation of 20 Gy to the tumor bed was implemented thereafter. Meningeal-based perineuriomas of the central nervous system are extremely rare, and literature on proper management is scarce. Although histologic classification reveals a benign lesion, follow-up may be considered for this type of tumor.