P2.16-23 Rates of Support and Care Offerings Among Patients in an Advocacy Organization Sponsored Lung Cancer Patient Registry

Abstract

Background: When talking about a probabilistic neural network a new concept on survival is introduced. Using advanced statistics, different characteristics amongst patients such as oncogenic driver mutation, smoking status or age can be correlated to calculate the probability of survival in each individual and even for each attending institution. Method: We built a neural network model that allowed us to estimate the probability of mortality according to the variables: Oncogenic addiction (EGFR mutation and ALK rearrangements), expression of PDL-1, age, gender and exposure to cigarette. These variables were obtained from a cohort of patients with advanced non-small cell lung carcinoma who received treatment in our institution during the last 3 years. Result: Thirty-one patients were included in the model. The accuracy of the neural network was 78.57% for the patients that died and 82.35% for the patients still alive. It was possible to calculate the probability of overall survival and the probability of dying in relation to age, exposure to cigarette, gender, oncogenic addiction and PDL-1 expression for each person and for the whole cohort. Individual results and global results (Kaplan Meier) are shown in table and graphic. Conclusion: The minimum data sample required to produce the model was used (n¼31), thus it would not be correct to talk about global conclusions. However, this is a representative model of a proof of concept related to predictive analytics related to probability of survival in a real world setting using a neural network that worked on an individual basis according to clinical and biological characteristics. Results for the entire cohort are also available. Using a greater amount of data will increase the accuracy of the neural network to predict survival and other outcomes in an individual and even institutional basis that will improve data analytics in real oncologic settings.

Leveraging patient‐reported outcomes (PROs) in patients with pancreatic cancer: The Pancreatic Cancer Action Network (PanCAN) online patient registry experience

“…[20][21][22] Analyses of clinical information allow research insights, such as identifying ''exceptional responders'', 21,22 exploring patterns of care delivery and outcomes, 19,20,24 and evaluating specific needs, such as those related to patient education resources. 23 These registries The answers to questions posed in the Basic and Health assessment surveys trigger the appearance of additional surveys on the dashboard if they are relevant for the participant (white boxes). Additional optional surveys appear on the dashboard at appropriate times to avoid overwhelming the participant (bottom box) are often supported by foundations and professional organizations, rely heavily on direct-to-patient outreach through social media, and promote a patient-partnered approach to research.…”

“… 18 Other cancer site‐specific registries include those for relatively less common cancers, such as pediatric adrenocortical carcinoma, gastrointestinal stromal tumors, and angiosarcoma, 19 , 20 , 21 and for more common cancers, such as lung cancer and metastatic breast cancer. 22 , 23 Much like the broader PanCAN mission to promote genetic testing of patients through the KYT program, some cancer registries, such as the International Pediatric Adrenocortical Tumor Registry, the Angiosarcoma Project, and the Metastatic Breast Cancer Project, allow patients to share biospecimens (germline and somatic) for genetic testing, along with clinical information. 20 , 21 , 22 Analyses of clinical information allow research insights, such as identifying ‘’exceptional responders’’, 21 , 22 exploring patterns of care delivery and outcomes, 19 , 20 , 24 and evaluating specific needs, such as those related to patient education resources.…”

“… 20 , 21 , 22 Analyses of clinical information allow research insights, such as identifying ‘’exceptional responders’’, 21 , 22 exploring patterns of care delivery and outcomes, 19 , 20 , 24 and evaluating specific needs, such as those related to patient education resources. 23 These registries are often supported by foundations and professional organizations, rely heavily on direct‐to‐patient outreach through social media, and promote a patient‐partnered approach to research. Thus, along with prior initiatives, we envision that this Registry effort can guide future actions, although every disease process and initiative will have a unique mission and needs.…”

Leveraging patient-reported outcomes (PROs) in patients with pancreatic cancer: The Pancreatic Cancer Action Network (PanCAN) online patient registry experience.

“…18 Other cancer sitespecific registries include those for relatively less common cancers, such as pediatric adrenocortical carcinoma, gastrointestinal stromal tumors, and angiosarcoma, [19][20][21] and for more common cancers, such as lung cancer and metastatic breast cancer. 22,23 Much like the broader PanCAN mission to promote genetic testing of patients through the KYT program, some cancer registries, such as the International Pediatric Adrenocortical Tumor Registry, the Angiosarcoma Project, and the Metastatic Breast Cancer Project, allow patients to share biospecimens (germline and somatic) for genetic testing, along with clinical information. [20][21][22] Analyses of clinical information allow research insights, such as identifying ''exceptional responders'', 21,22 exploring patterns of care delivery and outcomes, 19,20,24 and evaluating specific needs, such as those related to patient education resources.…”