10 Years of Pressurized Intraperitoneal Aerosol Chemotherapy (PIPAC): A Systematic Review and Meta-Analysis

Background: Pressurized intraperitoneal aerosol chemotherapy (PIPAC) is a novel intraperitoneal drug delivery method of low-dose chemotherapy as a pressurized aerosol in patients affected by peritoneal cancer of primary or secondary origin. We performed a systematic review and meta-analysis with the aim of assessing the feasibility, safety, and efficacy of PIPAC. Methods: A systematic literature search was performed using Medline and Web of Science databases from 1 January 2011, to inception, to 31 December 2021. Data were independently extracted by two authors. The Newcastle-Ottawa Scale was used to assess the quality and risk of bias of studies. Meta-analysis was performed for pathological response, radiological response, PCI variation along treatment, and for patients undergoing three or more PIPAC. Pooled analyses were performed using the Freeman–Tukey double arcsine transformation, and 95% CIs were calculated using Clopper–Pearson exact CIs in all instances. Results: A total of 414 papers on PIPAC were identified, and 53 studies considering 4719 PIPAC procedure in 1990 patients were included for analysis. The non-access rate or inability to perform PIPAC pooled rate was 4% of the procedures performed. The overall proportion of patients who completed 3 or more cycles of PIPAC was 39%. Severe toxicities considering CTCAE 3–4 were 4% (0% to 38.5%). In total, 50 studies evaluated deaths within the first 30 postoperative days. In the included 1936 patients were registered 26 deaths (1.3%). The pooled analysis of all the studies reporting a pathological response was 68% (95% CI 0.61–0.73), with an acceptable heterogeneity (I2 28.41%, p = 0.09). In total, 10 papers reported data regarding the radiological response, with high heterogeneity and a weighted means of 15% (0% to 77.8%). PCI variation along PIPAC cycles were reported in 14 studies. PCI diminished, increased, or remained stable in eight, one and five studies, respectively, with high heterogeneity at pooled analysis. Regarding survival, there was high heterogeneity. The 12-month estimated survival from first PIPAC for colorectal cancer, gastric cancer, gynecological cancer and hepatobiliary/pancreatic cancer were, respectively, 53%, 25%, 59% and 37%. Conclusions: PIPAC may be a useful treatment option for selected patients with PM, with acceptable grade 3 and 4 toxicity and promising survival benefit. Meta-analysis showed high heterogeneity of data among up-to-date available studies. In a subset analysis per primary tumor origin, pathological tumor regression was documented in 68% of the studies with acceptable heterogeneity. Pathological regression seems, therefore, a reliable outcome for PIPAC activity and a potential surrogate endpoint of treatment response. We recommend uniform selection criteria for patients entering a PIPAC program and highlight the urgent need to standardize items for PIPAC reports and datasets

Development of Targeted Alpha Particle Therapy for Solid Tumors

Abstract: Targeted alpha-particle therapy (TAT) aims to selectively deliver radionuclides emitting α-particles (cytotoxic payload) to tumors by chelation to monoclonal antibodies, peptides or small molecules that recognize tumor-associated antigens or cell-surface receptors. Because of the high linear energy transfer (LET) and short range of alpha (α) particles in tissue, cancer cells can be significantly damaged while causing minimal toxicity to surrounding healthy cells. Recent clinical studies have demonstrated the remarkable efficacy of TAT in the treatment of metastatic, castration-resistant prostate cancer. In this comprehensive review, we discuss the current consensus regarding the properties of the α-particle-emitting radionuclides that are potentially relevant for use in the clinic; the TAT-mediated mechanisms responsible for cell death; the different classes of targeting moieties and radiometal chelators available for TAT development; current approaches to calculating radiation dosimetry for TATs; and lead optimization via medicinal chemistry to improve the TAT radiopharmaceutical properties. We have also summarized the use of TATs in pre-clinical and clinical studies to dat

FORMULATION OF POPULATION PHARMACOKINETIC MODELS OF ANTI-CANCER AGENTS

The primary objective of the study is to assemble population pharmacokinetic models from the cancer pharmacokinetics literature for different types of anti-cancer drugs and to formulate them in ways suitable for input into cancer simulation programs. To fulfill the objectives, a step-based approach is adopted: 1)To catalogue the types of pharmacokinetic models through general review articles and books 2)To develop a search strategy for defining a body of research literature related to cancer pharmacokinetics in clinical trials for a limited set of drugs (Taxol, Platinum compounds. Fluoropyrimidine and Topoisomerase inhibitors) 3)To collect pharmacokinetic articles according to defined search criteria4)To gather information from the collected PK articles 5)To synthesize the information separately for each drug, using a questionnaire instrument and present them in template form for each class of antineoplastic agent.6)To formulate population pharmacokinetic models for each anti-cancer drug, from the constituent submodels for components of the overall model. This work will promote public health, specifically in support of the development of anti-cancer drug regimens for cancer patients, byproviding standardized information about pharmacokinetics for input into simulations

Bayesian Inference Methods Applied to Cancer Research

The purpose of this Thesis is to present a Bayesian analysis of oncological data sets with particular focus on cervical carcinomas and ovarian cancers. Bayesian methods of data analysis have a very long history, and have been used with great success in many disciplines, from Physics to Econometrics. Nonetheless, they remain very controversial among statisticians who belong to the orthodox - i.e, frequentist school, and are not well known by the medical community. To help in that direction, we reviewed in the introductory chapter the basic philosophical and practical differences between the two schools, and in the second chapter, we briefly reviewed the history of Bayesian methodology, from the early efforts of Thomas Bayes and of Pierre Simon de Laplace to the modern contributions of Harold Jeffreys, Richard Cox, and Edwin Jaynes. In many aspects of medical research, we deal with experimental data from which a certain proposition or hypothesis is validated. Unlike in physics, where we have strong and solid foundations such as Newton's law of motion, Snell's optical laws, Kirchoff's laws, Einstein's relativity theory, and many more, we do not have such privileges in medical research. Hence, many hypotheses are constantly tested as new evidence becomes available. One of the actively-researched medical areas is cancer research about which our understanding is still in its infancy. Numerous experiments (both in vivo and in vitro) and clinical trials have been conducted to further our knowledge; thus, Bayesian methodology finds its place to aid us in obtaining scientific inferences about certain propositions or hypotheses from available data and resources. In this work, we use data given to us by our medical collaborators at the Princess Margaret Hospital (PMH) in Toronto to carry out two main projects: Firstly, to make an inference about the oxygenation status (oxygen partial pressure, pO$_2$) within human cervical carcinomas and secondly, an inference about the effectiveness of various molecularly-targeted agents (MTAs) in phase II clinical trials of relapsed ovarian cancer patients. In the first problem, we address the challenges of tumor hypoxia - a state of oxygen deprivation in tumors. Currently, there are two methods to obtain tumor oxygen status, namely the direct Eppendorf needle electrode and the indirect immunohistochemical assay of a protein marker, Carbonic Anhydrase IX (CAIX). In this project, we introduce Bayesian probability theory to obtain inferences about tumor oxygenation from each technique and the concordance between the two techniques. From this study, we conclude that under certain conditions, two biopsies are sufficient to infer the tumor oxygenation level based on the immunohistochemical assays of CAIX. Additionally, there is a fair concordance between the direct and the indirect measurements of tumor oxygenation. In the latter problem, ovarian cancer is the topic of study. Ovarian cancer has the highest mortality rate among gynecological cancers and one that is known to relapse. CA-125 is still the most inexpensive biomarker for monitoring ovarian cancers. From the phase II clinical trial data, we demonstrate the survival advantage of CA-125 responsive group of patients by means of a non-parametric Kaplan-Meier statistic

A review of radiotherapy-induced late effects research after advanced technology treatments

The number of incident cancers and long-term cancer survivors is expected to increase substantially for at least a decade. Advanced technology radiotherapies, e.g., using beams of protons and photons, offer dosimetric advantages that theoretically yield better outcomes. In general, evidence from controlled clinical trials and epidemiology studies are lacking. To conduct these studies, new research methods and infrastructure will be needed. In the paper, we review several key research methods of relevance to late effects after advanced technology proton-beam and photon-beam radiotherapies. In particular, we focus on the determination of exposures to therapeutic and stray radiation and related uncertainties, with discussion of recent advances in exposure calculation methods, uncertainties, in silico studies, computing infrastructure, electronic medical records, and risk visualization. We identify six key areas of methodology and infrastructure that will be needed to conduct future outcome studies of radiation late effects