Trial Title:
Machine Learning Model to Predict HOLS and Mortality After Discharge in Hospitalized Oncologic Patients
NCT ID:
NCT05534178
Condition:
Solid Tumor
Nutrition Related Neoplasm/Cancer
Comorbidities and Coexisting Conditions
Mental Status Change
Artificial Intelligence
Oncology
Tumor
Quality of Life
Conditions: Official terms:
Neoplasms
Conditions: Keywords:
Hospitalization
Oncologic patients
Study type:
Observational [Patient Registry]
Overall status:
Unknown status
Study design:
Time perspective:
Prospective
Summary:
The study aims to understand which are the most relevant parameters at admission which
may allow to predict the hospital length of stay (HOLS) and mortality after discharge of
oncologic hospitalized patients.
This is the first multicentric prospective observational study that tries to understand
the complexity of the hospitalized oncologic patients. A comprehensive analysis will be
performed with the help of the nutrition, nursery, internal medicine and oncology teams.
Detailed description:
BACKGROUND:
Cancer is the second leading cause of death worldwide and is responsible for about 18.1
million new cases and 9.6 million deaths in 2018 alone according to the International
Agency for Research on Cancer. Cancer is anticipated to rank as the leading cause of
death and the most important barrier to increasing life expectancy in every country of
the world in the mid-21st century1. The economic impact of cancer is significant. The
annual economic cost of cancer in 2010 was estimated at approximately US$ 1.16 trillion.
The reasons are complex but both cancer incidence and mortality are increasing worldwide
due to aging and increasing risk factors for cancer, several of which are associated with
socioeconomic development. Cancer will probably soon reach the top leading cause of death
due to the rapid population growth and the declines in mortality rates by stroke or
coronary heart disease in many developed countries.
Cancer patients often require inpatient care due to treatment toxicities, complications
from cancer such as thrombosis, illness not related to the disease itself or terminally
ill patients. Among these individuals, their treatment should balance prolongation of
survival and maximization of the quality of remaining life. However, hospitalization is a
stressful event for individuals with advanced cancer and their caregivers.
Hospitalization often antagonizes these goals, contributing to the high cost of cancer
care, worsens survival, and is increasingly recognized as poor-quality cancer care. Thus,
interventions that reduce unnecessary hospitalizations, or shorten them, will likely
improve quality of life and reduce costs.
Some studies relate malnutrition, which presents a marked sarcopenia and loss of lean
mass, with prolonged hospitalization, reduced response to treatment, a worse overall
survival and impaired quality of life. A study published in 2007 found that lung cancer
patients had a longer hospitalization and required inpatient hospital treatment more
frequently than any other type of tumor. Moreover, in the surgical setting there have
been studies linking preoperative opioid usage and increased opioid doses with increased
length of stay. Based on this data, there have been protocols developed like the ERAS
(Enhanced recovery after surgery) applied first to colorectal cancer and now being tested
in other settings like head and neck and gynecologic tumors, showing that it is possible
to reduce opioid use with good pain control and a statistically significant shorter
average length of stay.
Prognostic factors for oncologic patients after surgery or curative systemic treatment
have been described, but there is no solid evidence on which combination of parameters
predict mortality after hospitalization of metastatic cancer patients under active
treatment. A potential solution to improve this scenario might be nutritional support to
malnourished cancer patients that also has proven to be effective in shorten hospital
stay and improve survival, or community based palliative care interventions that are
proven to improve quality of life and reduce costs of terminally ill patients. Thus, a
prognostic tool would be useful to help physicians adjust medical interventions for
hospitalized cancer patients.
To the best of our knowledge, this is the first study that examines independent clinical,
psychological, nutritional status, and laboratory characteristics of oncologic patients
in order to grasp a comprehensive picture of what factors play a role in the length of
stay, mortality, and quality of life.
MEANING The investigators pretend with this work to fill a gap of knowledge in the
oncology field through a prospective study. The investigators would like to measure the
effect of hospitalization on oncologic patients after discharge and how clinical and
laboratory parameters at admission may be able to predict HOLS and 30-day mortality after
discharge. The investigators would also like to validate the different scales already
published to assess nutritional status, psychological status, quality of life or
prediction of rehospitalization for oncologic patients in all-in-one study.
This study will hopefully be able to develop a predictive tool at admission to help
physicians adjust medical interventions and detect possible actions that will need to be
implemented during hospitalization in order to improve the overall survival and quality
of life of our patients.
Criteria for eligibility:
Study pop:
All oncologic patients that require hospitalization.
Sampling method:
Non-Probability Sample
Criteria:
Inclusion Criteria:
- ≥18 years-old.
- Histological cancer confirmation.
- Hospitalization in oncology ward.
Exclusion Criteria:
- <18 years-old.
- Not histological malignancy confirmed.
- Less than 24 hours in the hospital.
Gender:
All
Minimum age:
18 Years
Maximum age:
N/A
Locations:
Facility:
Name:
Hospital del Mar
Address:
City:
Barcelona
Zip:
08003
Country:
Spain
Status:
Recruiting
Contact:
Last name:
Jordi Recuero, MD
Email:
jordi.recuero.borau@gmail.com
Investigator:
Last name:
Jordi Recuero, MD
Email:
Sub-Investigator
Investigator:
Last name:
Sonia Servitja, MD
Email:
Principal Investigator
Facility:
Name:
Hospital Universitari Vall d'Hebron
Address:
City:
Barcelona
Zip:
08035
Country:
Spain
Status:
Recruiting
Contact:
Last name:
Oriol Mirallas, MD
Phone:
934 89 30 00
Email:
omirallas@vhebron.net
Investigator:
Last name:
Clara Salva, MD
Email:
Sub-Investigator
Investigator:
Last name:
Oriol Mirallas, MD
Email:
Principal Investigator
Investigator:
Last name:
Daniel López-Valbuena, MD
Email:
Sub-Investigator
Investigator:
Last name:
Diego Gómez-Puerto, MD
Email:
Sub-Investigator
Investigator:
Last name:
Kreina Sharela Vega, MD
Email:
Sub-Investigator
Investigator:
Last name:
Jose Maria Ucha, MD
Email:
Sub-Investigator
Investigator:
Last name:
Sergio Bueno, MD
Email:
Sub-Investigator
Facility:
Name:
Hospital de la Santa Creu i Sant Pau
Address:
City:
Barcelona
Zip:
08041
Country:
Spain
Status:
Recruiting
Contact:
Last name:
Berta Martin Cullell, MD
Phone:
+34935565638
Email:
bmartinc@santpau.cat
Contact backup:
Last name:
David Paez, MD
Email:
dpaez@santpau.cat
Investigator:
Last name:
Berta Martin-Cullell
Email:
Principal Investigator
Investigator:
Last name:
Judit Sanz
Email:
Sub-Investigator
Start date:
February 15, 2020
Completion date:
March 15, 2024
Lead sponsor:
Agency:
Vall d'Hebron Institute of Oncology
Agency class:
Other
Collaborator:
Agency:
Fundació Institut de Recerca de l'Hospital de la Santa Creu i Sant Pau
Agency class:
Other
Collaborator:
Agency:
Hospital del Mar
Agency class:
Other
Source:
Vall d'Hebron Institute of Oncology
Record processing date:
ClinicalTrials.gov processed this data on November 12, 2024
Source: ClinicalTrials.gov page:
https://clinicaltrials.gov/ct2/show/NCT05534178
