Diseases and Abnormalities at or Before Birth

All Conditions

Behaviors and Mental Disorders

Congenital Abnormalities

Quality of Life

At baseline, clinical research staff will:

* verify the possibility of an internet connection at the patient's home
* help the patient to fill in the 1st questionnaire (baseline questionnaire - frailty)

Every two weeks for 3 months:

* patients complete questionnaires via app (toxicity; quality of life, medication adherence)
* responses are verified by clinical research staff
* In case of severe symptoms, the clinician contacts the patient and arranges for management.

At the end of the study :

- patients answer a satisfaction questionnaire

Patient Self-Reporting of Symptoms

LAMBERT AURELIEN, MD

During treatment, cancer patients may experience side effects related to their disease but also to the different treatments they receive.

Currently, adverse effects and toxicities are well codified in the oncology community, notably via the NCI CTCAE criteria.

Unlike objective data such as a blood sample or a CTscan, a major bias in patient assessment is the subjective assessment of the physician or its team at a given time, which may not reflect the overall situation (for better or worse). Several studies had already highlighted the discrepancies between medical and patient data collection.

Self-assessment of symptoms is one way to overcome this bias. Moreover, there are now a large number of solutions that allow to perform these self-assessments at home.

Thanks to these tools, there are now two situations, the scheduled evaluation (before a chemotherapy treatment, or after a surgical procedure for instance) and the unscheduled situations, where it is the patient himself who can trigger an evaluation form.

These new evaluation methods also allow to take a quality of life approach. Patient-reported outcomes (PROs) is now a valid evidence-based assay to detect patient's symptoms and therefore provide helpful clinical information to healthcare providers.

The goal of this study is to go one step further than the previous PROs studies and evaluate the ability to train a machine learning algorithm to detect at-risk situations and lay the foundation for a viable solution for future prospective and randomized trials.

Artificial Intelligence to Search for Abnormalities in Ambulatory Cancer Patients

The number of unscheduled medical consultations or re-hospitalisations will be assessed based on abnormalities identified through the patient's self-report of symptoms.

Patient satisfaction will be assessed according to the Patient Assessment Chronic Illness Care Questionnaire (1= almost never : 5 = almost always)

The occurrence of toxicities will be evaluated according to the NCI-CTCAE v5.0 classification

The total dose of treatments given will be calculated from the total dose of chemotherapy received per course and the collection of dose adjustments.

Adherence to oral treatments will be assessed by the Morisky questionnaire

Handling of the digital tool will be assessed by the System Usability Scale ( 0 =Strongly disagree; 10=Strongly agree)

Anticipation of injectable chemotherapy preparations will be evaluated based on the number of treatments ordered and actually administered, without the need to call the patient.

The occurrence of sarcopenia will be measured by the body mass/fat mass ratio using the CT scan performed for tumor evaluation

Institut de Cancérologie de Lorraine

Neoplasms

Skin and Connective Tissue Diseases

Digestive System Diseases

Breast Neoplasms

Colorectal Neoplasms

Intestinal Neoplasms

Gastrointestinal Neoplasms

Digestive System Neoplasms

Gastrointestinal Diseases

Colonic Diseases

Intestinal Diseases

Rectal Diseases

Herbal and Botanical

All Drugs and Chemicals

Cola

Subjects with colon or breast carcinoma will respond to weekly electronic patient-reported outcome (ePRO) questionnaires.

Subjects will respond to Electronic patient-reported outcome (ePRO) every week for 8 weeks.

Weekly Survey

Erin Laurie-Zehr, MA

Katie Reeder-Hayes, MD

Katie Reeder-Hayes

This study assesses the feasibility and acceptability of a brief electronic patient-reported outcome (ePRO) tool that allows patients to self-identify impending delays. The risk of treatment delays according to tumor type and race will be measured by both ePRO and electronic health record (EHR) tools. Data from this study and the association of social determinants of health could be useful to flag patients at risk of delay and due timely intervention for modifiable treatment barriers. The prediction of the risk of treatment delay will be helpful to design another study using electronic tracking systems to prevent cancer treatment delays. The long-term goal of this research is to alert care teams when patients may be at risk of treatment days and to help patients get treatment faster. It was planned to enroll a total of 240 subjects with newly diagnosed cancer. Sixty colorectal and 180 breast cancer patients will be included.

The Care Tracker Study: Using Patient-Reported Data to Address Racial Disparity in Cancer Treatment

The Care Tracker Study: Using Patient-Reported Data to Address Racial Disparities in Cancer Treatment Delay

Feasibility of Electronic patient-reported outcome (ePRO) will be assessed as the proportion of subjects who responded to at least 4 out of offered 8 weekly ePRO.

Electronic patient-reported outcome (ePRO) confirming treatment initiation will be measured as the proportion of subjects who responded to at least one of the offered weekly ePRO) surveys.

Treatment Delay will be measured as the proportion of subjects not receiving ePRO-reported treatment.

If a subject reports on any weekly survey that they have started a treatment for their cancer, selected from a defined list of cancer treatment types this will be considered receiving treatment. Diagnostic procedures, imaging tests, and other medical interventions will not be considered receiving treatment. Patients who respond to surveys indicating no treatment throughout the 56 days of study participation, those who report treatment at a timepoint \>56 days from pathologic-confirmed diagnosis, as well as those who do not respond to surveys, will be considered as not receiving treatment for this endpoint.

Time to ePRO-reported treatment will be assessed as the time from the first documented pathologic confirmation of malignancy (or imaging evidence if biopsy was not obtained) to the first day of the week in which the patient reports receiving treatment as per.

Surveys are completed weekly; thus, the date of treatment is assumed to be the first day of the week in which the patient completes the survey and reports treatment initiation. For instance, if a patient completes a survey on day 32, reporting that they received treatment in the previous week, their date of treatment initiation is assumed to be day 26.

The proportion of treatment delay will be defined as days between the first documented pathologic confirmation of malignancy to the first therapeutic intervention longer than 56 days divided by the total number of consented patients. Dates will be identified by the study team using a structured abstraction form from either outside medical records captured in the EPIC or UNC EPIC records.

Time to treatment in days will be assessed as days between the first documented pathologic confirmation of malignancy to the first therapeutic intervention. Dates will be identified by the study team, using a structured abstraction form from either outside medical records captured in the EPIC or other medical records.

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization	Link
Artificial Intelligence to Search for Abnormalities in Ambulatory Cancer Patients	NCT05412420	Solid Tumor	Patient Self-Re...	18 Years -	Institut de Cancérologie de Lorraine
The Care Tracker Study: Using Patient-Reported Data to Address Racial Disparity in Cancer Treatment	NCT06096623	Cancer Breast Cancer Colorectal Canc...	Weekly Survey	18 Years -	UNC Lineberger Comprehensive Cancer Center

Spots Global Cancer Trial Database for electronic survey