UVEAL MELANOMA: EPIDEMIOLOGY, ETIOLOGY, CLUSTER DETECTION, AND CASE FOR A RARE TUMOR REGISTRY

Marlana Orloff, MDAssistant ProfessorDepartment of Medical OncologyThomas Jefferson University Hospital

FINANCIAL DISCLOSURE Nothing to disclose

WHAT WE KNOW Rare cancer Most common primary intraocular tumor Incidence: 7 per million per year in US Approximately 2000 new cases diagnosed

annually in the US Median age 60yrs Overall Survival varied *Above based on what is reported to

SEER/CINA national databases / single center experiences

WHAT WE KNOW More common in lighter eyed people White:Non-White 175:1 M:F slight M>F Very rarely hereditary

BAP1 Syndrome BRCA2

WHAT WE DON’T KNOW What causes it?

PREVIOUS EPIDEMIOLOGIC STUDIES Singh et al 2012

Queried SEER database 1973-2008 4,070 cases

Only included cases of the “uveal tract” Excluded cases of site unspecified

Concern if 2000 cases to be diagnosed annually in the US then this is a gross underestimation of number of cases

ATTEMPT TO SEE TRENDS IN DIAGNOSIS AND CAUSE

Eye cancer incidence 2006-2010 taken from North American Association of Central Cancer Registries (NAACCR)

Assumed ocular melanoma to be majority of cases Data from Washington, DC was censored due to

small numbers (N=9) Lowest rates in South Dakota

0.29/100,000 (13 cases) Highest rates in Oregon

1.23/100,000 (242 cases)

UNUSUAL CLUSTERING

PREVIOUS DESCRIBED CLUSTER: 1982

Patient Gender

Age at Diagnosi

s

Date of Diagnosi

s

Residence at

Diagnosis

Institution that made

Official Diagnosis

Residence at Time of Suspected Clustering

Dates at least part time at Residence

During Time of Suspected

Clustering

1 F 22 4/13/2009 Aiken, SC

Wills EyePhiladelphia,

PAHuntersville

, NC 2002-2005

2 F 24 12/2008 Charleston, SC

Duke Eye Center

Durham, NCHuntersville

, NC 1994-2007

3 F 20 7/8/2013 Charlotte, NC

Wills EyePhiladelphia,

PAHuntersville

, NC 2006-2011

4 F 31 2/7/11 Charlotte, NC

Wills Eye Philadelphia,

PAHuntersville

, NC2005/2007-

2013

5 F 30 2/2014 Concord, NC Duke Eye

CenterDurham, NC 

Huntersville, NC 2005-2007

Patient Gender

Age at Diagnosi

s

Date of Diagnosi

s

Residence at

Diagnosis

Institution that made

Official Diagnosi

s

Residence at

Time of Suspect

ed Clusterin

g

Dates at least part time at Residence

During Time of Suspected

Clustering

1 F 31 10/1/2001

Birmingham, AL

Wills Eye Philadelphia, PA

Auburn, AL

(Auburn University

)

1989-1993

2 F 31 1/2000 Birmingham, AL

Eye Foundatio

nBirmingham, AL

Auburn, AL

(Auburn University

)

1989-1993

3 F 42 7/2012 Memphis, TN

Hamilton Eye

InstituteMemphis,

TN

Auburn, AL

(Auburn University

)

1989-1993

OUR INVESTIGATION Contact individual state registries to look at

cases reported Calculation of STANDARD INCIDENCE RATIO

(SIR)

>1 suggests observed > expected NC (Mecklenberg): 0.7 (0.5-0.9) AL (Statewide only Females): 1.15 (0.98-1.32)

Lower limit =)Expected#(x2

2

/2 observed),x(#2 Upper Limit =)Expected#(x2

2

/2-1 1),observedx(#2

Where

2

,vis the 100α percentile of the chi-square distribution with v degrees of freedom and α is 0.05.

OUR INVESTIGATION: ROAD BLOCKS Issues with case reporting: Accuracy, Timing, Too Few Numbers

“The incidence rates may be underestimated because the N.C. CCR (North Carolina Central Cancer Registry) does not have complete cases for 2012 and 2013”.

Further, they noted that they had not had any data for cases diagnosed in 2014 due to lag time in reporting.

In addition they also noted in their report that “cases diagnosed out of the state and country but that may be receiving treatment in facilities in North Carolina were not included as they are not required to be reported to the N.C. CCR”.

When one looks at the details regarding the individual cases in the cluster, NONE of which would have been expected to be included as observed cases in the final analysis One diagnosed in 2014 Two lived in SC at the time of diagnosis Two though living in NC at the time of diagnosis were diagnosed in PA

When the state was asked to provide a report that would break down the observed and expected incidences based on age and gender, such data was not able to be generated due to “small numbers of observed cases”.

OTHER ISSUES WITH CASE REPORTING As of October 2016, a concise ICD-10 code

for “uveal melanoma” does not exist Rather it is coded as “choroidal/ciliary body/iris

neoplasm” or “melanoma of the face unspecified”

Often no biopsy for histologic diagnosis Often path report part of report to cancer

registry Current reporting of cases does not include

much beyond diagnosis

INVESTIGATING CANCER CLUSTERSREVIEW OF LAST 20 YEARS

EVALUATING CANCER CLUSTERS IN 2016 “Rapid Case Ascertainment” “Reconstruction Residential Histories” “Application of Spatial Analytics” “Continuous Monitoring of Registry Data”

PROPOSAL FOR REGISTRY National US UM Registry Cases directly entered by participating sites

Limited diagnosing and treating centers Allow for:

Accurate and quick case reporting Real time incidence and clustering surveillance Prospective and retrospective investigation

SAMPLE DATA SETTable 3. Sample Data Set

Demographicsa Tumor Genetics Occupation History

Medication Use

Host Factorsb Details of Primary Treatment

Hobbiese Radiation Exposure/Electromagnetic Exposuresh

Lifetime Residential History

Adjuvant Treatment

History of other Cancersf

Surveillance Schedule*

Tumor Characteristics

Clinical Trial Participation

Family Historyg

UV Exposurei

Pre-existing Nevic

Relapse Date Date and Cause of Death

Other Toxic or Environmental Exposuresj

Metastases Characteristics

Previous Ocular Historyd

Histologic Information

Other Medical Historyka: Age, gender, ethnicity b: Eye color, skin color, hair color c: Choroidal nevi d: Trauma, uveitis, infection e: Welding, cooking, other f: Melanoma, mesothelioma, renal cell carcinoma, meningioma, breast cancer, pancreatic cancer g: Melanoma, mesothelioma, renal cell carcinoma, meningioma, breast cancer, pancreatic cancer h: electromagnetic fields [19] i: Sunlight, blue light, black light, tanning bed use i: Pesticides, PCB, phenols j: Prior atypical fungal infections, charcot-marie tooth, valvular disorders  

GEOGRAPHIC SURVEILLANCEEXAMPLE: 10 CASES DIAGNOSED IN 2016

2003

2005

2008

2010

2014

2015

GEOGRAPHIC SURVEILLANCE10 CASES DIAGNOSED IN 2016

2008

ARCGIS: SPATIAL SOFTWAREDetecting and Quantifying Patterns

Analyze your data to reveal patterns or show areas of concentrations. Find statistically

significant spatial clusters of high values (hot spots) and low values (cold spots) in your data.

CONCLUSIONS Uveal melanoma is a rare cancer and may be difficult to

accurately report to state and national cancer registries We don’t know what causes it Efforts need to be focused towards the establishment of a

rare cancer registry for UM Accurate case reporting Real time geographic surveillance Can then lead to appropriate testing of hypotheses

Implementing spatial analytics to a rare cancer registry for the purposes of geographic pattern detection and cluster surveillance to our knowledge will be the first of its kind

Noticeable trends may then lead to the first ever opportunities for primary and secondary prevention

A properly designed rare cancer registry for UM may also encourage the development of such databases for other rare cancers

THANK YOU