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POST IASLC: la WCLC in italia

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Title: POST IASLC: la WCLC in italia


1
  • POST IASLC la WCLC in italia
  • Milano, 8 novembre 2013
  • Prevenzione
  • Ugo Pastorino
  • Chirurgia Toracica, Istituto Nazionale Tumori,
    Milano

2
Under the Australian legislation, companies have
had to sell their cigarettes in a logo-free, drab
dark brown packaging from 1 December 2012.
Government research found that olive green was
the least attractive colour, particularly for
young people. After concerns were expressed by
the Australian Olive Association, the name was
changed to drab dark brown.
Plain cigarette packaging
NicolaRoxon, Health Minister Attorney-General
of Australia
3
With the plain packaging and tax increases, the
Australian government aims to bring down smoking
rates from 16.6 per cent in 2007 to less than 10
per cent by 2018
Plain cigarette packaging
NicolaRoxon, Health Minister Attorney-General
of Australia
4
PL04.01 V Beral
5
THE MILLION WOMEN STUDY
Small cell, large cell squamous tumours
Small cell, large cell squamous tumours
Lung cancer incidence 60 fold increase in
small cell, large cell squamous
tumours 10 fold increase in adenocarcinoma
Adenocarcinoma
Adenocarcinoma
PL04.01 Valerie Beral
Unpublished results
6
THE MILLION WOMEN STUDY
90 excess prevented by stopping at 40
Reduction in lung cancer incidence by stopping
smoking
97 excess prevented by stopping at 30
PL04.01 Valerie Beral
Unpublished results
7
Lung Cancer in Never Smokers
  • Approximately 25 of lung cancer cases in the
    world occur in never-smokers
  • (Sun et al., 2007)
  • Lung cancer in never-smokers is now considered
    the 6th most common cause of cancer deaths in the
    United States, and two-third of them are women
  • (Samet et al., 2009)

PL04.02 - Chien-Jen Chen
8
Secondhand Smoke and LCNS in Taiwan
  • SHS Exposure Cases Controls
    Adjusted OR (95 CI)
  • No 325
    423 1.00 (referent)
  • Home or workplace 700 655
    1.32 (1.10-1.59)
  • Home and workplace 195 143
    1.73 (1.32-2.26)

  • P for trend lt0.0001

PL04.02 - Chien-Jen Chen
9
Conclusion
  • Lung cancer in never smokers is an important
    global heath issue with a significant disease
    burden.
  • Secondhand smoke, radon, arsenic, asbestos,
    silica, cooking fume, indoor air pollution from
    coal combustion in poorly ventilated spaces,
    history of tuberculosis, and family history of
    lung cancer are well-documented environmental
    risk factors for lung cancer in never smokers.
  • Lung cancer in never smokers is associated with
    genetic polymorphisms in CYP1A1, GSTM1, XRCC1,
    MLH1, IL10, IL6, IL1, and TNF, as well as in loci
    at 10q25.2, 6q22.2, 6q21.32, 5p15.33, 3q28 and
    17q24.3

PL04.02 - Chien-Jen Chen
10
Risk of lung cancer associated with domestic use
of coal in China (N37.272)
Compared with smokeless coal, an increased risk
of lung cancer death (HR 36 in M and 99 in W)
Barone-Adesi F et al, BMJ Aug 2012
E03.4 Silvia Novello
11
Hormone Replacement Therapy (HRT) and Lung Cancer
Risk
Reference Type of study N Risk of lung Ca with HRT 95 CI
Taioli, JNCI, 1994 Case control 180 1.7 1.0-2.8
Adams,Int J Cancer, 1989 Cohort study 23,244 1.3 0.9-1.7
Wu, Cancer Res, 1998 Case control 336 1.3 0.71-1.53
Women's Health Initiative, JAMA, 2002 Cohort 16,690 1.04 0.71-1.53
Blackman, Pharmacoepidemiol Drug Saf, 2002 Case Control 662 1.0 -
Ettinger, Ob Gynecol, 1996 - 454 0.78 0.04-1.15
Kreuzer, 2003 Case control 1723 0.83 0.64-1.09
Olsson, Ob Gyne, 2003 Cohort 29,508 0.24 0.08-0.76
Schabath, Clin Ca Res, 2004 Case Control 1008 0.66 0.51 - 0.89

12
LDCT screening is most effective (greatest
mortality reduction per screen) at highest risks
E01.01 Martin Tammemagi
13
PLCOm2012
CXR
Controls
PLCO smokers only N 36,286
37,332
Development
Validation
Logistic regression model - Predicts 6-year risk
of lung cancer
Prospective design Incidence data
(Optimal estimator of risk)
E01.01 Martin Tammemagi
14
PLCOM2012 PREDICTORS
  • Risk
  • ? age
  • ? race/ethnicity
  • ? education (SES)
  • ? body mass index
  • ? personal history of cancer
  • ? family history of lung cancer
  • ? COPD
  • ? smoking status, ?intensity, ?duration,
    ?quit-time

7 other
4 smoking
E01.01 Martin Tammemagi
15
Calibration in PLCO smokers - Observed
predicted probabilities of lung cancer by
PLCOm2012
E01.01 Martin Tammemagi
16
Lung cancer events (casesdeaths) in PLCO NLST
by deciles of PLCOm2012
NLST incidence - 6 years
PLCO deaths - 11 years
PLCO incidence - 6 years
NLST deaths - 6 years
E01.01 Martin Tammemagi
17
Biennial lung cancer screening by low-dose CT
scan - a simulation of cost effectiveness in
Canada
  • John R. Goffin1, William M. Flanagan2, Anthony B.
    Miller3, Fei Fei Liu4, Sonya Cressman5, Natalie
    Fitzgerald4, Sharon Fung4, Saima Memon4, Michael
    C. Wolfson6, William Evans1
  • 1Mcmaster University, Hamilton/Canada,
    2Statistics Canada, Ottawa/Canada, 3Dalla Lana
    School Of Public Health, Toronto/Canada,
    4Canadian Partnership Against Cancer,
    Toronto/Canada, 5The British Columbia Cancer
    Agency, Vancouver, BC/Canada, 6University Of
    Ottawa, Ottawa/Canada

O05.05 John Goffin
18
Canadian Risk Management Model (CRMM) of the
Canadian Partnership Against Cancer
  • Microsimulation individuals and aggregate
    population
  • Considers demographics, risk factors, mortality
    risk
  • Allows screening, staging, diagnosis, management

O05.05 John Goffin
19
Annual Screening
s at bar ends indicate 1000s QALYs saved
96
46
112
79
104
128
96
96
34
50
16
115
78
1000s Cdn / QALY
20
Scenario Comparisons
Scenario CT Scans (millions) Cost ( billions) QALYs ICER
Annual 7.8 2.4 96,000 24,700
Uptake 40 5.2 1.6 63,000 25,800
Uptake 80 10.4 3.2 125,000 25,200
Cessation 0.5 7.8 2.8 29,000 95,700
Cessation 1.5 7.8 2.6 111,000 23,500
CT cost 0.5 7.8 1.9 96,000 19,900
CT cost 2 7.8 3.8 96,000 39,800
Biennial B Stage Shift 1 4.3 1.2 69,000 17,700
Biennial B Stage Shift 4 4.3 1.2 94,000 12,900
O05.05 John Goffin
21
Conclusions
  • Annual reference scenario ICER 24,700 /QALY
  • Biennial ICER 12,900 20,600 /QALY
  • Sensitive to adherence, smoking cessation, CT
    cost
  • Model limits
  • Model calibration
  • systemic uncertainty analysis
  • Screening may be cost-effective
  • in the Canadian context

O05.05 John Goffin
22
  • Using published LDCT data,
  • LC rate higher in screenees with COPD
  • COPD was not usually severe
  • outcomes were similar to non-COPD pts
  • COPD is under-diagnosed in screenees

O05.07 Henry Marshall
23
PL03 Lung cancer probability in subjects with
CT-detected pulmonary nodules
Nanda Horeweg MD Erasmus University Medical
Center Department of Public Health /
Pulmonology Rotterdam, the Netherlands
Horeweg N, van Rosmalen J, Heuvelmans MA, van
der Aalst CM, Vliegenthart R, Scholten ET, ten
Haaf K, Nackaerts K, Lammers JWJ, Groen HJM,
Weenink C, Thunnissen E, van Ooijen P, de Jong
PA, de Bock MD GH, Mali W, Oudkerk M, de Koning
HJ
Pl03.01 Nanda Horeweg
24
Results nodule volume algorithm based on LC
probability
Screening result Nodule volume
negative lt 100 mm³
indeterminate 100 to 300 mm³
positive 300 mm³
Follow-up CT for VDT assessment - final
screening result negative for VDT 600 days
- final screening result positive for VDT lt 600
days
PL03 Lung cancer probability in subjects with CT
detected nodules N. Horeweg
25
Results performance nodule volume algorithm
Screen test parameters Performance percentage (95CI)
Diagnostic work-up 5.9
Follow-up CT scan 7.8
Sensitivity 90.9 (81.2-96.1)
Specificity 94.9 (94.4-95.4)
Positive predictive value 14.4 (11.3-18.1)
Negative predictive value 99.9 (99.8-100.0)
PL03 Lung cancer probability in subjects with CT
detected nodules N. Horeweg
26
Results 2-year lung cancer probability by nodule
volume
Volume of largest nodule in mm³ Rounds 1 and 2 Rounds 1 and 2 Lung cancer probability
Volume of largest nodule in mm³ Cases All Lung cancer probability
1000 62 241 25.7 (20.6-31.6)
750 - 1000 12 63 19.0 (11.1-30.6)
500 - 750 12 110 10.9 (6.2-18.2)
300 - 500 18 203 8.9 (5.6-13.7)
200 - 300 14 243 5.8 (3.4-9.5)
100 - 200 13 868 1.5 (0.9-2.6)
50 - 100 12 1,643 0.7 (0.4-1.3)
25 - 50 10 1,969 0.5 (0.3-0.9)
lt25 5 1,054 0.5 (0.2-1.1)
No nodule detected 30 7,630 0.4 (0.3-0.6)
All participants 188 14,024 1.3 (1.2-1.5)
PL03 Lung cancer probability in subjects with CT
detected nodules N. Horeweg
27
Results 2-year lung cancer probability by nodule
VDT
VDT of fastest growing nodule in days Rounds 1 and 2 Rounds 1 and 2 Lung cancer probability
VDT of fastest growing nodule in days Cases All Lung cancer probability
lt100 8 32 25.0 (13.0-42.3)
100 - 200 6 56 10.7 (4.7-21.8)
200 - 400 12 179 6.7 (3.8-11.5)
400 - 600 7 172 4.1 (1.8-8.3)
600 - 800 0 130 0.0 (0.0-3.4)
800 - 1000 1 108 0.9 (0.0-5.6)
1000 7 712 1.0 (0.4-2.1)
Smaller or equal volume on 2nd CT 6 903 0.7 (0.3-1.5)
Resolved on 2nd CT 1 208 0.5 (0.0-2.9)
No follow-up CT, not referred 4 443 0.9 (0.3-2.4)
No follow-up CT, directly referred 5 11 45.5 (21.3-72.0)
All participants with largest nodule 50-500mm³ 57 2954 1.9 (1.5-2.5)
PL03 Lung cancer probability in subjects with CT
detected nodules N. Horeweg
28
Discussion main results
  • LC risk nodules lt5mm (100mm³) NS different from
    no nodules
  • LC risk nodules 5-10mm (100-300mm³) justifies
    follow-up CT
  • LC risk nodules 10 mm (300mm³) warrants
    immediate work-up
  • Estimated performance Fleischner criteria good
  • Possible improvements raising thresholds,
    evaluation after 1 CT
  • Yield less CTs and diagnostic procedures
  • Performance comparable, slightly higher
    sensitivity and specificity

PL03 Lung cancer probability in subjects with CT
detected nodules N. Horeweg
29
Control N1408
Spiral CT N1403
O05.01 Maurizio Infante
30
Active Follow-up as of November 2012
LDCT Median FU 75.5 months 81.3 gt 60 months
Control Median FU 73.1 months 80.7 gt 60 months
13541 person-years overall
O05.01 Maurizio Infante
31
N lung cancers diagnosed per year
Patients 92
Lung cancers 100
Single Tumor 88
Synchronous 4
Metachronous 8
Patients 60
Lung cancers 61
Single Tumor 59
Synchronous 1
Metachronous 1
O05.01 Maurizio Infante
32
Number of deaths
163 (13)
138 (12)
73 deaths still undetermined
O05.01 Maurizio Infante
33
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cardio- vascular
true benefits in health care are measurable
mortality trends for major causes in USA from
1975
cancer
Jemal, CA Can J Clin 60277, 2010
38
males
cancer mortality trends in USA
PSA
Jemal, CA Can J Clin 60277, 2010
1930
2005
39
females
cancer mortality trends in USA
Mx
Jemal, CA Can J Clin 60277, 2010
1930
2005
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