real world evidence and the evolving cancer center oct 2018 rwe... · 2018. 11. 6. · real world...

Real World Evidence and the Evolving Cancer Center

Jack London, PhDResearch Professor Emeritus of Cancer Biology

Thomas Jefferson UniversityPhiladelphia, Pennsylvania USA

2

Copyright © 2017 Thomas Jefferson University. All Rights Reserved. Confidential.

REAL WORLD EVIDENCE (RWE)

Real world evidence (RWE) in medicine means evidence

obtained from real world data (RWD), which are

observational data obtained outside the context of

randomized controlled trials (RCTs) and generated during

routine clinical practice.Definition from Wikipedia

3


CANCER CENTER DATA

• Basic science results

• Clinical research trial results

• Data generated from patient clinical practice

RWDanalysis

RWE

4


RWD à RWE

Two considerations affect the value of RWE:

1. The quality of the RWD

2. The accuracy of the analysis that creates RWE from RWD

5


REAL WORLD DATA

RWD is generated by extracting data which is stored in electronic health records (EHR), billing activities databases, registries, patient-generated data, and now perhaps, mobile devices.

These data are not generated for research, but rather for patient management and billing uses.

The use of these data for research is secondary.

6


PATIENT DATA SOURCES FOR SECONDARY USE IN RESEARCH

o Hospital Electronic Medical Record (EMR)o Departmental information systems

• Pathology (Laboratory and Anatomic Pathology)• Radiology• Radiation Oncology systems

o Registries• Cancer registries (often government mandated)• Study registries (clinical investigator-driven)• Clinical trials management systemso Biobank management systems

o Clinical text reportso pathology reportso physician noteso discharge summaries

7


HOSPITAL ELECTRONIC MEDICAL RECORD

o Typically available patient data includeso demographicso diagnoseso procedureso medicationso laboratory resultso clinical reports

o Advantageso comprehensive, continually updated, patient clinical data set

oDisadvantageso often has “dirty” datao some data locked in text reports, requiring natural language processing extractiono lack of needed granularity (particularly true of cancer diagnostic data)

8


TYPICAL EMR CANCER DIAGNOSES (ICD9 / ICD10)

Malignant neoplasm of the colon (ICD9 153.9, ICD10 C18.9)Malignant neoplasm of the breast (ICD9 174.9, ICD10 C50.9)

Malignant neoplasm of the lung (ICD9 162.9, ICD10 C34.9)

No indication of tumor histology, behavior or disease stage

such as, localized adenocarcinoma of the colon, with no evidence of distant metastasis (i.e., stage I, II, or III)

primary site – histology (behavior) – stage

Therefore EMR data not granular enough for cancer research

9


PATHOLOGY SYNOPTIC REPORTS

However, when available from the EMR, College of American Pathologists

(CAP) synoptic reports – comprehensive pathology reporting of a cancer

specimen – can provide detailed cancer diagnostic data, specific to the

particular cancer.

10


CANCER (TUMOR) REGISTRY

o Typically includes comprehensive data set for cancer patients, spanning all clinical

oncology departments

o tumor histology and behavior

o disease stage

o recurrence

o treatment

o disease-specific factors

§ ER, PR, HER2 status for breast

§ Gleason score for prostate

o Advantages

o Human curated (trained abstractors) à accurate data

o Regional data model standards exist (NAACCR in U.S.)

o Disadvantages

o Because of human curation the data entry can lag by 4 to 6 months, or even longer.

o In the U.S., only follows patients initially diagnosed at that institution thereby ignoring patients initially

seen elsewhere but being treated locally.

11


CLINICAL TEXT REPORTS

Important clinical information (e.g., cancer stage, patient response

to treatment) is often found only in text reports (e.g., pathology,

physician notes).

These data must be extracted using Natural Language

Processing.

12


ANALYSIS OF RWD à RWE

Proper analysis of RWD is required to produce useful RWE.

Just as with basic science or clinical trial research, analyses of

RWD have to eliminate confounding factors that would lead to

spurious conclusions.

13


21ST CENTURY CURES ACT – EXPANDS THE ROLE OF RWE

The 21st Century Cures Act (the “Cures Act”) requires the FDA to develop a framework and guidance for evaluating RWE

• in the context of drug regulation to support approvals of new indications for previously approved drugs,

• and to support or fulfill post-approval study requirements.

Definition from Wikipedia.

14


TO BE DISCUSSED …

RESEARCH DATA ANALYTICS AT JEFFERSON

15


JEFFERSON RESEARCH DATA ANALYTICS TIMELINE

2010 2011 2012 2013 2014 2015 2016 2017

i2b2 pilot project

Deployment of i2b2 research

data mart (RDM).

Expansion of RDM to include specimen and tumor registry ontologies and

data

Developed methodology

for the prediction of clinical trial

accrual using the RDM

Addition of i2b2 “omic” data

ontology and data

TriNetX project starts

TriNetX deployment

includes tumor

registry data.

TriNetX deployment

includes genomics

data.TriNetX

collaborative network with

UTSW

TriNetX NLP project

starts.TJU

migrates to Epic EMR.

16


SKCC’S RESEARCH DATA MART DEPLOYMENT

Today, more than 180 million observations on over 3 million patients, refreshed weekly

• EMR patient data (demographics, diagnoses, medications, labs and procedures)

• Cancer registry data (tumor histology, stage, recurrence, treatment and disease-specific factors)

• “Omic” molecular diagnostic patient data o both in-house Jefferson NGS lab and outsourced Foundation Medicine resultso Currently > 400 genes with > 15,000 mutations

• Biospecimen annotation from biobanking systemo Specimen anatomic origin, class, type, pathology and slide images

17


HYPOTHESIS GENERATIONCOHORT IDENTIFICATION

• USE CASE: A clinical researcher wants to assess the feasibility of finding sufficient non-small cell lung cancer patients expressing ROS1 mutations for a clinical trial

RESEARCH DATA ANALYTICS USE OF RWD

• USE CASE: A neuroscientist wishes to access patient data to explore possible links between PSEN2 mutations and early onset Alzheimer's disease

18


USING RWD FOR CLINICAL TRIAL DESIGN

Use TriNetX platform to determine anticipated Jefferson cohort size for a proposed clinical trial.

Consider a trial for patients with locally advanced colon cancer with mutation(s) in KRAS and/or BRAF and/or PIK3CA gene(s) [NCT01108107]

• Inclusion criteriao stage 2 or 3 colon cancero KRAS, BRAF, and/or PIK3CA mutation testing determined in a CLIA-certified lab

• Exclusion criteriao Clinically significant cardiovascular disease (including myocardial infarction, unstable angina,

symptomatic congestive heart failure)

19


QUERY BASED ON TRIAL ELIGIBILITY CRITERIA

20


COHORT RWD DEMOGRAPHICS

21


COHORT RWD MOLECULAR DIAGNOSTICS

22


COHORT RWD PREDICTED ACCRUAL

23


USE RWD/RWE FOR HYPOTHESIS GENERATION

With RWD available over the TriNetX Research Network,

compare survival of lung cancer patients treated with

OPDIVO (nivolumab) vs KEYTRUDA (pembrolizumab)

24


RWD TO RWE VIA THE TRINETX RESEARCH NETWORK

Form cohorts of lung cancer patients treated with OPDIVO (nivolumab) or KEYTRUDA (pembrolizumab)

25


ANALYSES OF THE TWO COHORTS

Patients treated with KEYTRUDA show better survival than those treated with OPDIVO

26


real world evidence and the evolving cancer center oct 2018 rwe... · 2018. 11. 6. · real world...

Documents