Comparison of tumor assessments using RECIST 1.1 and irRECIST, and association with overall survival

Neutrophil-to-Eosinophil Ratio Predicts the Efficacy of Avelumab in Patients With Advanced Urothelial Carcinoma Enrolled in the MALVA Study (Meet-URO 25)

BACKGROUND

Neutrophil-to-eosinophil ratio (NER) has been described to be associated with outcomes to immune checkpoint inhibitors (ICI) in several tumor types, but less is known about its role of in the response to avelumab in advanced urothelial cancer (aUC). Thus, we reported outcomes by NER of aUC patients treated with avelumab as maintenance after initial response to platinum-based chemotherapy and enrolled in the Maintenance with AVeLumAb ([MALVA] in advanced urothelial neoplasms in response to first-line chemotherapy: an observational retrospective study) study (Meet-URO 25).

PATIENTS AND METHODS

Median NER at baseline and after 3 cycles of avelumab were calculated. Progression-free survival (PFS) and overall survival (OS) by NER were reported.

RESULTS

At the cutoff date (April 15, 2023), a total of 109 patients were included. The median NER was 28.05 at baseline and 24.46 after 3 cycles of avelumab, respectively. Median PFS was not reached for patients with baseline NER less than the median (

CONCLUSION

NER Collapse

Key Words

• Biomarker
• Eosinophilia
• Predictive factors
• Prognostic factors

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MESH Headings

• Humans
• Antibodies, Monoclonal, Humanized/therapeutic use
• Male
• Female
• Aged
• Retrospective Studies
• Middle Aged
• Neutrophils
• Aged, 80 and over
• Urologic Neoplasms/drug therapy
• Urologic Neoplasms/pathology
• Prognosis
• Antineoplastic Agents, Immunological/therapeutic use
• Treatment Outcome
• Progression-Free Survival
• Carcinoma, Transitional Cell/drug therapy
• Carcinoma, Transitional Cell/pathology
• Adult

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Affiliation(s)

Elisabetta Gambale Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy; Careggi University Hospital, Clinical Oncology, Florence, Italy
Marco Maruzzo Oncology Unit 1, Istituto Oncologico Veneto, IOV - IRCCS, Padova, Italy
Carlo Messina Ospedale Arnas Civico, Clinical Oncology, Palermo, Italy
Irene De Gennaro Aquino Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy; Careggi University Hospital, Clinical Oncology, Florence, Italy
Ismaela Anna Vascotto Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy; Careggi University Hospital, Clinical Oncology, Florence, Italy
Virginia Rossi Careggi University Hospital, Clinical Oncology, Florence, Italy
Davide Bimbatti Oncology Unit 1, Istituto Oncologico Veneto, IOV - IRCCS, Padova, Italy
Nicolò Cavasin Oncology Unit 1, Istituto Oncologico Veneto, IOV - IRCCS, Padova, Italy
Marco Messina Ospedale Arnas Civico, Clinical Oncology, Palermo, Italy
Alessia Mennitto University Hospital Maggiore della Carità, Division of Oncology, Novara, Italy
Sara Elena Rebuzzi Ospedale San Paolo, Medical Oncology Unit, Savona, Italy; Department of Internal Medicine and Medical Specialties (Di.M.I.), University of Genoa, Genoa, Italy
Cecilia Nasso Medical Oncology, Ospedale Santa Corona, 17027 Pietra Ligure, Italy
Chiara Mercinelli Azienda Ospedaliero-Universitaria Pisana, Medical Oncology Unit 2, Pisa, Italy; Department of Medical Oncology, IRRCS San Raffaele Hospital, Milan, Italy
Brigida Anna Maiorano Department of Medical Oncology, IRRCS San Raffaele Hospital, Milan, Italy; Oncology Unit, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo
Martina Fanelli University Hospital of Udine, Department of Oncology, Udine, Italy
Mariella Sorarù Ospedale di Camposampiero, U.O. Oncologia, Camposampiero, Italy
Federico Scolari Department of Biomedical, Experimental and Clinical Sciences, University of Florence, Florence, Italy
Marinella Micol Mela Careggi University Hospital, Clinical Oncology, Florence, Italy
Luca Galli Azienda Ospedaliero-Universitaria Pisana, Medical Oncology Unit 2, Pisa, Italy
Alessia Salfi Azienda Ospedaliero-Universitaria Pisana, Medical Oncology Unit 2, Pisa, Italy
Mimma Rizzo Oncologia Medica Universitaria Azienda Ospedaliera Universitaria Consorziale Policlinico di Bari piazza Giulio Cesare, 11, 70124 Bari
Silvia Puglisi IRCCS Ospedale Policlinico San Martino, Genoa, Italy
Valentina Orlando Department of Oncology, Ospedale Maggiore, Trieste, Italy
Giuseppe Fornarini IRCCS Ospedale Policlinico San Martino, Genoa, Italy
Alessandro Rametta Medical Oncology Department, Fondazione IRCCS Istituto Nazionale dei Tumori, Via Giacomo Venezian 1, Milan, Italy
Patrizia Giannatempo Medical Oncology Department, Fondazione IRCCS Istituto Nazionale dei Tumori, Via Giacomo Venezian 1, Milan, Italy
Linda Cerbone Department of Medical Oncology, San Camillo Forlanini Hospital, Rome, Italy
Laura Doni Careggi University Hospital, Clinical Oncology, Florence, Italy
Giandomenico Roviello Department of Health Sciences, Section of Clinical Pharmacology and Oncology, University of Florence, Viale Pieraccini, 6, 50139 Florence, Italy
Serena Pillozzi Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy; Careggi University Hospital, Clinical Oncology, Florence, Italy
Lorenzo Antonuzzo Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy; Careggi University Hospital, Clinical Oncology, Florence, Italy

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From immune equilibrium to tumor ecodynamics

Objectives

There is no theory to quantitatively describe the complex tumor ecosystem. At the same time, cancer immunotherapy is considered a revolution in oncology, but the methods used to describe tumors and the criteria used to evaluate efficacy are not keeping pace. The purpose of this study is to establish a new theory for quantitatively describing the tumor ecosystem, innovating the methods of tumor characterization, and establishing new efficacy evaluation criteria for cancer immunotherapy.

Methods

Based on the mathematization of immune equilibrium theory and the establishment of immunodynamics in a previous study, the method of reverse immunodynamics was used, namely, the immune braking force was regarded as the tumor ecological force and the immune force was regarded as the tumor ecological braking force, and the concept of momentum in physics was applied to the tumor ecosystem to establish a series of tumor ecodynamic equations. These equations were used to solve the fundamental and applied problems of the complex tumor ecosystem.

Results

A series of tumor ecodynamic equations were established. The tumor ecological momentum equations and their component factors could be used to distinguish disease progression, pseudoprogression, and hyperprogression in cancer immunotherapy. On this basis, the adjusted tumor momentum equations were established to achieve the equivalence of tumor activity (including immunosuppressive activity and metabolic activity) and tumor volume, which could be used to calculate individual disease remission rate and establish new efficacy evaluation criteria (ieRECIST) for immunotherapy of solid tumor based on tumor ecodynamics. At the same time, the concept of moving cube-to-force square ratio and its expression were proposed to calculate the area under the curve of tumor ecological braking force of blood required to achieve an individual disease remission rate when the adjusted tumor ecological momentum was known.

Conclusions

A new theory termed tumor ecodynamics emphasizing both tumor activity and tumor volume is established to solve a series of basic and applied problems in the complex tumor ecosystem. It can be predicted that the future will be the era of cancer immune ecotherapy that targets the entire tumor ecosystem.

Immune checkpoint inhibitor (ICI)-based treatment beyond progression with prior immunotherapy in patients with driver-gene negative advanced non-small cell lung cancer

BACKGROUND

No definite conclusion has yet to be reached for immunotherapy beyond progression(IBP) of first-line immunotherapy as the second-line treatment for advanced NSCLC patients with negative driver genes. Therefore a retrospective study was conducted to evaluate the efficacy of IBP in this population and investigated whether the cycles best response and progressive mode of first-line immunotherapy could affect the results.

PATIENTS AND METHODS

The clinical data of patients with advanced NSCLC whose response was evaluated as progressive disease (PD) after receiving a PD-1/PD-L1 inhibitors as first-line therapy were retrospectively collected and the patients were assigned to the IBP and non-IBP groups. The overall survival (OS), progression-free survival (PFS) were evaluated between the two groups. The survival effects of cycles best response and progressive mode of first-line immunotherapy were also evaluated.

RESULTS

Between January 2019 and January 2022, a total of 121 patients was evaluated as PD after first-line immunotherapy in our institution; 53 (43.8%) patients were included in the IBP group and 68 (56.2%) patients were included in the non-IBP group. The OS and PFS were no significantly different between the two groups in whole population. Further analysis revealed the OS was prolonged with the prolongation of first-line medication cycle. The median OS was 15.4m (15.4 vs 10.8 p=0.047) 16.1m (16.1 vs 10.8 p=0.039), 16.3m (16.3 vs 10.9 p=0.029) for patients with ≥4, ≥6, ≥8 cycles in first-line immunotherapy, respectively. The advantages of OS and PFS were also seen in the subgroup of PR (best response) and oligo progression of first-line immunotherapy.

CONCLUSIONS

The clinical outcomes of IBP were similar to those of non-IBP in patients with PD after first-line immnuotherapy in advanced NSCLC. But more cycles, PR as best response and oligo progression in first-line was benefit.

Bevacizumab, olaparib, and durvalumab in patients with relapsed ovarian cancer: a phase II clinical trial from the GINECO group

Most patients with advanced ovarian cancer (AOC) ultimately relapse after platinum-based chemotherapy. Combining bevacizumab, olaparib, and durvalumab likely drives synergistic activity. This open-label phase 2 study (NCT04015739) aimed to assess activity and safety of this triple combination in female patients with relapsed high-grade AOC following prior platinum-based therapy. Patients were treated with olaparib (300 mg orally, twice daily), the bevacizumab biosimilar FKB238 (15 mg/kg intravenously, once-every-3-weeks), and durvalumab (1.12 g intravenously, once-every-3-weeks) in nine French centers. The primary endpoint was the non-progression rate at 3 months for platinum-resistant relapse or 6 months for platinum-sensitive relapse per RECIST 1.1 and irRECIST. Secondary endpoints were CA-125 decline with CA-125 ELIMination rate constant K (KELIM-B) per CA-125 longitudinal kinetics over 100 days, progression free survival and overall survival, tumor response, and safety. Non-progression rates were 69.8% (90%CI 55.9%-80.0%) at 3 months for platinum-resistant relapse patients (N = 41), meeting the prespecified endpoint, and 43.8% (90%CI 29.0%-57.4%) at 6 months for platinum-sensitive relapse (N = 33), not meeting the prespecified endpoint. Median progression-free survival was 4.1 months (95%CI 3.5-5.9) and 4.9 months (95%CI 2.9-7.0) respectively. Favorable KELIM-B was associated with better survival. No toxic deaths or major safety signals were observed. Here we show that further investigation of this triple combination may be considered in AOC patients with platinum-resistant relapse.

Immunotherapy for lung cancer

Immune checkpoint blockers have transformed non-small-cell lung cancer treatment, but they can lead to autoimmune and inflammatory side effects, leading to the concurrent use of immunosuppressive treatments. In this analysis, we delve into the potential of antibodies checkpoint blockade, focusing on CTLA-4 inhibition using ipilimumab, as a groundbreaking cancer immunotherapy. We also concentrate on the role of biomarkers, particularly PD-L1 activity and mutation significance, in predicting the response to programmed cell death protein 1 blockage and the prevalence of side effects associated with immune-related side effects. In describing the patterns of cancer response to immunotherapy, we underline the limitations of response assessment criteria like RECIST and World Health Organization. We also stress the necessity of ongoing studies and clinical trials, standardized guidelines, and additional research to improve response assessment in the era of immunotherapy.

Navigating the ICI Combination Treatment Journey: Patterns of Response and Progression to First-Line ICI-Based Combination Treatment in Metastatic Renal Cell Carcinoma

The use of immune checkpoint inhibitors (ICIs) in combination with tyrosine kinase inhibitors or other ICIs has significantly improved the prognosis for patients with mccRCC. This marks a major milestone in the treatment of mccRCC. Nonetheless, most patients will discontinue first-line therapy. In this narrative review, we analyze the different patterns of treatment discontinuation in the four pivotal phase III trials that have shown an improvement in overall survival in mccRCC first-line therapy, starting from 1 January 2017 to 1 June 2023. We highlight the different discontinuation scenarios and their influences on subsequent treatment options, aiming to provide more data to clinicians to navigate a complex decision-making process through a narrative review approach. We have identified several causes for discontinuations for patients treated with ICI-based combinations, such as interruption for drug-related adverse events, ICI treatment completion, treatment discontinuation due to complete response or maximum clinical benefit, or due to progression (pseudoprogression, systemic progression, and oligoprogression); for each case, an extensive analysis of the trials and current medical review has been conducted.

Cancer immunotherapy efficacy and machine learning

INTRODUCTION

Immunotherapy is one of the major breakthroughs in the treatment of cancer, and it has become a powerful clinical strategy, however, not all patients respond to immune checkpoint blockade and other immunotherapy strategies. Applying machine learning (ML) techniques to predict the efficacy of cancer immunotherapy is useful for clinical decision-making.

AREAS COVERED

Applying ML including deep learning (DL) in radiomics, pathomics, tumor microenvironment (TME) and immune-related genes analysis to predict immunotherapy efficacy. The studies in this review were searched from PubMed and ClinicalTrials.gov (January 2023).

EXPERT OPINION

An increasing number of studies indicate that ML has been applied to various aspects of oncology research, with the potential to provide more effective individualized immunotherapy strategies and enhance treatment decisions. With advances in ML technology, more efficient methods of predicting the efficacy of immunotherapy may become available in the future.

Case Report: Long-term metabolic response of metastatic uveal melanoma to pembrolizumab on FDG-PET/CT despite a serial pseudoprogressions phenomenon

Uveal melanoma (UV) is a rare and aggressive melanoma with poor 1-year survival. up to 50% of UV patients develop metastases, mainly to the liver. Here, the authors present a 2-deoxy-2-[18F] fluoro-D-glucose positron emission tomography (18F-FDG-PET) study of a very rare case of secondarily metastatic UV in an 81-year-old Caucasian with a dramatic response to pembrolizumab associated with serial pseudogression. 18F-FDG-PET associated with clinical status and peripheral blood derived neutrophil-to-lymphocyte ratio (dNLR) were performed to guide therapeutic strategy due to an atypical pseudoprogression phenomenon.

Trial Design for Cancer Immunotherapy: A Methodological Toolkit

Immunotherapy with checkpoint inhibitors (CPIs) and cell-based products has revolutionized the treatment of various solid tumors and hematologic malignancies. These agents have shown unprecedented response rates and long-term benefits in various settings. These clinical advances have also pointed to the need for new or adapted approaches to trial design and assessment of efficacy and safety, both in the early and late phases of drug development. Some of the conventional statistical methods and endpoints used in other areas of oncology appear to be less appropriate in immuno-oncology. Conversely, other methods and endpoints have emerged as alternatives. In this article, we discuss issues related to trial design in the early and late phases of drug development in immuno-oncology, with a focus on CPIs. For early trials, we review the most salient issues related to dose escalation, use and limitations of tumor response and progression criteria for immunotherapy, the role of duration of response as an endpoint in and of itself, and the need to conduct randomized trials as early as possible in the development of new therapies. For late phases, we discuss the choice of primary endpoints for randomized trials, review the current status of surrogate endpoints, and discuss specific statistical issues related to immunotherapy, including non-proportional hazards in the assessment of time-to-event endpoints, alternatives to the Cox model in these settings, and the method of generalized pairwise comparisons, which can provide a patient-centric assessment of clinical benefit and be used to design randomized trials.

Immune checkpoint inhibitors in hepatocellular carcinoma: emerging challenges in clinical practice

Systemic therapy for advanced hepatocellular carcinoma has expanded at an unprecedented pace over the past 5 years. After tyrosine kinase inhibitors dominated the field for more than a decade, immune checkpoint inhibitor (ICI)-based therapies have become the main component in systemic first-line treatment of this cancer. Delivery of immunotherapy in routine clinical practice recognises several challenges. In this Viewpoint, we discuss the major gaps in knowledge around the role of ICI-based therapies in patients with Child-Pugh class B. We discuss the challenges in individuals with rare histological subtypes of primary liver cancer, including combined hepatocellular-cholangiocarcinoma, fibrolamellar hepatocellular carcinoma, and sarcomatoid hepatocellular carcinoma. We also review data on ICI rechallenge in patients previously treated with ICIs, and discuss atypical patterns of progression related to immunotherapy (ie, hyperprogressive disease and pseudoprogression).

Imaging biomarkers for clinical applications in neuro-oncology: current status and future perspectives

Biomarker discovery and development are popular for detecting the subtle diseases. However, biomarkers are needed to be validated and approved, and even fewer are ever used clinically. Imaging biomarkers have a crucial role in the treatment of cancer patients because they provide objective information on tumor biology, the tumor's habitat, and the tumor's signature in the environment. Tumor changes in response to an intervention complement molecular and genomic translational diagnosis as well as quantitative information. Neuro-oncology has become more prominent in diagnostics and targeted therapies. The classification of tumors has been actively updated, and drug discovery, and delivery in nanoimmunotherapies are advancing in the field of target therapy research. It is important that biomarkers and diagnostic implements be developed and used to assess the prognosis or late effects of long-term survivors. An improved realization of cancer biology has transformed its management with an increasing emphasis on a personalized approach in precision medicine. In the first part, we discuss the biomarker categories in relation to the courses of a disease and specific clinical contexts, including that patients and specimens should both directly reflect the target population and intended use. In the second part, we present the CT perfusion approach that provides quantitative and qualitative data that has been successfully applied to the clinical diagnosis, treatment and application. Furthermore, the novel and promising multiparametric MR imageing approach will provide deeper insights regarding the tumor microenvironment in the immune response. Additionally, we briefly remark new tactics based on MRI and PET for converging on imaging biomarkers combined with applications of bioinformatics in artificial intelligence. In the third part, we briefly address new approaches based on theranostics in precision medicine. These sophisticated techniques merge achievable standardizations into an applicatory apparatus for primarily a diagnostic implementation and tracking radioactive drugs to identify and to deliver therapies in an individualized medicine paradigm. In this article, we describe the critical principles for imaging biomarker characterization and discuss the current status of CT, MRI and PET in finiding imaging biomarkers of early disease.

Immunotherapy in hepatocellular carcinoma: how will it reshape treatment sequencing?

The treatment landscape of advanced hepatocellular carcinoma (HCC) has broadened with immune checkpoint inhibitors (ICIs) setting a novel standard of care. With the increased number of therapies either in first or in further line, disentangling the possible treatment sequences has become much more complex. Yet, all the second-line therapies have been evaluated after sorafenib. After ICIs, offering multikinase inhibitors is a widespread approach, either shifting forward sorafenib or lenvatinib, or choosing among regorafenib or cabozantinib, already approved in the refractory setting. Under specific circumstances, ICIs could be maintained beyond disease progression in patients with proven clinical benefit, as supported by some data emerging from phase III clinical trials with immunotherapy in HCC. Rechallenge with ICIs is an additional attractive alternative, although requiring careful and individual evaluation as efficacy and safety of such a strategy have not been yet clarified. Still, a considerable number of patients displays primary resistance to ICIs and might benefit from antiangiogenics either alone or in addition to ICIs instead. Hopefully, the ongoing clinical trials will enlighten regarding the most effective treatment pathways. The identification of predictive correlates of response to immunotherapy will help treatment allocation at each stage, thus representing an urgent matter to address in HCC research. With programmed death ligand 1 expression, tumor mutational burden, and microsatellite status being inadequate biomarkers in HCC, patient characteristics, drug safety profile, and regulatory approval remain key elements to acknowledge in routine practice. Despite the tissue remaining a preferred source, biomarkers discovery could take advantage of liquid biopsy to overcome the matter of tissue availability and track tumor changes. Lastly, tumor genetic phenotypes, tumor microenvironment features, gut microbiome, and markers of immune response and systemic inflammation are all potential emergent predictors of response to ICIs, pending validation in the clinical setting.

Skin Cancer Pathobiology at a Glance: A Focus on Imaging Techniques and Their Potential for Improved Diagnosis and Surveillance in Clinical Cohorts

Early diagnosis is essential for completely eradicating skin cancer and maximizing patients' clinical benefits. Emerging optical imaging modalities such as reflectance confocal microscopy (RCM), optical coherence tomography (OCT), magnetic resonance imaging (MRI), near-infrared (NIR) bioimaging, positron emission tomography (PET), and their combinations provide non-invasive imaging data that may help in the early detection of cutaneous tumors and surgical planning. Hence, they seem appropriate for observing dynamic processes such as blood flow, immune cell activation, and tumor energy metabolism, which may be relevant for disease evolution. This review discusses the latest technological and methodological advances in imaging techniques that may be applied for skin cancer detection and monitoring. In the first instance, we will describe the principle and prospective clinical applications of the most commonly used imaging techniques, highlighting the challenges and opportunities of their implementation in the clinical setting. We will also highlight how imaging techniques may complement the molecular and histological approaches in sharpening the non-invasive skin characterization, laying the ground for more personalized approaches in skin cancer patients.

What is the optimal duration of immune checkpoint inhibitors in malignant tumors?

Immunotherapy, represented by immune checkpoint inhibitors (ICIs), has made a revolutionary difference in the treatment of malignant tumors, and considerably extended patients' overall survival (OS). In the world medical profession, however, there still reaches no clear consensus on the optimal duration of ICIs therapy. As reported, immunotherapy response patterns, immune-related adverse events (irAEs) and tumor stages are all related to the diversity of ICIs duration in previous researches. Besides, there lacks clear clinical guidance on the intermittent or continuous use of ICIs. This review aims to discuss the optimal duration of ICIs, hoping to help guide clinical work based on the literature.

Assessment and Monitoring of Response to Systemic Treatment in Advanced Hepatocellular Carcinoma: Current Insights

Advanced hepatocellular carcinoma (HCC) management has become more complex as novel therapies have been proven effective. After sorafenib, the approval of other multikinase inhibitors (MKIs) and immune checkpoints inhibitors (ICIs) has considerably increased the number of systemic therapies available. Therefore, careful assessment and monitoring of response to systemic treatment are essential to identify surrogate endpoints of overall survival (OS) in clinical trials and reliable tools to gauge treatment benefit in clinical practice. Progression-free survival (PFS) and objective response rate (ORR) are early informative parameters of efficacy that are not influenced by further lines of therapy. However, none of them has shown sufficient surrogacy to be recommended in place of OS in phase 3 trials. With such a wealth of therapeutic options, the prime intent of tumor assessments is no longer limited to identifying progressive disease to spare ineffective treatments to non-responders. Indeed, the early detection of responders could also help tailor treatment sequencing. Tumor assessment relies on the Response Evaluation Criteria for Solid Tumors (RECIST), which are easy to interpret – being based on dimensional principles – but could misread the activity of targeted agents. The HCC-specific modified RECIST (mRECIST), considering both the MKI-induced biological modifications and some of the cirrhosis-induced liver changes, better capture tumor response. Yet, mRECIST could not be considered a standard in advanced HCC. Further prognosticators including progression patterns, baseline and on-treatment liver function deterioration, and baseline alpha-fetoprotein (AFP) levels and AFP response have been extensively evaluated for MKIs. However, limited information is available for patients receiving ICIs and regarding their predictive role. Finally, there is increasing interest in incorporating novel imaging techniques which go beyond sizes and novel serum biomarkers in the advanced HCC framework. Hopefully, multiparametric models grouping dimensional and functional radiological parameters with biochemical markers will most precisely reflect treatment response.

Occurrence of hyperprogressive disease following administration of immune checkpoint inhibitors in lung squamous cell carcinoma: A case report

Immunotherapy through blocking programmed cell death 1, programmed death-ligand 1 and cytotoxic T lymphocyte antigen 4 is developing rapidly and has gained increasing attention as a treatment for malignant tumors. However, some patients experience varying degrees of immune-related side effects after undergoing immunotherapy, with hyperprogressive disease (HPD) occurring in severe cases which increases the risk of mortality. The present study discussed the risk factors for HPD following immunotherapy in a case of lung squamous cell carcinoma, after treatment with a combination of anti-angiogenic drugs and biological cytotoxic drugs, the mass was found to have become smaller than before, along with follow-up treatment options, to provide a reference for clinical treatment decisions.