the rapid registrations cancer dataset

The Rapid Registrations Cancer Dataset

Sean McPhail

Principal Analyst, National Disease Registration Service

Intended Audience & Learning Goals

Technical brief for researchers, ‘cancer data people’, information leads/

managers interested in the capabilities of the Rapid Registration (RR) Data.

Not presenting finalised 2020 time series data.

• What is the Rapid Registration Data?

• Survey of data features and quality issues to be aware of

• How do I use/access the data?

• Q&A

2 The Rapid Registrations Cancer Dataset

Please also refer to the data quality document

http://www.ncin.org.uk/cancer_type_and_topic_specific_work/topic_specific_work/covid19

Learning Goals

• What is the Rapid Registration Data

• Data features and quality issues to be aware of

• 2020 data sneak peak

• How do I access/use the data?

• Q&A

What is the Rapid Registration Data

• Background – ‘normal’ cancer registration

• Rationale for creating the RR dataset

• Build process for the RR dataset

• RR Structure: Tables & field lists


Encore

2018 ONS FIGURES517,604

quality >98%

timeliness~18 months


Rapid Registrations Rationale


Build process for the RR dataset

CWT

HES

COSD RTDS

SACTRapid

Registrations

Arriving at NDRS within 4 months:

• Cancer Outcomes & Services Dataset

• Hospital Episode Statistics

• Cancer Waiting Times

• Systemic Anti-Cancer Therapy

• Radiotherapy DataSet


Build process for the RR dataset

1. Summarise everything useful into an unified events ‘pathway’ table.

2. Refine, combine and filter those events into rapid “proxy” tumour diagnoses

– the best performance so far from case-finding using COSD data.

3. Add auxiliary information to bare tumour & patient detail.

4. (Note - patients in pathway table >> patients in tumour table.)


Rapid Registration tumour table inclusion

1. Created for 2018-01-01 to most recently available data

2. Covers all malignant cancers (excl. NMSC) and selected non-malignant

cancers: Breast, Bladder & Brain (ICD-10 C00-C97 excl. C44, plus D05,

D09, D32, D33, D35, D41, D42-D44)

3. Persons appearing in English COSD data – includes cross-border cases.


Rapid Registration structureRAPID_TUMOURTUMOUR_AVPID

INDIVIDUALID

PATIENTID

NHSNUMBER

DIAGNOSIS DATE

BASIS OF DIAGNOSIS

TUMOUR SITE

TUMOUR MORPHOLOGY

ROUTE TO DIAGNOSIS (HES)

CHARLSON COMORBIDITY

STAGE

BIRTH DATE

SEX

POSTCODE

SURNAME

FORENAME

ETHNICITY

RAPID_PATHWAYAVPID

INDIVIDUALID

PATIENTID

NHSNUMBER

SOURCE_TABLE

SOURCE ID

EVENT_TYPE

EVENT_PROPERTY_1

EVENT_PROPERTY_2

EVENT_PROPERTY_3

EVENT_DATE

EVENT_END

TRUST_CODE

ID fields

Patient fields

Tumour fields

“What, where & when”

34 event types summarising 5 data types


Aside: Encore, CAS & monthly snapshots

So… a monthly system and “CAS2010” is the 2020 October snapshot (CASyymm)

Cancer Analysis

System (CAS)

inc. COSD,

SACT, & RTDS

Encore

monthly

External (NHSD /

NHSE)

monthly(-ish)

CAS-reference

(CASREF) inc.

HES and CWTNHSnumberlinkage+Rapid Reg.

Learning Goals





• Q&A

Data features and quality issues

• Comparing to normal registration data

• False positives and false negatives

• Stage at diagnosis

• “snapshot creep”

• Summary


Comparing to normal cancer registration data, 2018 cases

CR

Lung

Br Pr

Mel. Bladder

C00 C97D05 D45

Cancer type by ICD-10 code


Further defining quality – False Positives, False Negatives

Compare rapid registration data to normal registrations, Apr 2018 to Sept 2018.

Define a matched/successful proxy registration as:

1. Matching in a broad cancer group (e.g., C18-C21, or C50 & D05)

2. Matching diagnosis date to within 3 months

Errors:

False negative (FNE) – real registration but no proxy registration (“missing data”)

False positive (FPE) – no real registration but proxy registration (“bad data”)

Note assumption – COSD data behaviour in 2020 ~ that in 2018


False Positives (5%), False Negatives (18%)


False Positives, False Negatives


What are the False negatives?

Cancers not represented in

COSD…

Age dependence is explained

by more clinical pathways in

older people (plus DCOs).


What are the False Positives?

Not so clear cut, but approximately:

30% ‘Tricky’ tumour sites – (Unknown/Sarcoma)

20% D-code / C-code mismatch in COSD and normal registration

12.5% COSD tumours proved mistaken and deleted

5% Melanoma / NMSC confusion

32.5% Tumours diagnosed in previous years reoccuring?

Proportion of FNEs & FPEs treated

20 Presentation title - edit in Header and Footer

FNE FPE

SACT 13% 22%

RTDS 9% 14%

Surgery 26% 14%

Any 39% 40%


Relaxing the matching criteria


Stage at diagnosis (Big 4 cancers) – TNM stage

Proxy Stage

Normal stage 1 2 3 4 Unk

1 89% 9% 2% 1% 30%

2 6% 83% 5% 1% 16%

3 3% 5% 85% 3% 12%

4 1% 2% 6% 95% 16%

Unknown 2% 2% 2% 1% 26%

100% 100% 100% 100% 100%

0%

5%

10%

15%

20%

25%

30%

35%

1 2 3 4 Unknown

Pro

po

rtio

n o

f tu

mo

urs

Big 4 cancers, stage completeness, TNM Group

Proxy Normal

“~80% of (Big 4) cancers are staged, of those 80-90% are correct.”

23 Presentation title - edit in Header and Footer

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

1 2 3 4 Unknown

Pro

port

ion o

f tu

mours

Breast cancer

Proxy Normal

0%

5%

10%

15%

20%

25%

30%

35%

1 2 3 4 Unknown

Pro

port

ion o

f tu

mours

Colorectal cancer

Proxy Normal

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

1 2 3 4 Unknown

Pro

port

ion o

f tu

mours

Lung cancer

Proxy Normal

0%

5%

10%

15%

20%

25%

30%

35%

40%

1 2 3 4 UnknownP

roport

ion o

f tu

mours

Prostate cancer

Proxy Normal


Stage at diagnosis – Early/Late stage

Proxy Stage

Normal stage Early Late UnkEarly 93% 5% 46%

Late 5% 94% 28%

Unknown 2% 2% 26%

100% 100% 100%0%

10%

20%

30%

40%

50%

60%

Early Late Unknown

Pro

po

rtio

n o

f tu

mo

urs

Big 4 cancers, stage completeness, Early vs Late

Proxy Normal


‘snapshot creep’


Data Summary

• Overall error rate:

• False Positive: 5%

• False Negative: 18%

• Older persons and more clinical pathways are under-represented

• Strong variation in quality with cancer type

• “creep”: completeness in the most recent months increases over >1 month

Please also refer to the data quality document


Learning Goals





• Q&A

How do I access / use the data?

• Which datasets?

• Capabilities of the RR data

• Accessing the data

• Ongoing development


Which datasets?

Cancer Analysis

System (CAS)

inc. COSD,

SACT, & RTDS

CAS-reference

(CASREF) inc.

HES and CWT

RAPID_TUMOURTUMOUR_AVPID

INDIVIDUALID

PATIENTID

NHSNUMBER

RAPID_PATHWAYAVPID

INDIVIDUALID

PATIENTID

NHSNUMBER

SOURCE_TABLE

SOURCE ID


Capabilities of the Rapid Reg. dataset

The Good

Reasonable proxy for cancer registrations (in 2018 overlap).

Typically 4-5 month delay (varying with data type).

Strong potential to link to other datasets.

The less good

Some systematic biases in FNE (missing registrations) in particular.

2018 data ~ 2020 data?


Accessing the data

General principles:

• Not trying to replace gold standard cancer registration data.

• Use where normal registration data doesn’t cover period of interest…

& where question can be adequately answered given limitations.

• Generally restricting patient data availability to those in tumour table.

Available through PHE’s Office for Data Release (from late October):

[email protected]

https://www.gov.uk/government/publications/accessing-public-health-england-data


mailto:[email protected]

https://www.gov.uk/government/publications/accessing-public-health-england-data



Ongoing development

• Monthly builds incorporating data as it comes in.

• Extend staging to new tumour types.

• Attempt to lower FNE without raising FPE.

• Add other events/fields, depending on demand?

User feedback is very welcome.

Learning Goals





• Q&A

Any Questions?

[email protected]

Many thanks to:

Tom Bacon

Jackie Charman

Cong Chen

Carolynn Gildea

Sophie Jose

Ravneet Sandhu

Sally Vernon

This work uses data that has been provided by

patients and collected by the NHS as part of their

care and support. The data are collated, maintained

and quality assured by the National Cancer

Registration and Analysis Service, which is part of

Public Health England (PHE).

the rapid registrations cancer dataset

Documents