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Second round results from the Manchester ‘Lung Health Check’ community-based targeted lung cancer screening pilot

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  • Wythenshawe Hospital, Manchester University NHS Foundation Trust

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We report results from the second annual screening round (T1) of Manchester’s ‘Lung Health Check’ pilot of community-based lung cancer screening in deprived areas (undertaken June to August 2017). Screening adherence was 90% (n=1194/1323): 92% of CT scans were classified negative, 6% indeterminate and 2.5% positive; there were no interval cancers. Lung cancer incidence was 1.6% (n=19), 79% stage I, treatments included surgery (42%, n=9), stereotactic ablative radiotherapy (26%, n=5) and radical radiotherapy (5%, n=1). False-positive rate was 34.5% (n=10/29), representing 0.8% of T1 participants (n=10/1194). Targeted community-based lung cancer screening promotes high screening adherence and detects high rates of early stage lung cancer.
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Second round results from the Manchester ‘Lung
Health Check’ community-based targeted lung cancer
screeningpilot
Phil A Crosbie,1,2 Haval Balata,1 Matthew Evison,1 Melanie Atack,3
Val Bayliss-Brideaux,3 Denis Colligan,3,4 Rebecca Duerden,1 Josephine Eaglesfield,3
Timothy Edwards,1 Peter Elton,5 Julie Foster,6 Melanie Greaves,1 Graham Hayler,3
Coral Higgins,4 John Howells,7 Klaus Irion,8 Devinda Karunaratne,8 Jodie Kelly,1
Zoe King,3 Judith Lyons,1 Sarah Manson,1 Stuart Mellor,9 Donna Miller,10
Amanda Myerscough,3 Tom Newton,9 Michelle O’Leary,11 Rachel Pearson,3,4
Julie Pickford,6 Richard Sawyer,1 Nick J Screaton,12 Anna Sharman,1 Maggi Simmons,3
Elaine Smith,1 Ben Taylor,13 Sarah Taylor,3,4 Anna Walsham,14 Angela Watts,1
James Whittaker,15 Laura Yarnell,3,4 Anthony Threlfall,3 Phil V Barber,1 Janet Tonge,3,4
Richard Booton1
Brief communication
To cite: CrosbiePA,
BalataH, EvisonM, etal.
Thorax Epub ahead of print:
[please include Day Month
Year]. doi:10.1136/
thoraxjnl-2018-212547
For numbered affiliations see
end of article.
Correspondence to
DrPhil ACrosbie, Manchester
Thoracic Oncology Centre, North
West Lung Centre, Manchester
University NHS Foundation Trust,
Wythenshawe, M23 9LT, UK;
philip. crosbie@ manchester.
ac. uk
Received 30 August 2018
Revised 12 October 2018
Accepted 22 October 2018
© Author(s) (or their
employer(s)) 2018. Re-use
permitted under CC BY.
Published by BMJ.
ABSTRACT
We report results from the second annual screening
round (T1) of Manchester’s ’Lung Health Check’ pilot of
community-based lung cancer screening in deprived areas
(undertaken June to August 2017). Screening adherence
was 90% (n=1194/1323): 92% of CT scans were classified
negative, 6% indeterminate and 2.5% positive; there
were no interval cancers. Lung cancer incidence was 1.6%
(n=19), 79% stage I, treatments included surgery (42%,
n=9), stereotactic ablative radiotherapy (26%, n=5) and
radical radiotherapy (5%, n=1). False-positive rate was
34.5% (n=10/29), representing 0.8% of T1 participants
(n=10/1194). Targeted community-based lung cancer
screening promotes high screening adherence and detects
high rates of early stage lung cancer.
INTRODUCTION
The National Lung Screening Trial (NLST) demon-
strated a 20% reduction in lung cancer–specific
mortality with annual low-dose CT (LDCT) screening
of high-risk ever smokers compared with chest X-ray.1
A key requirement for screening implementation is
to ensure services are accessible to those at greatest
risk. In Manchester, we developed a community-based
‘Lung Health Check’ (LHC) approach to target high-
risk smokers in deprived areas. LHCs were nurse-led
and included calculation of lung cancer risk using
the PLCOM2012 risk model. Those at higher risk were
eligible for annual LDCT screening over two screening
rounds. There was a high prevalence of lung cancer
detection at baseline (T0; undertaken June to August
2016) (3%); most cancers were early stage (80%) and
therefore radically treatable.2 Here, we report the
results of the second screening round (T1; undertaken
June to August 2017).
METHODS
A description of the screening pilot has previously
been published.2 In brief, ever smokers aged 55–74
at participating general practices (n=14) were
invited to a LHC; this consisted of 6-year lung cancer
risk calculation (PLCOM2012),3 symptom assessment,
smoking cessation advice and spirometry. Individ-
uals at higher risk (defined as ≥1.51% over 6 years)
were offered annual LDCT screening. All LDCT
scans (Optima 660; GE Healthcare) were reported
by National Health Service (NHS) consultant radi-
ologists with an interest in thoracic radiology and
classified as either negative, indeterminate or posi-
tive. Pulmonary nodules were managed in accord-
ance with British Thoracic Society (BTS) guidelines
adapted for an annual screening programme.4 Inde-
terminate scans required surveillance imaging at
3 months and positive scans had findings concerning
for lung cancer requiring immediate assessment
in the rapid access lung cancer clinic based in a
specialist centre. A false positive was any screened
individual referred to the lung cancer clinic who
was not diagnosed with lung cancer. An interval
cancer was defined as any lung cancer diagnosed
outside of screening before the second-round scan
(T1). Volume doubling times (VDTs) were calcu-
lated in accordance with BTS guidelines.4 VDT
was estimated in those without a nodule at baseline
(T0) by assuming the nodule appeared the day after
the CT scan was performed and measured 1 mm.
Lung cancers were managed in accordance with
national guidelines.5 The seventh edition of TNM
lung cancer staging manual was used.6 In this paper,
the first screening round is referred to as T0 and
the second screening round 12 months later as T1.
Individuals with an indeterminate scan at T1 had a
further LDCT scan 3 months later, which we refer
to as the ‘3-month surveillance’ scan.
RESULTS
Ninety per cent of those eligible had a T1 scan
(June to August 2017) (n=1194/1323). Non-at-
tendees were significantly more likely to be
current smokers (63.6% vs 50.6%, p=0.005), but
there was no difference according to deprivation
1CrosbiePA, etal. Thorax 2018;0:1–5. doi:10.1136/thoraxjnl-2018-212547
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Brief communication
(p=0.79) (table 1). The majority of T1 scans were ‘negative’
(92%, n=1099) (figure 1); 71 were ‘indeterminate’ of which
84.1% (n=58/71) were for nodule surveillance. The 3-month
surveillance imaging rate was significantly lower than T0 (6%
vs 13.7%; p=0.0001); six individuals were reclassified positive
after 3-month scans. Overall, 30 scans were ‘positive’ (2.5%,
n=30/1194)—one patient declined assessment. Of 29 individ-
uals seen, 19 were diagnosed with lung cancer and 10 were not.
The false-positive rate was 34.5% (n=10/29), which represents
0.8% of T1 participants (n=10/1,194). This false-positive rate
was significantly lower (p=0.0001) than T0 (corresponding
values 48.1% and 2.8%) and over both screening rounds it was
44.5% and 3.5%, respectively. There were no interval cancers
between T0 and T1.
The incidence of lung cancer in T1 was 1.6% (n=19/1,194),
79% were stage I (n=15), 10.5% stage III (n=2) and 10.5%
stage IV (n=2) (table 2). Pathological subtypes included adeno-
carcinoma (32%, n=6), squamous cell (21%, n=4), small cell
(16%, n=3) and non-small cell lung cancer not otherwise spec-
ified (10.5%, n=2). A clinical diagnosis was confirmed by the
multidisciplinary team in four cases without pathological confir-
mation (21%). Cancer treatments included surgery (42%, n=9),
stereotactic ablative radiotherapy (26%, n=5) and radical radio-
therapy (n=1) (table 2). One individual had surgery for a benign
lesion (granulomatous disease). There were no deaths within 90
days of surgery.
Thirteen individuals with a negative baseline scan (T0)
were diagnosed with lung cancer in the second round; after
Table 1 Comparison of attendees and non-attendees of the second (T1) screening round
Variable
T1 Screening round
P valuesAttendees Non- attendees
No of attendees (%) 1194 129
Mean age (years±SD) 64.7 (5.4) 64.2 (5.6) 0.34
Sex M/F (F%) 587/607 (50.8) 65/64 (49.6) 0.79
Median IMD rank (IQR) 2848 (3615) 2908 (4195) 0.79
BMI (±SD) 28.5 (5.4) 28.3 (5.7) 0.73
Lung cancer risk (PLCOM2012±SD) 4.8 (3.8) 5.4 (4.7) 0.13
Education(%) Less than ‘O’ level 822 (68.8) 93 (72.1) 0.58
‘O’ level 213 (17.8) 24 (18.6)
A’ level 44 (3.7) 3 (2.3)
University/college 77 (6.4) 5 (3.9)
University degree 26 (2.2) 4 (3.1)
Postgraduate/professional 12 (1.0) 0
Smoking status(%) Current 604 (50.6) 82 (63.6) 0.005
Former 590 (49.4) 47 (36.4)
Smoking exposure(mean±SD) Duration (years) 43.4 (8.3) 45.4 (7.0) 0.008
Cigarettes/day 24.1 (12.8) 23.9 (12.5) 0.83
Pack-years 51.2 (25.9) 53.4 (28.6) 0.37
Spirometry(mean±SD) FEV12.16 (0.7) 2.08 (0.7) 0.26
% predicted FEV184.9 (24.5) 81.0 (21.6) 0.09
FVC 3.17 (1.0) 3.10 (1.0) 0.44
% predicted FVC 100.4 (24.6) 96.3 (23.7) 0.07
FEV1:FVC ratio 67.9 (10.7) 67.6 (12.3) 0.75
Airflow obstruction Yes (%) 588 (49.6) 63 (53.1) 0.45
COPD/emphysema Yes (%) 386 (32.2) 37 (28.7) 0.40
FH lung cancer Yes (%) 326 (27.3) 32 (24.8) 0.54
MRC Dyspnoea Score (%) 1 781 (65.4) 72 (55.8) 0.13
2 261 (21.9) 32 (24.8)
3 98 (8.2) 14 (10.9)
4 53 (4.4) 11 (8.5)
5 1 (0.1) 0
Performance status (%) 0 655 (54.9) 60 (46.5) 0.12
1 403 (33.8) 46 (35.7)
2 116 (9.7) 19 (14.7)
3 20 (1.7) 4 (3.1)
4 0 0
BMI, Body Mass Index;FH, family history;IMD, Index of Multiple Deprivation; MRC, Medical Research Council.
2CrosbiePA, etal. Thorax 2018;0:1–5. doi:10.1136/thoraxjnl-2018-212547
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Brief communication
retrospective review, five were visible at baseline as sub-5 mm
nodules and all were stage I at diagnosis (table 2). The T0
false-negative rate was therefore 0.4% (n=5/1337), negative
predictive value 99.6%, sensitivity 89.4% and specificity 97.1%.
The benign surgical resection rate over both rounds was 2.5%
(n=1/40). Tumour VDT was highest in those with a true nega-
tive baseline scan (average 49±26 days), followed by false-neg-
ative (99±50 days) and indeterminate scans (297±215 days;
p=0.009) (table 2).
DISCUSSION
In this paper, we report results from the second round of the
Manchester ‘Lung Health Check’ pilot, a targeted lung cancer
screening service based in deprived areas of Manchester.
Screening adherence was high (90%) despite most participants
being from the lowest decile of deprivation in England, empha-
sising the benefit of accessible community-based services. The
incidence of lung cancer was 1.6% (n=19), most cancers were
stage I (79%) and 89% of individuals with screen detected cancer
were offered curative-intent treatment. Over both screening
rounds, 4.4% of the cohort were diagnosed with lung cancer,
equivalent to one cancer detected for every 23 people screened.
This is high when compared with other studies and more than
2.5 times that seen in NLST (T0: 1.0%, T1: 0.7%) and NELSON
(T0: 0.9%, T1: 0.7%).1 7 Our benign surgical resection rate was
low at 2.5%, 10-fold lower than NLST and NELSON.1 7 The
pathological confirmation rate and surgical resection rate are
lower than reported in other trials. The exact reason for this
is unclear but may be a consequence of higher deprivation and
increased comorbidity in our population.
When reviewed retrospectively, five cancers diagnosed in the
second screening round were present on baseline CT, and all
were sub-5 mm solid nodules and therefore appropriately clas-
sified as negative in accordance with BTS guidelines .4 In all five
cases, the cancers were stage I when detected, although with
VDTs ranging from 51 to 163 days, there may have been a stage
shift if we had adopted biennial rather than annual screening.
This was also true for cancers that developed in individuals with
true negative baseline scans; the estimated mean VDT of 49 days
in this cohort suggests a more aggressive phenotype.
Figure 1 Diagram showing flow of participants through the screening service.LDCT,low-dose CT scan; MDT, multidisciplinary team.
3CrosbiePA, etal. Thorax 2018;0:1–5. doi:10.1136/thoraxjnl-2018-212547
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Brief communication
It is noteworthy that the proportion of attendees classified as
false positive was three times lower in the second round than
the first; the 3-month surveillance imaging rate was also 30%
lower. This may be a consequence of having the baseline CT as
a comparator; a similar finding was reported by the ITALUNG
study investigators and suggests that the risk of screen-related
harm may be greatest in the first round.8 Over both screening
rounds, the false-positive rate was higher than NELSON but
lower than other studies.1 8–10 In terms of baseline (T0) screening
performance, the service had a sensitivity of 89.4% and speci-
ficity 97.1%. This represents a slightly lower sensitivity (93.8%)
than NLST but a much improved specificity (73.4%).1
In conclusion, we have demonstrated that a targeted commu-
nity-based lung cancer screening programme, delivered within
the NHS, can engage those most at risk and detect a high propor-
tion of curable early stage lung cancers.
Author affiliations
1Manchester Thoracic Oncology Centre, Wythenshawe Hospital, Manchester
University NHS Foundation Trust, Manchester, UK
2Division of Molecular and Clinical Cancer Sciences, Faculty of Biology, Medicine and
Health, University of Manchester, Manchester, UK
3Manchester Clinical Commissioning Group, Macmillan Cancer Improvement
Partnership, Manchester, UK
4Manchester Health and Care Commissioning, Manchester, UK
5Greater Manchester, Lancashire, South Cumbria Strategic Clinical Network,
Manchester, UK
6Manchester City Council, Manchester, UK
7Department of Radiology, Royal Preston Hospital, Preston, UK
8Department of Radiology, Manchester Royal Infirmary, Manchester University NHS
Foundation Trust, Manchester, UK
9Department of Radiology, Royal Blackburn Hospital, Blackburn, UK
10The Black Health Agency, Manchester, UK
11Macmillan Cancer Support, Manchester, UK
12Department of Radiology, Papworth Hospital, Cambridge, UK
13Department of Radiology, Christie NHS Foundation Trust, Manchester, UK
14Department of Radiology, Salford Royal NHS Foundation Trust, Salford, UK
15Department of Radiology, Stockport NHS Foundation Trust, Stockport, UK
Acknowledgements The Macmillan Cancer Improvement Partnership facilitated
the design and development of the pilot. The service was delivered by the lung
cancer team at Wythenshawe Hospital, Manchester University NHS Foundation Trust,
in partnership with Alliance Medical. LDCT reporting was performed by a consortium
of NHS consultant radiologists with subspecialty interest in thoracic medicine. The
pilot service was commissioned by South Manchester Clinical Commissioning Group
on behalf of the three Manchester Clinical Commissioning Groups. Community
engagement was delivered by multiple members of the team and was led by MCIP
and the Manchester CCGs in conjunction with Manchester City Council, Macmillan
Cancer Support and BHA for Equality. This work was supported by the NIHR
Manchester Biomedical Research Centre.
Contributors Service concept: RB, PAC, PVB, AT, JT. Service development by
members of the Macmillan Cancer Improvement Partnership: JT, ZK, GH, CH, PVB,
MA, VB-B, JE, DM, JF, MS, AM, MO’L, RP, JP, LY, AT, PE, DC, ST, RB, PAC, ES, DK, BT, DC,
Table 2 Clinical details of screen detected lung cancers
T0 outcome Stage
VDT
(days) Final stage
Pathology
(subtype) Treatment
Indeterminate pT1a N0 369 IA Adenocarcinoma
(acinar)
Surgery
Indeterminate pT1a N0 148 IA Adenocarcinoma
(acinar)
Surgery
Indeterminate pT1a N0 89 IA Squamous Surgery
Indeterminate pT1a N0 687* IA Adenocarcinoma
(acinar 50%, solid 20%,
lepidic 30%)
Surgery
Indeterminate pT1a N0 206 IA Squamous Surgery
Indeterminate pT1a N0 285 IA Adenocarcinoma
(micropapillary 50%,
papillary 10%, lepidic 40%)
Surgery
Negative† pT1a N0 142 IA Adenocarcinoma
(solid 80%, acinar 20%)
Surgery
Negative cT1a N0 29‡ IA Clinical SABR
Negative† cT1a N0 163 IA Clinical SABR
Negative† cT1a N0 51 IA NSCLC (NOS) SABR
Negative cT1a N0 71§ IA Squamous SABR
Negative cT1a N0 67§ IA Clinical No treatment¶
Negative† cT1b N0 65 IA Clinical Radical radiotherapy
Negative pT2a N0 IB Adenocarcinoma
(solid 80%, lepidic 20%)
Surgery
Negative† cT2a N0 72 IB NSCLC (NOS) SABR
Negative cT1a N2 37‡ IIIA Squamous Chemoradiotherapy(S)
Negative pT1a N2 86§ IIIA Small cell Surgery/chemotherapy(A)
Negative cT4 N2 M1a 34‡ IV Small cell Chemoradiotherapy(S)
Negative cT3 N3 M1b 16‡ IV Small cell Chemoradiotherapy(S)
*Morphology of nodule changed with increasing density despite low VDT.
†False negative, (S)sequential treatment, (A)adjuvant chemotherapy.
‡Estimated VDT.
§VDT calculated between T1 and T1+3-month surveillance scans.
¶Hadchemoradiotherapy for oesophageal cancer.
NOS, not otherwise specified; NSCLC, non-small cell lung cancer; SABR, stereotactic ablative radiotherapy; VDT, volume doubling time.
4CrosbiePA, etal. Thorax 2018;0:1–5. doi:10.1136/thoraxjnl-2018-212547
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Brief communication
ST. Service operation and delivery by the Manchester University NHS Foundation Trust
lung cancer team: HB, ME, JL, TE, JK, SMan, AWal, RD, MG, RS, AS, ES, PVB, PAC, RB.
Radiology reporting by the radiology consortium: RD, MG, JH, KI, DK, SMel, TN, RS,
NJS, AS, ES, BT, AWat, JW. Analysis of data and drafting of manuscript: PAC, HB, ME,
JT, RB and guarantors of overall content: PAC, RB. Review, revision and agreement of
final manuscript: all authors.
Funding The pilot was supported by funding from Macmillan Cancer Support.
Competing interests None declared.
Patient consent Not required.
Provenance and peer review Not commissioned; externally peer reviewed.
Open access This is an open access article distributed in accordance with the
Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits
others to copy, redistribute, remix, transform and build upon this work for any
purpose, provided the original work is properly cited, a link to the licence is given,
and indication of whether changes were made. See: https:// creativecommons. org/
licenses/ by/ 4. 0/.
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... 3 However, despite widespread screening availability and public health insurance coverage, uptake has been reported to be as low as 2%. 4 5 In England, following the success of local initiatives, lung cancer screening implementation is expanding through the Targeted Lung Health Check (TLHC) programme. [6][7][8][9] The UK National Screening Committee recently recommended national adoption of lung cancer screening, using the TLHC model, following a favourable cost-effectiveness evaluation. 10 An important question for screening implementation is how best to identify and invite the target group. ...
... The previous Manchester LHC pilot saw 90% secondround adherence. 6 This was higher than the 83% observed in NEM-LHC, where the second round coincided with the COVID-19 pandemic in 2020. This may have discouraged adherence for a proportion of screenees, although subjective reasons for non-adherence were not captured systematically. ...
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Introduction: Although lung cancer screening is being implemented in the UK, there is uncertainty about the optimal invitation strategy. Here, we report participation in a community screening programme following a population-based invitation approach, examine factors associated with participation, and compare outcomes with hypothetical targeted invitations. Methods: Letters were sent to all individuals (age 55-80) registered with a general practice (n=35 practices) in North and East Manchester, inviting ever-smokers to attend a Lung Health Check (LHC). Attendees at higher risk (PLCOm2012NoRace score≥1.5%) were offered two rounds of annual low-dose CT screening. Primary care recorded smoking codes (live and historical) were used to model hypothetical targeted invitation approaches for comparison. Results: Letters were sent to 35 899 individuals, 71% from the most socioeconomically deprived quintile. Estimated response rate in ever-smokers was 49%; a lower response rate was associated with younger age, male sex, and primary care recorded current smoking status (adjOR 0.55 (95% CI 0.52 to 0.58), p<0.001). 83% of eligible respondents attended an LHC (n=8887/10 708). 51% were eligible for screening (n=4540/8887) of whom 98% had a baseline scan (n=4468/4540). Screening adherence was 83% (n=3488/4199) and lung cancer detection 3.2% (n=144) over 2 rounds. Modelled targeted approaches required 32%-48% fewer invitations, identified 94.6%-99.3% individuals eligible for screening, and included 97.1%-98.6% of screen-detected lung cancers. Discussion: Using a population-based invitation strategy, in an area of high socioeconomic deprivation, is effective and may increase screening accessibility. Due to limitations in primary care records, targeted approaches should incorporate historical smoking codes and individuals with absent smoking records.
... In addition to rurality, distance to travel for screening is a major factor in determining likelihood of screening [16]. Previous studies have determined associations between common rural factors such as poverty / distance to travel for screening and lower screening participation, making this an important area for potential intervention [17][18][19]. ...
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... 13 Previous studies have determined associations between common rural factors such as poverty / distance to travel for screening and lower screening participation, making this an important area for potential intervention. 14,15,16 Therefore, it is critical to better understand the current screening landscape in these at-risk populations in the Southeastern US. 17 . It will facilitate targeted interventions that will increase uptake, potentially improve survival while paying particular attention to inequalities in screening since it ultimately has the potential to exacerbate inequalities in lung cancer survival. ...
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Purpose : Low-dose computed tomography lung cancer screening is effective for reducing lung cancer mortality. It is critical to understand the lung cancer screening practices for screen-eligible individuals living in Alabama and Georgia where lung cancer is the leading cause of cancer death. High lung cancer incidence and mortality rates are attributed to high smoking rates among underserved, low income, and rural populations. Therefore, the purpose of this study: (1) to define sociodemographic and clinical characteristics of patients who were screened for lung cancer at an Academic Medical Center (AMC) in Alabama and a Safety Net Hospital (SNH) in Georgia. Methods: A retrospective cohort study of patient electronic health records who received lung cancer screening between 2015 to 2020 was performed to identify the study population and outcome variable measures. Chi-square tests and Student t-tests were used to compare screening uptake across patient demographic and clinical variables. Bivariate and multivariate logistic regressions determined significant predictors of lung cancer screening uptake. Results: At the AMC, 67,355 were identified as eligible for LCS and 1,129 were screened. In bivariate analyses, there were several differences between those who were screened and those who were not screened. Screening status in the site at Alabama varied significantly by age (P<0.01), race (P<0.001), marital status (P<0.01), smoking status (P<0.01) health insurance (P<0.01), median income (P<0.01), urban status (P<0.01) and distance from UAB (P<0.01). Those who were screened were more likely to have lesser comorbidities (2.31 vs. 2.53; P<0.001). At the SNH, 11,011 individuals were identified as screen-eligible and 500 were screened. In the site at Georgia, screening status varied significantly by race (P<0.01), health insurance (P<0.01), and distance from site (P<0.01). At the AMC, the odds of being screened increased significantly if the individual was a current smoker compared to former smoker (OR=3.21; P<0.01). At the SNH, the odds of being screened for lung cancer increased significantly with every unit increase in co-morbidity count (OR = 1.12; P=0.01) Conclusion: The study provides evidence that LCS has not reached all subgroups and that additional targeted efforts are needed to increase lung cancer screening uptake. Furthermore disparity was noticed between adults living closer to screening institutions and those who lived farther.
... The National Screening Committee has recommended population screening for lung cancer as targeted lung cancer screening with low-dose Computerised Tomography is cost-effective at a threshold of £20,000 per QALY [16,17]. Current attempts to improve early lung cancer diagnosis involve diagnostically evaluating large volumes of individuals with less than 1% of successful case identification [18,19]. The population of England is estimated to increase by 6% over the next decade [20]. ...
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Background Lung cancer has the poorest survival due to late diagnosis and there is no universal screening. Hence, early detection is crucial. Our objective was to develop a lung cancer risk prediction tool at a population level. Methods We used a large place-based linked data set from a local health system in southeast England which contained extensive information covering demographic, socioeconomic, lifestyle, health, and care service utilisation. We exploited the power of Machine Learning to derive risk scores using linear regression modelling. Tens of thousands of model runs were undertaken to identify attributes which predicted the risk of lung cancer. Results Initially, 16 attributes were identified. A final combination of seven attributes was chosen based on the number of cancers detected which formed the Kent & Medway lung cancer risk prediction tool. This was then compared with the criteria used in the wider Targeted Lung Health Checks programme. The prediction tool outperformed by detecting 822 cases compared to 581 by the lung check programme currently in operation. Conclusion We have demonstrated the useful application of Machine Learning in developing a risk score for lung cancer and discuss its clinical applicability.
... 16 The UK-based Targeted Lung Health Check (TLHC) program employs the PLCOm2012 model for selection into screening, with favourable interim results. 17,18 However, it is unknown whether the chosen 1.51% risk threshold, combined with the targeted age range of 55 to 74 years, represents the optimal strategy for other European countries. Moreover, there are no known estimates of the incremental harms and benefits of risk-based screening in the European setting, relative to PY-based criteria. ...
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Throughout Europe, computed tomography (CT) screening for lung cancer is in a phase of clinical implementation or reimbursement evaluation. To efficiently select individuals for screening, the use of lung cancer risk models has been suggested, but their incremental (cost‐)effectiveness relative to eligibility based on pack‐year criteria has not been thoroughly evaluated for a European setting. We evaluate the cost‐effectiveness of pack‐year and risk‐based screening (PLCOm2012 model‐based) strategies for Switzerland, which aided in informing the recommendations of the Swiss Cancer Screening Committee (CSC). We use the MISCAN (MIcrosimulation SCreening ANalysis)‐Lung model to estimate benefits and harms of screening among individuals born 1940 to 1979 in Switzerland. We evaluate 1512 strategies, differing in the age ranges employed for screening, the screening interval and the strictness of the smoking requirements. We estimate risk‐based strategies to be more cost‐effective than pack‐year‐based screening strategies. The most efficient strategy compliant with CSC recommendations is biennial screening for ever‐smokers aged 55 to 80 with a 1.6% PLCOm2012 risk. Relative to no screening this strategy is estimated to reduce lung cancer mortality by 11.0%, with estimated costs per Quality‐Adjusted Life‐Year (QALY) gained of €19 341, and a €1.990 billion 15‐year budget impact. Biennial screening ages 55 to 80 for those with 20 pack‐years shows a lower mortality reduction (10.5%) and higher cost per QALY gained (€20 869). Despite model uncertainties, our estimates suggest there may be cost‐effective screening policies for Switzerland. Risk‐based biennial screening ages 55 to 80 for those with ≥1.6% PLCOm2012 risk conforms to CSC recommendations and is estimated to be more efficient than pack‐year‐based alternatives.
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Incorporating susceptibility genetic variants of risk factors has been reported to enhance the risk prediction of polygenic risk score (PRS). However, it remains unclear whether this approach is effective for lung cancer. Hence, we aimed to construct a meta polygenic risk score (metaPRS) of lung cancer and assess its prediction of lung cancer risk and implication for risk stratification. Here, a total of 2180 genetic variants were used to develop nine PRSs for lung cancer, three PRSs for different histopathologic subtypes, and 17 PRSs for lung cancer‐related risk factors, respectively. These PRSs were then integrated into a metaPRS for lung cancer using the elastic‐net Cox regression model in the UK Biobank (N = 442,508). Furthermore, the predictive effects of the metaPRS were assessed in the prostate, lung, colorectal, and ovarian (PLCO) cancer screening trial (N = 108,665). The metaPRS was associated with lung cancer risk with a hazard ratio of 1.33 (95% confidence interval: 1.27–1.39) per standard deviation increased. The metaPRS showed the highest C‐index (0.580) compared with the previous nine PRSs (C‐index: 0.513–0.564) in PLCO. Besides, smokers in the intermediate risk group predicted by the clinical risk model (1.34%–1.51%) with the intermediate‐high genetic risk had a 6‐year average absolute lung cancer risk that exceeded the clinical risk model threshold (≥1.51%). The addition of metaPRS to the clinical risk model showed continuous net reclassification improvement (continuous NRI = 6.50%) in PLCO. These findings suggest the metaPRS can improve the predictive efficiency of lung cancer compared with the previous PRSs and refine risk stratification for lung cancer.
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Introduction Lung cancer (LC)-screening programs concern smokers at risk for cardiovascular diseases (CVDs) and chronic obstructive pulmonary disease (COPD). The LUMASCAN study aimed to evaluate the acceptability and feasibility of screening for these 3 diseases in a community population with centralized organization and to determine low-dose computed tomography (LDCT) markers associated with each disease. Methods This cohort enrolled subjects meeting NCCN criteria (v1.2014) in an organized LC-screening program including LDCT-scans, spirometry, evaluations of coronary artery calcifications (CACs), and a smoking-cessation plan at inclusion, 1 and 2-year, then telephone follow-up. Outcomes were the participation rate and the proportion of participants affected by LC, obstructive lung disease (OLD) or CVD events. Logistic-regression models were used to identify radiological factors associated with each disease. Results Between 2016 and 2019, 302 subjects were enrolled: 61% men, median age 58.8 years, 77% active smoker, 11% diabetes, 38% hypertension, 27% taking lipid-lowering agents. Inclusion, 1-year and 2-year participation rate were 99%, 81%, 79%, respectively. After a median follow-up of 5.81 years, screenings detected 12 (4%) LCs, 9/12 via LDCT (78% localized) and 3/12 during follow-up (all stage IV), 83 (27%) unknown OLD, and 131 (43.4%) moderate/severe CACs warranting a cardiology consultation. Preexisting COPD and moderate/severe CACs were associated with major CVD events with odds ratios of 1.98 [95% confident interval (CI) 1.00-3.88] and 3.27 [95% CI 1.72-6.43] respectively. Conclusion The LUMASCAN study demonstrated the feasibility of combined screening for LC, COPD and CVD in a community population. Its centralized organization enabled high participation and coordination of care providers.
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of Key Points Eligibility criteria for lung cancer screening increasingly need to consider family history of lung cancer, as well as age and smoking status. Lung cancer screening will reveal a multitude of incidental findings, of variable clinical significance, and with a need for clear pathways of management. Pulmonary nodule sampling is enhanced by intra‐procedural imaging and cutting‐edge robotic technology. Systematic thoracic lymph node sampling has implications for treatment efficacy. Bronchoscopic ablative techniques are feasible for peripheral lung cancers. Bronchoscopic sampling continues to have a high yield for lung cancer molecular characterization. Immunotherapy indications have expanded to include early stage and resectable lung cancer.
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This guideline is based on a comprehensive review of the literature on pulmonary nodules and expert opinion. Although the management pathway for the majority of nodules detected is straightforward it is sometimes more complex and this is helped by the inclusion of detailed and specific recommendations and the 4 management algorithms below. The Guideline Development Group (GDG) wanted to highlight the new research evidence which has led to significant changes in management recommendations from previously published guidelines. These include the use of two malignancy prediction calculators (section ‘Initial assessment of the probability of malignancy in pulmonary nodules’, algorithm 1) to better characterise risk of malignancy. There are recommendations for a higher nodule size threshold for follow-up (≥5 mm or ≥80 mm3) and a reduction of the follow-up period to 1 year for solid pulmonary nodules; both of these will reduce the number of follow-up CT scans (sections ‘Initial assessment of the probability of malignancy in pulmonary nodules’ and ‘Imaging follow-up’, algorithms 1 and 2). Volumetry is recommended as the preferred measurement method and there are recommendations for the management of nodules with extended volume doubling times (section ‘Imaging follow-up’, algorithm 2). Acknowledging the good prognosis of sub-solid nodules (SSNs), there are recommendations for less aggressive options for their management (section ‘Management of SSNs’, algorithm 3). The guidelines provide more clarity in the use of further imaging, with ordinal scale reporting for PET-CT recommended to facilitate incorporation into risk models (section ‘Further imaging in management of pulmonary nodules’) and more clarity about the place of biopsy (section ‘Non-imaging tests and non-surgical biopsy’, algorithm 4). There are recommendations for the threshold for treatment without histological confirmation (sections ‘Surgical excision biopsy’ and ‘Non-surgical treatment without pathological confirmation of malignancy’, algorithm 4). Finally, and possibly most importantly, there are evidence-based recommendations about the information that people …
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Introduction: Recruitment and nodule management are critical issues of lung cancer screening with low-dose computed tomography (LDCT). We report subjects' compliance and results of LDCT screening and management protocol in the active arm of the ITALUNG trial. Methods: Three thousand two hundred six smokers or former smokers invited by mail were randomized to receive four annual LDCT (n = 1613) or usual care (n = 1593). Management protocol included follow-up LDCT, 2-[18F]fluoro-2-deoxy-D glucose positron emission tomography (FDG-PET), and CT-guided fine-needle aspiration biopsy (FNAB). Results: One thousand four hundred six subjects (87%) underwent baseline LDCT, and 1263 (79%) completed four screening rounds. LDCT was positive in 30.3% of the subjects at baseline and 15.8% subsequently. Twenty-one lung tumors in 20 subjects (1.5% detection) were found at baseline, and 20 lung tumors in 18 subjects (0.5% detection) in subsequent screening rounds. Ten of 18 prevalent (55%) and 13 of 17 incident (76%) non-small-cell cancers were in stage I. Interval growth enabled diagnosis of lung cancer in 16 subjects (42%), but at least one follow-up LDCT was obtained in 741 subjects (52.7%) over the screening period. FDG-PET obtained in 6.5% of subjects had 84% sensitivity and 90% specificity for malignant lesions. FNAB obtained in 2.4% of subjects showed 90% sensitivity and 88% specificity. Positivity of both FDG-PET and FNAB invariably predicted malignancy. Surgery for benign lesions was performed on four subjects (10% of procedures) but followed protocol violations on three subjects. Conclusions: High-risk subjects recruited by mail who entered LDCT screening showed a high and stable compliance. Efficacy of screening is, however, weakened by low detection rate and specificity. Adhesion to management protocol might lessen surgery for benign lesions.
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The National Lung Screening Trial (NLST) used risk factors for lung cancer (e.g., ≥30 pack-years of smoking and <15 years since quitting) as selection criteria for lung-cancer screening. Use of an accurate model that incorporates additional risk factors to select persons for screening may identify more persons who have lung cancer or in whom lung cancer will develop. We modified the 2011 lung-cancer risk-prediction model from our Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial to ensure applicability to NLST data; risk was the probability of a diagnosis of lung cancer during the 6-year study period. We developed and validated the model (PLCO(M2012)) with data from the 80,375 persons in the PLCO control and intervention groups who had ever smoked. Discrimination (area under the receiver-operating-characteristic curve [AUC]) and calibration were assessed. In the validation data set, 14,144 of 37,332 persons (37.9%) met NLST criteria. For comparison, 14,144 highest-risk persons were considered positive (eligible for screening) according to PLCO(M2012) criteria. We compared the accuracy of PLCO(M2012) criteria with NLST criteria to detect lung cancer. Cox models were used to evaluate whether the reduction in mortality among 53,202 persons undergoing low-dose computed tomographic screening in the NLST differed according to risk. The AUC was 0.803 in the development data set and 0.797 in the validation data set. As compared with NLST criteria, PLCO(M2012) criteria had improved sensitivity (83.0% vs. 71.1%, P<0.001) and positive predictive value (4.0% vs. 3.4%, P=0.01), without loss of specificity (62.9% and. 62.7%, respectively; P=0.54); 41.3% fewer lung cancers were missed. The NLST screening effect did not vary according to PLCO(M2012) risk (P=0.61 for interaction). The use of the PLCO(M2012) model was more sensitive than the NLST criteria for lung-cancer detection.
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The International Staging Committee (ISC) of the International Association for the Study of Lung Cancer (IASLC) collected 68,463 patients with nonsmall cell lung cancer and 13,032 patients with small cell lung cancer, registered or diagnosed from 1990 to 2000, whose records had adequate information for analyzing the tumor, node, metastasis (TNM) classification. The T, N, and M descriptors were analyzed, and recommendations for changes in the seventh edition of the TNM classification were proposed based on differences in survival. For the T component, tumor size was found to have prognostic relevance, and its analysis led to recommendations to subclassify T1 tumors into T1a (< or = 2 cm) and T1b (>2 - < or = 3 cm) and T2 tumors into T2a (>3 - < or = 5 cm) and T2b (>5 - < or = 7 cm), and to reclassify T2 tumors > 7 cm into T3. Furthermore, with additional nodules in the same lobe as the primary tumors, T4 tumors would be reclassified as T3; with additional nodules in another ipsilateral lobe, M1 as T4; and with pleural dissemination, T4 as M1. There were no changes in the N category. In the M category, M1 was recommended to be subclassified into M1a (contralateral lung nodules and pleural dissemination) and M1b (distant metastasis). The proposed changes for the new stage grouping were to upstage T2bN0M0 from stage IB to stage IIA, and to downstage T2aN1M0 from stage IIB to stage IIA and T4N0-N1M0 from stage IIIB to stage IIIA. The proposed changes better differentiate tumors of different prognoses.
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We report baseline results of a community-based, targeted, low-dose CT (LDCT) lung cancer screening pilot in deprived areas of Manchester. Ever smokers, aged 55–74 years, were invited to ‘lung health checks’ (LHCs) next to local shopping centres, with immediate access to LDCT for those at high risk (6-year risk ≥1.51%, PLCOM2012 calculator). 75% of attendees (n=1893/2541) were ranked in the lowest deprivation quintile; 56% were high risk and of 1384 individuals screened, 3% (95% CI 2.3% to 4.1%) had lung cancer (80% early stage) of whom 65% had surgical resection. Taking lung cancer screening into communities, with an LHC approach, is effective and engages populations in deprived areas.
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The efficacy and cost-effectiveness of low-dose spiral computed tomography (LDCT) screening in heavy smokers is currently under evaluation worldwide. Our screening program started with a pilot study on 1035 volunteers in Milan in 2000 and was followed up in 2005 by a randomized trial comparing annual or biennial LDCT with observation, named Multicentric Italian Lung Detection. This included 4099 participants, 1723 randomized to the control group, 1186 to biennial LDCT screening, and 1190 to annual LDCT screening. Follow-up was stopped in November 2011, with 9901 person-years for the pilot study and 17 621 person-years for Multicentric Italian Lung Detection. Forty-nine lung cancers were detected by LDCT (20 in biennial and 29 in the annual arm), of which 17 were identified at baseline examination; 63% were of stage I and 84% were surgically resectable. Stage distribution and resection rates were similar in the two LDCT arms. The cumulative 5-year lung cancer incidence rate was 311/100 000 in the control group, 457 in the biennial, and 620 in the annual LDCT group (P=0.036); lung cancer mortality rates were 109, 109, and 216/100 000 (P=0.21), and total mortality rates were 310, 363, and 558/100 000, respectively (P=0.13). Total mortality in the pilot study was similar to that observed in the annual LDCT arm at 5 years. There was no evidence of a protective effect of annual or biennial LDCT screening. Furthermore, a meta-analysis of the four published randomized trials showed similar overall mortality in the LDCT arms compared with the control arm.
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Each year in the United Kingdom over 35 000 people die from lung cancer, 4000 more than from breast and bowel cancer combined,1 and survival remains lower than in other developed countries.2 Inequality exists in the UK in the delivery of treatment with curative intent3 as well as in delivery of active treatments generally. All healthcare professionals involved at any stage of the care pathway have important roles to play in tackling these inequalities. Thus the 2005 guidance from the National Institute for Health and Clinical Excellence (NICE) on the diagnosis and treatment of lung cancer was updated to advise healthcare professionals of important advances in management and to ensure patients have a supported, informed choice of the treatment that will help them most. This article summarises the recommendations from the updated NICE guideline on the diagnosis and treatment of lung cancer.4 NICE recommendations are based on systematic reviews of best available evidence and explicit consideration of cost effectiveness. When minimal evidence is available, recommendations are based on the Guideline Development Group’s experience and opinion of what constitutes good practice. Evidence levels for the recommendations are given in italic in square brackets. ### Early diagnosis and referral #### Referral (recommendations retained from 2005)