Alejandro A Schaffer, Ph.D.

The researchers have developed and distributed several software packages for pedigree analysis (FAST, CASPAR, PedHunter, IIC) and cancer genetics (oncotree, METREX). Users who need assistance with the software or who want to see new features added often send the researchers data files that include human data. The information is normally coded, and the researchers do not have access to the identification of the people whose information is in the files. Sometimes the content of the files gives rise to collaborations between the software developers and the providers of the files. Because concerns over the confidentiality of medical information have increased significantly over the past few years, the researchers must apply for exemptions from detailed ethics committee oversight for every data set they receive. This process is cumbersome and makes it difficult to assist software users. The amount of information required to apply for an exemption also poses a barrier to collaborations.

A full protocol will subject all data sets to ethics committee oversight without the need for individual exemption requests, enabling the researchers to assist users with software problems and to collaborate with other researchers.

From January 1, 2000, through December 15, 2001, the researchers received 71 requests for assistance, 19 of which included data files. None of the data files had any names or patient identifiers. Of these 19, in 8 cases the researchers sent back modified output files. In two of these eight cases, the researchers could see results of research interest; one of them concerned human data. In 2 of the 19 cases, the researchers sent back modified input files; in one such case, they established a collaboration with the originator of the files. In sum, most requests come under the heading of customer service, with no research contents. A few, however, do lead to research results or collaborations, for which ethics committee oversight is required.

Over the three-year time frame of this protocol, the researchers anticipate receiving data on a maximum of 10,000 individuals. They have modified their software documentation to explicitly instruct users to make sure the data files they send have no names. Should they receive files with names, they will delete the files and ask the originator to resubmit them with names encoded. Users submit data through unencrypted e-mail. The data are stored in password-protected computers at the National Institutes of Health.

We have developed software packages for pedigree analysis (FAST, CASPAR, PedHunter, IIC) and cancer genetics (oncotrees, METREX). The purpose of this protocol is to allow us to work on software problems reports that may contain human subjects data in them. The data should be coded, by which we mean that if there are any links between identifiers and names, we do not possess the links to decode the names. Occasionally our assistance leads to a more formal research collaboration. This protocol seeks to clarify the guidelines under which we can provide assistance to users of our human genetics software and to establish a formal procedure under which we can seek IRB approval for the serendipitous collaborations that arise from providing that assistance. We cannot predict the sizes of samples or the diseases studied in the data sets sent to us, so most of the medical aspects of this protocol are necessarily general. We rely on the data being coded and the collectors of the data having their own institutional approvals to protect against most risks. The scientific aspects of investigating problem reports cannot be hypothesis driven because we cannot guess what problems will arise. On the engineering side, the basic hypotheses are that: 1) our software is likely to contain some bugs or other weaknesses, which cannot be easily found except by having others use the software and 2) a good way to improve the functionality of the software is to encourage users to submit problem reports and other suggestions.

This protocol has been in effect since early 2002. The only amendments during that time were to set up three collaborations, as described in Sections 4.6 and 4.7 and 4.8. The protocol has been quite useful and no changes are proposed in procedures.

Exploratory Data Analysis for Disease Pedigrees and Cancer Genetics

National Human Genome Research Institute (NHGRI)

Neoplasms

Blood and Lymph Conditions

Immune System Diseases

All Conditions

Heart and Blood Diseases

Symptoms and General Pathology

Nutritional and Metabolic Diseases

Rare Diseases

Behaviors and Mental Disorders

Lymphoma

Lymphoma, T-Cell

Multiple Myeloma

Neoplasms, Plasma Cell

Plasmacytoma

Leukemia

Leukemia, Lymphoid

Leukemia, Myeloid

Leukemia, Myeloid, Acute

Leukemia, Lymphocytic, Chronic, B-Cell

Leukemia, Myelogenous, Chronic, BCR-ABL Positive

Amyloidosis

Hodgkin Disease

Myeloproliferative Disorders

Preleukemia

Myelodysplastic Syndromes

Lymphoma, B-Cell

Lymphoma, Non-Hodgkin

Neoplasms by Histologic Type

Lymphoproliferative Disorders

Lymphatic Diseases

Immunoproliferative Disorders

Hematologic Diseases

Hemostatic Disorders

Blood Coagulation Disorders

Vascular Diseases

Paraproteinemias

Blood Protein Disorders

Hemorrhagic Disorders

Leukemia, B-Cell

Chronic Disease

Disease Attributes

Proteostasis Deficiencies

Metabolic Diseases

Bone Marrow Diseases

Chronic Graft Versus Host Disease

Quality of Life

Lymphosarcoma

Myeloid Leukemia

Acute Myeloid Leukemia

Acute Non Lymphoblastic Leukemia

Chronic Lymphocytic Leukemia

Chronic Myeloid Leukemia

B-cell Lymphoma

Hodgkin Lymphoma

Acute Graft Versus Host Disease

Chronic Myeloproliferative Disorders

Dermatologic Agents

All Drugs and Chemicals

Coal Tar

The interventional study group will use the Device Rita, an application that allow the oncological and onco-hematological patients to receive and communicate information about the quality of life and about the treatment related adverse events, providing a support in the therapy management. The access to the app functionalities is granted when the physician habilitates the personal profile. The app can be also used from people designated from the patient as caregiver, who can view the data inserted by the patient and, if enabled, they can insert the data for the patient.

This clinical trial has no control intervention; on the other hand, the clinical outcomes of this treatment will be compared with the retrospective clinical data obtained from a historical group of comparison. The historic control used in this clinical trial is specifically selected to reflect the endpoints. According to a feasibility phase of this study, the information on the date of start and end of treatments is routinely collected in the medical records of patients, and for this reason, these data are potentially already available for the historical control group.

The RITA "Remote Intelligence for Therapeutic Adherence" application was designed, on the doctor's side, as a support for the management of the onco-hematological patient and, on the patient's side, as a first aid tool for the management of the most common problems, as well as an efficient and "non-invasive" means of communication with the doctor. The system also allows the caregiver and general practitioner to be included in the communication group.

The added value of the app consists in improving the relationship between the patient and the doctor, creating an effective communication channel, increasing the safety the patient has when facing his difficult path, reducing the number of visits to the facility and, in general, making those visits more efficient, thus creating savings both in terms of time and resources.

RITA (App)

Alessandro Flavio Ferri

It is essential to improve clinical efficiency and management of hematological and oncological patients treated on an outpatient basis. The most promising operative way to achieve this result is the development of tele-oncology platforms, that allow not only a telemedicine visit, but also the patient support in the daily management of the disease and related disorders, as well as treatments and their complications. In this perspective, the RITA communication platform should be able to support the patient, the caregiver, the physician and the general practitioner in the management of the disease and its treatments.

Summary description of the investigational device:

The RITA "Remote Intelligence for Therapeutic Adherence" application was designed, on the doctor's side, as a support for the management of the onco-hematological patient and, on the patient's side, as a first aid tool for the management of the most common problems, as well as an efficient and "non-invasive" means of communication with the doctor. The system also allows the caregiver and general practitioner to be included in the communication group.

The added value of the app consists in improving the relationship between the patient and the doctor, creating an effective communication channel, increasing the safety the patient has when facing his difficult path, reducing the number of visits to the facility and, in general, making those visits more efficient, thus creating savings both in terms of time and resources. RITA is also designed to communicate and receive information on the quality of life and side effects, thus making the medical doctor aware of the progress of treatments in his patient population.

Often occurs that the mild drug/disease related symptoms that the patient perceive during the treatment period are underestimated, leading to a more severe symptomatology that could impair the patient adherence to treatment. Thanks to the app RITA, on the patients side it will be easier to notify their daily physical condition, while on the physician side it will be easier to manage and solve the mild symptoms the patient could face during the treatment period, improving the overall adherence to the treatment.

The mobile app, which can also be used on a conventional desktop or laptop, aims to optimize the interaction between the onco-hematological patient and the referring physician. The hospital doctor will have access to the website, in order to manage all the functions through the appropriate dashboard.

Intended purpose of the investigational device in the proposed clinical investigation:

The application allows, on the patient side, to:

* record the relevant symptoms, with a simple classification, to be reported to the doctor at the next visit;
* record Quality of Life (QoL) data at pre-selected timepoints;
* inform the doctor about the necessary drug prescriptions;
* contact the doctor for advice for the same day;
* receive suggestions, through both video and text, specific to the most common problems that patients may face (the advice can be specific in relation to the type of treatment carried out). The consultation is personalized by the attending physician based on the clinical characteristics of the patient, and the personalization takes place through the selection of a series of profiles created for the different types of patients (e.g. fever in patients with mild, moderate or severe impaired immune system, etc.);
* monitor relevant clinical parameters, such as: temperature, heart rate, blood pressure, oxygen saturation, respiratory rate, glycemia;
* report information on the quality of life by filling in a specific questionnaire at defined timepoints;
* monitor the intake of specific drugs;
* manage contacts with the caregiver.

While, on the hospital doctor side, the website allows to:

* have a quick and complete overview of the problems suffered by the patient in the period since the last visit, thus making the visit faster and more productive;
* have information related to different and relevant clinical parameters measured and inserted from the patient, including temperature, heart rate, blood pressure, oxygen saturation, respiratory rate, glycemia; the collection of this information will allow the doctor to have patient's information necessary to carry out the appropriate clinical assessments on response to therapy, stability and/or relapse of the disease. For example, the temperature value can be communicated directly to the doctor to anticipate the prescription of the antibiotic;
* facilitate the home management of the most common clinical problems that the patient can face, through videos and texts, customizable by the doctor, which explain how to deal with the most common symptoms in an initial phase;
* know in advance the drug prescriptions needed by the patient, thus allowing to assign the prescription activity to the support staff;
* collect in a single "container" all daily communications of patients, which are normally dispersed in a multiplicity of channels (telephone calls, faxes, e-mails), in order to be able to manage them conveniently;
* easily communicate with the caregiver;
* monitor patients' QoL prospectively.

Description of the specific medical procedures involved in the use of the investigational device:

Possible features of the RITA app:

* possibility of reminder for drugs intake;
* possibility of creating a grading or threshold levels in case of symptoms such as fever (e.g., temperature at 37.1°C or 39°C); then a response is generated based on the grading (e.g., "go to the emergency room" or "take a drug'');
* possibility for the doctor to select the advice to send to the patient;
* possibility for the doctor to select the type of pathology and the characteristics of the patient (e.g., immunodepressed patient);
* possibility of integrating diets and ad hoc menus based on drugs administered;
* possibility of inserting tutorials (e.g., how to send blood counts values);
* possibility of uploading contents: both the doctor and the patient can send texts or multimedia contents;
* possibility of sending a warning about adherence to therapy both to the doctor and to the caregiver.

Rationale for benefit-risk ratio.

The major risk for onco-hematologic patients is the progression of their underlying disease and the consequent reduction in the quality of life, which can be accelerated by a reduced adherence to the therapy. Risks associated with participation in the clinical investigation are the same as the risks identified for the general use. No additional risk is identified, specifically related to the participation in the clinical investigation, as the patient does not receive a lowered standard of care. Moreover, no special risks are reported due to the use of applications for adherence to treatment.

Therefore, the potential risks identified in association with the treatment administered with the App RITA are justified by the anticipated benefits resulting from the implementation of the standard of care aiming at improving the patients' involvement in their own health management and intended increase of adherence to treatment.

Primary Objective

The primary objective is the evaluation of patients' compliance to treatment through the use of the app RITA, thanks to more efficient management of the patients' mild symptoms that could, if not promptly treated, lead to a more severe condition and sometimes to the treatment interruption.

Secondary Objectives

* Reduction of grade 3-4 treatment-related adverse events.
* Reduction in the number of visits to the emergency room for complications not requiring hospitalization: careful monitoring of the patient, both during follow-up visits and through the use of the RITA app, allows for better control of complications, reducing the patient's need to access the emergency room.
* Reduction in the number of visits to the emergency room for severe complications requiring hospitalization: careful monitoring of the patient, both during follow-up visits and through the use of the RITA app, allows for better control of complications, reducing the patient's need to access the emergency room.
* Reduction in the average number of days in hospital stay: through careful monitoring of the patient, both during follow-up visits and through the use of the RITA app, it is possible to reduce the occurrence of severe complications that may require the patient to be hospitalized. This objective evaluates the average number of days of hospitalization of the patient due to the onset of complications.
* Improvement in the quality of life perceived by the patient: the use of tools in order to assess the quality of life (for example: questionnaires) allows the medical doctor to check the patient's perception of health and identify any limitations in daily life activities. A constant survey allows to identify timely and more effective solutions aimed at improving the patient's quality of life.
* User Experience: the use of digital tools (for example: apps, web systems, etc..), to support the doctor-patient clinical health interactions, allows continuous monitoring of the patient both with respect to any clinical complications and with regard to a worsening of the quality of life. The indicator monitors the overall degree of patient satisfaction in relation to the use of the RITA app. In this way, it is possible to verify the real effectiveness of the app and intercept any elements of attention with respect to the features present.

Primary Endpoint The primary endpoint is the evaluation of the therapeutic adherence measured as at least the 80% of the relative dose intensity (defined as the ratio of delivered dose intensity to the prescribed referenced dose intensity, expressed as a percentage) during the study period. The effectiveness of the RITA app use will be evaluated by comparing results on therapeutic adherence with a historical group of cancer patients.

Secondary Endpoint

Secondary endpoints based on the comparisons between groups:

* Number of visits to the emergency room for complications not requiring hospitalization: analysis will be performed on the population enrolled in the trial versus an historical control, evaluating the recorded number of visits to the emergency room for minor complications not requiring hospitalization. This information will be obtained by consulting the management control of the hospital or the emergency room system.
* Number of visits to the emergency room for severe complications requiring hospitalization: analysis will be performed on the population enrolled in the trial versus an historical control, evaluating the recorded number of visits to the emergency room for severe complications requiring hospitalization. This information will be obtained by consulting the management control of the hospital or the emergency room system.
* Average number of days in hospital stay: analysis will be performed on the population enrolled in the trial versus an historical control, dividing the number of days in hospital stay for hematological patients by the number of hematological patients taken care of. This information will be obtained by consulting the management control of the hospital.
* Number of AE/minor complications not requiring assistance notified by the patient during the study period, through the app RITA and directly during the clinical visit, compared to the historical control group.
* To measure quantitatively the therapeutic adherence through the mean relative dose intensity (defined as the ratio of delivered dose intensity to the prescribed referenced dose intensity, expressed as a percentage) during the study period.

Secondary endpoints on the safety assessment of RITA APP:

* Occurrence of individual adverse events (%) reported during the follow-up period, during the user session, and during intervals between one use session and the following.
* Occurrence of device adverse events (%) during the user session.

Medical Device CLASS IIA

Determination of Sample Size With a total of 112 patients (56 patients in the interventional arm and 56 in the patient-level historical group), this investigation will have 80% power to detect a 20% improvement in treatment adherence (i.e., in the intervention group, 90% or more as compared to 70%) (Passardi et al., 2022), with a one-sided type I error rate of 0.05. We set a goal of enrolling 124 patients to account for a drop-out rate of 10% (Passardi et al., 2022), with a consequent enrollment of 62 patients per arm.

Statistical Analyses

In the primary analysis, all the patients observed until the end of the study will be included.

Patients in the historical group will be matched with patients in the prospective interventional study according to cancer diagnosis and type of anticancer treatment.

The main characteristics of the patients will be reported using descriptive analyses by tabulating frequencies and percentages (categorical variables) and mean and median values, standard deviations (SD), quartiles and extreme values (continuous variables). With reference to comparison between groups, odds ratios (OR) and 95% confidence intervals (CI) will be calculated to evaluate the effectiveness of the RITA app, using logistic regression models. The statistical significance limit will be accepted as 5%, and the results below this value (P \< .05) will be considered statistically significant. Comparisons within group (i.e., in the interventional study group) will be performed by using the paired t-test or the corresponding Wilcoxon signed-rank test, a non-parametric test for paired samples, after checking data were normally distributed (based on the Shapiro-Wilk statistic). Comparisons between groups (i.e., interventional and historical) for continuous data will be analysed using a two-sided Student's t-test, after checking data were normally distributed (based on the Shapiro-Wilk statistic) and a two-sided Wilcoxon's rank-sum test otherwise. For categorical data comparisons between groups will be performed by using the contingency table analysis with the Chi-square or Fisher's exact test, when appropriate. Explorative analyses, with descriptive purpose only, will be performed in the subgroups of potential determinants of adherence of anticancer treatments, including age, gender, educational status, stage of disease, comorbidities, poly-pharmacy and complexity of oral anticancer regimens(weekly/daily). Adverse events occurring during the study follow-up will be tabulated.

QUALITY ASSURANCE AND CONTROL

All participant data relating to the study will be recorded on eCRF. The investigator is responsible for verifying that data entries are accurate and correct by electronically signing the eCRF.

The investigator must maintain accurate documentation (source data) that supports the information entered in the eCRF.

The investigator must permit study-related monitoring, audits, IRB/IEC review, and regulatory agency inspections and provide direct access to source data documents.

Monitoring details describing strategy (eg, risk-based initiatives in operations and quality such as Risk Management and Mitigation Strategies and Analytical Risk-Based Monitoring), methods, responsibilities, and requirements, including handling of noncompliance issues and monitoring techniques (central, remote, or on-site monitoring) are provided in the monitoring plan.

The sponsor or designee is responsible for the data management of this study including quality checking of the data.

The sponsor assumes accountability for actions delegated to other individuals (eg, Contract Research Organizations).

Study monitors will perform ongoing source data verification to confirm that data entered into the eCRF by authorised site personnel are accurate, complete, and verifiable from source documents; that the safety and rights of participants are being protected; and that the study is being conducted in accordance with the currently approved protocol and any other study agreements, ICH GCP, and all applicable regulatory requirements.

Data Management System The CRFs in this trial are implemented electronically using a dedicated EDC system (ICE, Integrated Clinical Trial Environment, Advice Pharma) that fulfils the legal requirements for clinical trials. The EDC system is activated for the user only after successfully passing a formal test procedure. All data entered in the EDC are stored on a Linux server in a dedicated Oracle database.

Monitoring The study will be monitored on a regular basis by the Sponsor's adequately qualified and trained clinical Monitors throughout the study period to ensure the proper conduct of the clinical Investigation.

The purposes of study monitoring are to verify that the rights and well-being of study subjects are protected, that the reported study data are accurate, complete and verifiable against the source documents, and that the study is conducted in accordance with the current clinical investigation plan, Good Clinical Practice guideline (UNI EN ISO 14155) and applicable regulatory requirements.

Audits and Inspections Upon request by the Sponsor, on-site study audits may be conducted in order to ensure the study is in compliance with GCP, applicable regulatory requirements, and the clinical investigation plan. The auditing activities may also be conducted after study completion.

This is a prospective, interventional, confirmatory investigation, pre-market study, with a historical group of comparison

MargheRITA (Remote Intelligence for Therapeutic Adherence)

Evaluation of Performance and Safety of APP RITA in Increasing the Therapeutic Adherence of Onco-Hematological Patients - a Prospective Monocentric Pre-Market Study With a Historical Group of Comparison

Number of AE/minor complications not requiring assistance notified by the patient during the study period, through the app RITA and directly during the clinical visit, compared to the historical control group

Occurrence of individual adverse events (%) reported during the follow up period, during the use session, and during intervals between one use session and the following Occurrence of device adverse events (%) during the use session

The primary outcome is defined as the comparison between the proportion of patients with at least 20% of increase in the relative dose intensity (defined as the ratio of delivered dose intensity to the prescribed referenced dose intensity, expressed as a percentage) of anticancer treatment during the study period in the two arms (i.e., intervention and historical group). The actual delivered dose intensity will be evaluated at each follow up visit through the drug accountability performed onsite.

Incidence of grade 3-4 treatment-related adverse events

Number of visits to the emergency room for complications not requiring hospitalization Number of visits to the emergency room for severe complications requiring hospitalization

Evaluation of changes in the quality of life perceived by the patients using the validated questionnaire for data collection EQ-5D-5L

Evaluation of changes in the quality of life perceived by the cancer patients using the validated questionnaire for data collection EORTC QLQC30

User Experience in using the RITA APP, through the questions proposed by the app about the user satisfaction

Advice Pharma Group srl

Respiratory Tract (Lung and Bronchial) Diseases

Lung Neoplasms

Respiratory Tract Neoplasms

Thoracic Neoplasms

Lung Diseases

Respiratory Tract Diseases

Radiologists who have certification by the American Board of Radiology

This is an observer performance study. Radiologists will interpret chest radiographs without and then with the Riverain software, both SoftView (TM) OnGuard (TM) CADe Software with be tested

Software

Matthew T. Freedman, MD, MBA

Ben Lo, Ph.D.

This is a clinical trial using retrospective data of two different software devices developed by Riverain Medical Group: Softview and OnGuard 5.0. The two studies will be run concurrently. Riverain Medical Group's computer systems are designed to assist radiologists in their identification of lung cancer on chest radiographs. The current machine received FDA Pre-Market Approval. This is to test two new software approaches.

In 2000, data was presented to the FDA to demonstrate that a new system for computer analysis could assist radiologists in the detection of small lung cancers on chest radiographs. Radiologists using the system showed a statistically significant improvement in lung cancer detection rate when they used the system, compared to their interpretation of chest radiographs when they did not use the computer system. This study, along with other supporting data, resulted in the FDA giving Pre-Market Approval for the system.

The system has undergone several improvements in software and hardware, and it is now intended to test two different software systems to determine whether radiologists using the systems can improve their detection of lung cancer on chest radiographs.

One of these systems processes the chest radiograph to decrease the emphasis given to the shadow of the ribs and thereby enhances the ability of radiologists to detect disease in the lungs. The second system performs a series of evaluations on chest radiographs and, based on a complex system of analysis, points to locations on the chest radiograph that contain solitary pulmonary nodules having the characteristics of primary lung cancer or solitary metastases of cancer to the lungs.

This will be a test of radiologists to determine the degree of improvement, if any, that results when they interpret chest radiographs that may or may not have cancer, first interpreted without the computer and, second, with the images output by the software.

Testing of Computer Aided Detection Software for Riverain Medical Group

This reports the comparison of the detection of lung nodules that were proven to represent lung cancers. It compares the results of two versions of computer-aided detection software: OnGuard 1.0 from 2001 and OnGuard 5.1 from 2009. The results represent the responses of radiologists when they use one or the other types of software. To compare radiologists' results with the two types of software, the measurement analyzed was the difference in the areas under the localized receiver operating characteristic curve (LROC). The results from the 15 participating radiologists were averaged (mean value). The area under the LROC curve is a measure of the trade-offs between sensitivity and 1-specificity that occurs as the level of certainty of a positive finding changes. It is normally reported as a decimal without units. In this study dsign, a lower number indicates that the new method (OnGuard 5.1), if statistically significant, if better.

Standard methods for LROC methodology and statistical analysis were used. We are testing two different types of software using different cases, but the same radiologists to control for radiologist differences. LROC is Localized Receiver Operating Characteristic. LROC measures the trade-offs between sensitivity and specificity as radiologists use different levels of suspicion of disease. This analysis is for the software that decreases the visibility of the ribs and clavicles while preserving (and potentially enhancing) the visibility of the lungs and lung diseases. In this case, the level of suspicion recorded was for the radiologist's concern that a finding did or did not represent cancer. Please note that the FDA approved indications for use is to detected nodules that may represent cancer, but in our study scoring for a true finding was based on whether or not the nodule did represent cancer.

A larger number, if statistically significant, indicates that that method is better.

Sensitivity and specificity were calculated using the radiologists' responses of recommendations for follow-up with CT or biopsy. Truth was whether or not the nodule identified was found to be cancer. Sensitivity is the percentage of correct identification of a positive case (a case with cancer). Specificity is the percentage of negative cases (those without cancer) that were correctly identified as not having cancer. The mean values of 15 radiologists are used.

Riverain Technologies

Georgetown University

Associate Professor Oncology, Adjunct (Pending)

Participants

Radiologists who have certification by the American Board of Radiology

Riverain OnGuard CAD Software : This is an observer performance study. Radiologists will interpret chest radiographs without and then with the Riverain software, both SoftView (TM) OnGuard (TM) CADe Software with be tested

Radiologists

number of participants

Age, Customized

Sex: Female, Male

United States

Region of Enrollment

Power calculation was performed to determine the number of participants

No adverse events occurred. Study was subject to the following potential biases: Sample bias; Majority rule bias; Referral Bias, bias from knowledge that this is an experiment; reader order bias; learning bias; Bias from use of new technology, et al

Matthew T. Freedman

The sample size of 351 patients, in a 2:1 ratio of nodule absent to present patients was selected to provide 80% power to detect a difference in areas under the curve of 0.10 or greater. This sample size was calculated using PASS software (Hintze, 2008). Settings: • α = 0.025. • one-sided test • AUCA = 0.80 and AUCSV = 0.90.• 2:1 ratio of patients with nodules to those without • areas calculated for the entire curves • correlation 0.3\* • discrete data. • standard deviation ratios of 1\*.

Control image interpretation unaided by software of either type. This is the control for the SoftView experiment. It uses the same radiologists (to avoid a bias that might result from using different radiologists) as the OnGuard Computer-aided detection software, but different cases.

Radiologists Control for SoftView

This software suppresses the visibility of the ribs and clavicles potentially revealing non-calcified nodules make less conspicuous by the bones projected on top of the nodules

Radiologists Using Softview Software

122 subjects had cancer that potentially could be detected on their chest radiograph. Power analysis showed that sample size of 351 patients, in a 2:1 ratio of nodule absent to present patients was selected to provide 80% power to detect a difference in areas under the curve of 0.10 or greater.

Improvement in Cancer Detection as Measured by Localized Receiver Operating Characteristic) LROC Changes Under the LROC Curve.

Radiologists using OnGuard software. Two different versions were tested. OnGuard 1.0 and OnGuard 5.1. This software uses a computer algorithm to identify non-calcified lung nodules consistent with lung cancer. The value presented is the average difference in the areas under the LROC curve as demonstrated for the participating radiologists. The value for OnGuard 5.1 was subtracted from that of OnGuard 1.0, so a negative value indicates that OnGuard 5.1 had a higher value than OnGuard 1.0. The 95% confidence interval indicates that the OnGuard 5.1 was significantly improved.

Radiologists Using OnGuard Software: Difference of 1.0 and 5.1

81 of the 263 radiographs contained a non-calcified nodule that had been diagnosed as lung cancer. Power calculation showed 246 patients, in a 2:1 ratio of nodule absent to present would provide 80% power to detect a difference in areas under the curve of 0.10 or greater.

Difference in the Area Under the LROC Curve Comparing OnGuard 1.0 and OnGuard 5.1

Sensitivity

Specificity

Sensitivity and Specificity Using SoftView Software

Radiologists who have certification by the American Board of Radiology

Riverain OnGuard and SoftView Software : This is an observer performance study. Radiologists will interpret chest radiographs without and then with the Riverain software, Two types of software are tested: SoftView (TM). SoftView decreases the visibility of the ribs and clavicles on chest radiographs. OnGuard marks locations on chest radiographs meeting some of the software signs of lung nodules, a method often called Computer Aided Detection (CADe).

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Exploratory Data Analysis for Disease Pedigrees and Cancer Genetics	NCT00339508	Data Analysis Cancer Genetics		-	National Institutes of Health Clinical Center (CC)
Exploratory Data Analysis for Disease Pedigrees and Cancer Genetics	NCT00339508	Data Analysis Cancer Genetics		-	National Institutes of Health Clinical Center (CC)
MargheRITA (Remote Intelligence for Therapeutic Adherence)	NCT05260203	Multiple Myelom... Solitary Plasma... Amyloidosis Chronic Myeloid... Chronic Lymphoc... T Cell Non-Hodg... Lymphocytic Lym... Hodgkin Lymphom... B-cell Non Hodg... Acute Myeloid L... Myelodysplasia Chronic Myelopr... Treatment Adher... Treatment Adher...	RITA (App)	18 Years -	Advice Pharma Group srl
Testing of Computer Aided Detection Software for Riverain Medical Group	NCT00906789	Lung Cancer	Software	-	Georgetown University
Testing of Computer Aided Detection Software for Riverain Medical Group	NCT00906789	Lung Cancer	Software	-	Georgetown University

Spots Global Cancer Trial Database for software

Every month we try and update this database with for software cancer trials from around the world to help patients and their families find trials that might be right for them.
We offer this 100% free of charge and do not endorse any of the trials listed here, we hope it helps you or a loved one.

Spots Global Cancer Trial Database for software

Every month we try and update this database with for software cancer trials from around the world to help patients and their families find trials that might be right for them. We offer this 100% free of charge and do not endorse any of the trials listed here, we hope it helps you or a loved one.

Every month we try and update this database with for software cancer trials from around the world to help patients and their families find trials that might be right for them.
We offer this 100% free of charge and do not endorse any of the trials listed here, we hope it helps you or a loved one.