the go2 trial - siogthe go2 trial dr peter s hall 1 sponsor: the university of leeds funder: cancer...

Optimising chemotherapy for frail or elderly patients with advanced gastric or

oesophageal cancer

The GO2 trial

1Dr Peter S Hall

Sponsor: The University of Leeds

Funder: Cancer Research UK

PS Hall, D Swinson, JS Waters, S Falk, R Roy, T Tillett, J Nicoll, S Cummings, SA Grumett, K Kamposioras, E Katona, G Velikova, RD Petty, HI Grabsch, MT Seymour

on behalf of the GO2 Investigators

daniel.swinson@nhs.net

• Disclosures– None

Background

• The median age of gastric and oesophageal (GO) cancer

diagnosis > 75 years old.1

• Many patients are frail.

• …however “standard” chemo schedules were developed in

trials of mostly fit patients with median age <65 years2.

3

1. Cancer Research UK. CancerStats. https://www.cancerresearchuk.org/health-professional/cancer-statistics/2. Cunningham D, Starling N, Rao S, et al. New England Journal of Medicine 2008;358(1):36-46

Dr Peter S Hall daniel.swinson@nhs.net

daniel.swinson@nhs.net

administered dose

administered dose

patient’s drug exposure

patient’s drug exposure

efficacy and toxicity effects

efficacy and toxicity effects

consequences for the patient

consequences for the patient

pharmacokinetics

pharmacodynamics

impact

standard oncology trial outcome measures:

RECIST response, PFS, CTCAE adverse events, OS, …

…do not properly reflect our (both doctors’ and patients’) goals

standard oncology trial outcome measures:

RECIST response, PFS, CTCAE adverse events, OS, …

…do not properly reflect our (both doctors’ and patients’) goals

daniel.swinson@nhs.net

we need good clinical trials to ask these questions in:• the fit and very old• the frail and ‘somewhat elderly’• patients with comorbidities

…i.e. all the patients who are often treated but rarely offered enrollment in trials

• Developing better assessment of patients:– Comprehensive Health Assessment (CHA) in the oncology clinic

– nurse and patient modules, 20-40 mins total

– frailty, comorbidity, symptoms, functioning, psychological QL

• Developing better assessment of outcomes:– Overall Treatment Utility (OTU)

– “Am I glad I decided to go ahead with this treatment?”

– combines: survival, non-progression, clinical benefit, patient satisfaction, adverse events and maintenance of QL

FOCUS2 321GO GO2

daniel.swinson@nhs.net

daniel.swinson@nhs.net

80% FU80% FU

80% OxFU80% OxFU

80% Cap80% Cap

80% OxCap80% OxCap

80% EOxCap80% EOxCap

80% OxCap80% OxCap

80% Cap80% Cap

100% OxCap100% OxCap

80% OxCap80% OxCap

60% OxCap60% OxCap

60% OxCap60% OxCap

BSCBSC

RR

R1

R2

FOCUS2CRC

321GOOG

GO2OG

Overall Treatment Utility (OTU) asks 2 questions

Dr Peter S Hall

Good Intermediate Poor

Question1

Clinicianconsidered effective

• Radiological progression• Clinical progression• Deterioration QoL

Clinician scores benefit

Clinician does not score benefit

Clinician does not score benefit

AND OR AND

Question 2

Patient found treatment tolerable

• Toxicity• Interference in daily life• Worth it

Patient scores benefit

Patient does not score benefit

Patient does not score benefit

OR death

daniel.swinson@nhs.net

OTU scores in GO2OTU scored in all 514 patients in the chemotherapy randomisation:

factor contributing to OTU n /514 %

Survival patient died before 11 wk assessment 80 16%

Q1 Alive @ 11 weeks

radiological progression 58 11%

clinical evidence of progression 77 15%

deterioration in QL score§ 178 35%

Q2 Alive @ 11 weeks

SAR or SUSAR 82 16%

“Interfered with my daily activities” 207 40%

“Was not worthwhile” 105 20%

§ fall of >16% from baseline global QL score, EORTC QLQ-C30

daniel.swinson@nhs.net

Elements of OTU Survival

Yes: 434 pts

Effective 273

Tolerated 196 Not tolerated 77

Not effective 161

Tolerated 72 Not tolerated 89

No: 80 pts

Poor OTU169

Poor OTU169

Intermediate OTU149

Intermediate OTU149

Good OTU196

Good OTU196

Q1

Q2

daniel.swinson@nhs.net

11daniel.swinson@nhs.net

Level A (100%) Level C (60%)

Level B (80%)

Level A (100%) Level C (60%)

Level B (80%)

PFS

OS

Level A (100%) Level B (80%) Level C (60%)

poorOTU38%

intermed.OTU26%

good OTU36%

poorOTU31%

intermed.OTU34%

good OTU35%

poorOTU29%

intermed.OTU27%

good OTU43%

OTU to compare treatment arms

Step 3: Can We Personalise Dose?

12daniel.swinson@nhs.net

Frailty

Age Performance status

Question 1: Efficacy

Level A Level B Level C0

102030405060708090

100

Effective

No prog but QoL

Clin prog no rad prog

Rad prog

Question 2: Tolerability

daniel.swinson@nhs.net

0102030405060708090

100

TolerableNot worth it aloneToxicity but not interfereInterfere

Leve

l A

Leve

l B

Leve

l C0

102030405060708090

100

Dead

Alive

Alive at 11 weeks

Can we build a decision aid?

daniel.swinson@nhs.net

Baseline CHA to aid decision makingClinico-pathological factors Age, gender, PS,

comorbidity, disease characteristics

Quality of life EQ-5D

GHS/ Qol C-30

EORTC QLQ fatigue score

Symptoms OG-25 symptoms

Function ADL/ IADL

Get Up and Go test

Standard of care bloods FBC, U&E, LFTs

Specialist bloods BNP, CA19.9, CEA

Frailty assessment 9 elements15daniel.swinson@nhs.netdaniel.swinson@nhs.net

Patient collectedPatient collectedNurse interviewNurse interview

Frailty assessment

16Dr Peter S Hall

• 9 domains• Definition of frailty– Moderately frail 1-2

domains– Severely frail >2

daniel.swinson@nhs.net

Domains Cut pointsWeight loss Weight loss (> 3kg in 3m) | BMI

(<18.5)

Mobility Timed up and go test (>10 seconds)

Falls 2 or more falls in 6m (EORTC G8)

Cognition Mild or severe dementia diagnosis

Function One or more impairment in IADL

Social Place of residence (Requires 24 hour care)

Mood EQ5D question (feelings today)

Fatigue EORTC QLQ Fatigue Score

Polypharmacy Prescribed regular medications (>4)

Baseline CHA to aid decision-making

...as a predictor of treatment benefit – univariate– CHA elements correlating with risk of worse OTU at 9 wk

Factor p

Age (>75 vs <75) 0.63

Frailty (>3/9) 0.003

WHO PS (0-1, 2, >2) 0.21

Distant mets (y/n) 0.13

Histology (sq/other)

0.87

Site (oes/OGJ/stom)

0.72

Anxiety/depression 0.56

Fatigue 0.12

Weight loss 0.29

Factor p

Get-up-and-go 0.60

Dementia/MCI 0.004

ADL/IADL impairment

0.02

EQ-VAS impairment 0.02

QLQ-C30 Global 0.02

EQ-5D Pain 0.14

Anxiety/depression 0.56

OG-25 Taste 0.01

Number of symptoms

0.15

Factor p

raised BNP (/pro) 0.0005

raised CEA/CA19.9 0.02

raised WBC 0.04

raised NLR 0.01

raised plts 0.27

low albumin 0.02

low Hb 0.11

raised urea 0.03

raised bilirubin 0.78

daniel.swinson@nhs.net

Baseline CHA to aid decision-making

...as a predictor of treatment benefit – univariate– CHA elements correlating with risk of worse OTU at 9 wk

Factor p

Age (>75 vs <75) 0.63

Frailty (>3/9) 0.003

WHO PS (0-1, 2, >2) 0.21

Distant mets (y/n) 0.13

Histology (sq/other)

0.87

Site (oes/OGJ/stom)

0.72

Anxiety/depression 0.56

Fatigue 0.12

Weight loss 0.29

Factor p

Get-up-and-go 0.60

Dementia/MCI 0.004

ADL/IADL impairment

0.02

EQ-VAS impairment 0.02

QLQ-C30 Global 0.02

EQ-5D Pain 0.14

Anxiety/depression 0.56

OG-25 Taste 0.01

Number of symptoms

0.15

Factor p

raised BNP (/pro) 0.0005

raised CEA/CA19.9 0.02

raised WBC 0.04

raised NLR 0.01

raised plts 0.27

low albumin 0.02

low Hb 0.11

raised urea 0.03

raised bilirubin 0.78

daniel.swinson@nhs.net

12 of 27 factors p

redictive for O

TU on univariate analysis

Baseline CHA to aid decision-making {Provisional}...as a predictor of treatment benefit – multivariable model

- Best fit of baseline characteristics vs OTU at 9 wk

Factor Cut point Odds ratio

Test statistic

P-value

Age ≥75 1.01 0.00 1.0

Frailty 3+ domains 1.87 5.61 0.018

VAS (EQ-5D) <50 1.99 4.47 0.034

BNP or NT-Pro BNP ≥ULN 2.40 10.25 0.001

CEA or CA19-9 ≥ULN 2.39 7.10 0.008

Dose reduction for GFR

<50/ 1.5 ULN 4.09 8.54 0.003

daniel.swinson@nhs.net

Ordered logistic regression multi-variable model. • Likelihood ratio p<0.0001, Score p<0.0001, Wald

p<0.0001

Provisional Decision Aid

daniel.swinson@nhs.net

Age Dose reduction for renal BNP or NT- CEA >3ug/ml or VAS <50 Frailty Poor GoodProp<75 No No No No Not/Slightly frail (0-2)

>=75 No No No No Not/Slightly frail (0-2)

<75 No No No No Severely frail (≥3)

<75 No No No Yes Not/Slightly frail (0-2)

>=75 No No No No Severely frail (≥3)

>=75 No No No Yes Not/Slightly frail (0-2)

<75 No No Yes No Not/Slightly frail (0-2)

<75 No Yes No No Not/Slightly frail (0-2)

>=75 No No Yes No Not/Slightly frail (0-2)

>=75 No Yes No No Not/Slightly frail (0-2)

<75 Yes No No No Not/Slightly frail (0-2)

<75 No No Yes No Severely frail (≥3)

<75 No No Yes Yes Not/Slightly frail (0-2)

<75 No Yes No No Severely frail (≥3)

<75 No Yes Yes No Not/Slightly frail (0-2) <40 35 4<75 Yes No No Yes Not/Slightly frail (0-2)

<75 Yes No Yes No Not/Slightly frail (0-2)

>=75 Yes Yes Yes Yes Severely frail (≥3) 90 3 9

55

1740

125

<20

<30

<50

75 19<10

2160

30

Provisional Decision Aid Simplified

Variables Proportion of Patients Probability of Good OTU

All favourable 19% 75%

Severely frail or QoL 21% 60%

Either TM or BNP/ NT-ProBNP 30% 55%

Dose reduction alone or2 other variables with full dose

21% 35-40%

Dose reduction + 1 other variable

1% 25%

All unfavourable 9% 3%

daniel.swinson@nhs.net

TM = tumour markerQoL measured by EQVD VAS

22Click to edit Author Name

Key points

Treatment recommendations• Doublet chemotherapy delivered at significantly lower doses delivers

better patient experience without sacrificing efficacy

Assessing patients• CHA is deliverable and may inform decision making

• Decision aid includes both clinical and lab elements (e.g. frailty and BNP)

•Novel trial end points • OTU may provide more patient centred information than

conventional oncology endpoints

• Heavily influenced by patient reported experiencedaniel.swinson@nhs.net

Further work……• Validate and refine

–Criteria for frailty and decision tool with other data sets

–Test established frailty criteria using OTU as an endpoint

–Qualitative research to further refine OTU

• Explore

–Mechanisms of why BNP (/pro) correlation with poor outcomes

–Dose minimisation in other cancer sites, younger fitter patients, in

combination with novel agents23daniel.swinson@nhs.net

All 321 GO investigatorsMatt Seymour, Peter Hall,

Simon LordMichelle Collinson

Helen MarshallMarc Jones

Helen HowardGalina VelikovaAlan Anthoney

Rajesh Roy, Jo DentSue Cheeseman, Kim Last

CTRU LeedsYorkshire CRN

55 patients and their families

All the GO2 Investigators Matt Seymour, Peter Hall,

Justin Waters, Helen Marshall, David Cairns, Russell Petty, Raj Roy,

Stephen Falk, Jon Wadsley, Simon Lord, Christine

Allmark, Cat Handforth, Ann Crossley, Heike Grabsch, Galina Velikova, Kostas

Kamposoras, Jonathan Nicoll, Tania Tillett, Sharon

Ruddock, Eszter Katona , Helen Howard

CTRU Leeds, NIHR CRN558 patients and their

families

daniel.swinson@nhs.net

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