Communicating with cancer patients in the era of personalized medicine September 9 th, 2017 Gerald Prager, M.D. Comprehensive Cancer Center Vienna Medical University of Vienna, Austria
Gerald Prager, M.D. Head of the Intestinal Cancer Group Head of the Precision Medicine Program Comprehensive Cancer Center Vienna Medical University of Vienna, Austria
Test Question: Do you participate in this test vote? A. YES B. NO
Stratified Therapy: The right therapy for the right patient at the right time Stratified Therapy: Clinical criteria (tumor/patients factors) Individual treatment aims Individual Medicine Gene signatures and molecular subtyping can predict treatment response and avoid unnecessary toxicity. patient demands (e.g. benefit vs toxicity) Biomarkers: RAS wt or mt, Her-2, etc. Treatment A Treatment B Expression profiling Treatment C
Overview 1. What can WE expect from personalized medicine in 2017? 2. What do PATIENTS expect from personalized medicine? 3. How we can TRANSPORT INFORMATION about tumor biology, about mode of action of targeted medicine and about treatment aims to our patients 4. WHO SHOULD DECIDE about a personalized (experimental) treatment concept.
Poll Question: What is a prerequisite for an individulized treatment approach? A. informed consent B. biomarker C. money D. time E. all of the above
Background: Biomarkers
Definition: Biomarkers Biomarkers are characteristics that are objectively measured and evaluated as indicators of normal biological processes, pathogenic processes, or pharmacologic responses to therapeutic intervention.
Nature MedicineVolume: 17,Pages:297 303Year published:(2011)
Patient selection through biomarkers Predicted poor or no response to drug Increased likelihood of toxicity of drug Predicted good response to drug
Biomarkers in clinical practice The Biomarkers Consortium Biomarkers can be used in clinical practice to identify risk for or diagnose a disease stratify patients assess disease severity or progression predict prognosis guide treatment
Marker Type 1: passenger mutations Not prognostic Not predictive
Marker Type 2: predictive marker Not prognostic Predictive
Marker Type 3: prognostic marker Prognostic Non-predictive Example: Tumor stage and chemotherapy
Marker Type 4: predictive and prognostic Prognostic Predictive Worse prognosis correlates with treatment efficacy Example: HER2 and trastuzumab
Marker Type 5: predictive and prognostic Prognostic Predictive Better prognosis correlates with treatment efficacy Example: ER and tamoxifen
Which biological material? Depending on the marker Most common: DNA, RNA, protein Common biological material Serum/plasma Tumor tissue Fresh frozen Paraffin-embedded Sputum
Which technology/technique? Immunohistochemistry ELISA RT-Q PCR-based technology RNA expression Gene copy number DNA Mutations SNPs Hypermethylation Sequencing Methylation-specific PCR Microarrays
Cancer Treatment: The Challenge The Outcome: A group of patients all are suffering from lung cancer Therapy works in a few patients One type of therapy is given to all patients Therapy causes toxic side effects in many patients Side Effects Tumor Shrinks
Treatment A Treatment B Cancer Treatment: Individualized Therapy A group of patients all have lung cancer The tumor of each patient is tested using proteomics and molecular profiling technology Therapy is tailored to the molecular circuitry of the individual patient s The tumor Outcome: The correct therapy is given to the correct patient Higher treatment success rate Patients are spared unnecessary toxicity Tumor Shrinks Tumor Shrinks
Numerous Actionable Targets, example mcrc ALK fus, 2% KIT, 0.30% FLT3, 0.30% JAK2, 0.30% IDH1, 0.30% MLK4, 2% AKT, 0.30% STK, 2% PDGFRB, 0.50% NTRKs, 1% BRCA, 2% EGFR, 2% IGF2ampl, 4% Her4, 1% FGFRs, 2% MET, 1% Her2, 2% HER3, CDK8, 1% 4% PTEN, 8% RAS, 45% GNAS, 0.30% PIK3CA, 5% BRAF, 8% Others, 10%
Doctors expectations
Pilot Trial: Individualized Treatment according to the molecular profile of the individual patient after failure of standard treatment. Von Hoff D D et al. JCO 2010;28:4877-4883 n=66 n=2 (A) Illustration of the primary end point, progression-free survival (PFS) ratio, for the study. (B) Mechanics of the study. TTP, time to progression; MP, molecular profiling. IHC, immunohistochemistry; FISH, fluorescent in situ hybridization. 2010 by American Society of Clinical Oncology
Waterfall plot in all patients for maximum percent change of summed diameters of target lesions with respect to baseline diameters. Von Hoff D D et al. JCO 2010;28:4877-4883 2010 by American Society of Clinical Oncology
Poll Question: What is the % of patients treated according to their molecular profile in prospective clinical trials? A. < 10 % B. 10-25 % C. 26-50 % D. 51-75 % E. > 75 %
Challenges of Precision Medicine Approaches SAFIR01 Prospective multicenter trial, France Breast Cancer 423 pts 406 pts included Material for analysis 13% 67-70% 195pts (45%) 55pts (13%) 43pts (9%) Feasible for sequencing Mutation identified Started targeted treatment assessable 4 pts had a objective response 9 pts. had a stablization of disease = 13 pts. (30%) Disease controll rate André F., et al.; Lancet Oncol. 2014 Mar;15(3):267-74
All Solid Tumors MOSCATO-01 Prospective monocenter trial, France (Gustave Roussy) All solid tumors 20% 928 pts 406 792 pts 621 pts 67-70% (78%) 358 195pts (45%) 155 55pts (13%) (20%) included Material for analysis Molecular Profile Mutation identified Started targeted treatment 33% had an improved outcome 30% had a longer PFS compared to the PFS before 62% disease control rate Annals of Oncology, Volume 26, Issue suppl_2, 1 March 2015, Pages ii4
Patient (n=42) EXACT trial: Progression-Free Survival 41 39 37 35 33 31 29 27 25 23 21 19 17 15 13 11 9 7 5 3 1 0 100 200 300 400 500 600 700 median PFS=102d days Prager-GW et al; submitted
patient s involvement in treatment decisions patients expectation
Tumor biology related factors Localisation o left versus right o liver- or lung-only metastases versus multiple sites Extent of disease o Potentially convertible o bulky, non-convertible Growth dynamics o aggressive o indolent Tumor-related symptoms o asymptomatic o symptomatic Patient-related factors biological age co-morbidity physical capacity to tolerate more intensive treatment psychological willingness to undergo more intensive treatment Drug efficacy / toxicity profile of chemotherapy potential to prolong PFS or OS toxicity profile drug sensitivity- / biomarkers Drug availability and cost availability (depending on region) reimbursement cost/economic reasons factors influencing choice of treatment
Metastatic disease: scenarios and treatment aims Scenario non-resectable locally advanced Disseminated disease: impending clinical threat and/ or symptoms Dissmeninated disease: no clinical threat and asymptomatic therapeutic aims Tumor shrinkage Improve survival Quality of life Treatment decision according to clinical aims
Treatment decision on an individual patient: example TKIs Patient Selection Criteria alternative options (on-label or off-label) Patient needs to be in an adequate PS (ECOG 0-2) Needs to be able to understand pill intake schedule Needs to be compliant Patient Education Focus on timing pill intake (on) and treatment breaks (off) Emphasize CBC or organ function testing Discuss side effect management nausea, abdominal pain, fatique Discuss proactive prevention of side effects Patient Monitoring Have contact with patient on on a regular base within the first 1-2 cycles Consider dose delay Monitor blood cell count or organ function / cycle Dose reduce before serious side effects emerge 32 Gerald Prager, M.D. Ljubljana, Slovenia March 15 th, 2017
Poll Question: Who should decide the treatment? A. patient B. doctor C. both D. study nurse E. health plan
Who should decide? older, those with less education, lower income, less resilient younger, high education, higher income, resilient Oncologist. 2014 Apr; 19(4): 433 436; Psycho-Oncology 2016 (10)
Summary Patient s involvement in treatment decision Patient selection for treatment (social, co-morbidities, compliance, ) Treatment aim Treatment line Patients preference (quantity vs. quality) Patients expectation, whishes Informed consent Shared decision making
Communication
1. Just briefly highlight the mode of action: chemo vs. biological 2. Focus on the treatment aim: stabilization, shrinkage, etc. 3. Focus on treatment schedule 4. Highlight the most important side-effects and how to (pro-)actively act on them 5. give contact details for follow-up or emergency The multityrosinekinase inhibitor targets BRAF, PDGFR, VEGFR-2, FGFR, bla, bla, bla Is he going to cure or kill me?
Summary Personalized treatment might be an effective treatment option for selected patients Not every patients has a benefit from such an approach Tremendous efforts were taken to define predictive biomarkers to characterize the subgroup of patients who might benefit for precision medicine. Many studies are ongoing While prognostic markers are often defined, prediction of treatment response is so far limited to some markers for certain treatment approaches in defined diseases (e.g. BRAF V600E). Patients expectations should clearly be addressed before a precision medicine approach is offered.
Thank you for your attention!