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. 2026 Oct 5;12(5):00351-2026. doi: 10.1183/23120541.00351-2026

Ever-smokers in Norway and lung cancer: median time from self-reported smoking debut to lung cancer diagnosis in 11 prospective population studies (CONOR)

Olav Toai Duc Nguyen 1,2, Ioannis Fotopoulos 3, Ioannis Tsamardinos 3,4,5, Vincenzo Lagani 6,7, Oluf Dimitri Røe 1,2,8,✉
PMCID: PMC13636103  PMID: 42835565

Abstract

Background

Tobacco smoking patterns and lung cancer incidence are closely related, but with years of lag. Most smokers start smoking as teenagers, and lung cancer is diagnosed at a median age of 70 years. However, the median lag time between smoking consumption and lung cancer incidence and smoking-related mortality is commonly reported to be up to 40 years. Here we investigate the median lag time from smoking debut to lung cancer diagnosis in Norway.

Methods

We used the Cohort of Norway (CONOR), consisting of linked data from 11 Norwegian prospective population-based cohorts (n=180 534). The study included 80 761 ever-smokers, where 1336 developed lung cancer. Median follow-up time from inclusion in the CONOR study was 11.9 years (0.0–20.8 years) and follow-up from self-reported smoking debut was 44.2 years (2.7–85.4 years). The time from smoking initiation to lung cancer diagnosis was calculated for all cases.

Results

The median age of lung cancer diagnosis is 72.5 years. The mean and median time from smoking debut to lung cancer diagnosis are 51.9 (30.2–69.1) and 53.3 years, respectively. The median time from smoking debut until lung cancer diagnosis is >40 years (p<0.001). There is a shorter median lag time in women compared to men and in current smokers compared to former smokers, 48.6 versus 55.5 years and 50.7 versus 54.2 years, respectively (p<0.001).

Conclusion

The latency between smoking debut and lung cancer diagnosis in Norwegian ever-smokers is much longer than what has previously been reported. Women and current smokers have a shorter time to diagnosis than men and former smokers, respectively. This is important knowledge in the planning of future healthcare, lung cancer screening, and prevention measures.

Shareable abstract

The latency between smoking debut and lung cancer diagnosis in Norwegian ever-smokers is much longer than what has previously been reported, and time to diagnosis in women and current smokers is shorter compared to men and former smokers, respectively https://bit.ly/4e64HDv

Introduction

Lung cancer takes more lives than any other cancer type worldwide, [1] and smoking tobacco is the main etiological factor in lung cancer development [2]. Despite decades of policies and campaigns to mitigate the tobacco epidemic, the absolute number of people smoking in the world is increasing, from 0.99 billion in 1990 to 1.14 billion in 2019 [3].

The smoking prevalence in Norway among people in the 16 to 79 years age group has changed radically in the last 50 years [4]. As of 2025, the proportion of daily smokers aged 16–79 years in Norway had dropped to 7% in both men and women, from 52% and 32% in 1973, respectively [4]. The numbers have dropped steadily since 1998 [4]. Furthermore, the prevalence of occasional smokers aged 16–79 years in Norway in 1973 was 9% and 10% among men and women, respectively. In 2025, these numbers have remained about the same being 10% and 7% in men and women, respectively [4]. Among young adults aged 16–24 years the percentage of daily smokers has dropped from 14% to 1% in the last 15 years [4]. However, the fall in numbers of occasional smokers among this group appears to be levelling off and even showing signs of increasing [4, 5]. In 2025, 21% of young adults aged 16–24 years reported occasional smoking [4].

Social inequality is the main determinant factor for prediction of smoking prevalence in Norway [6]. There is difference in smoking prevalence in Norway between the lower educated compared to the higher educated groups [5].

In 2024, a total of 3435 new lung cancer cases were diagnosed in Norway, 1700 of which were among men and 1735 among women [7]. The age-standardised incidence rate of lung cancer in Norway is 54.6 and 50.2 per 100 000 person-years in men and women, respectively [7]. The annual number of new lung cancer cases among men and women has been equal since 2018 [6]. Projections suggest an increase in the absolute incidence of lung cancer in Norway over the coming decade before subsequently declining, partly due to demographic changes with an increasingly aging population [6]. The median age at lung cancer diagnosis is 73 years in Norway [6, 7].

Lung cancer incidence is often closely related to tobacco smoking pattern in a dose–response manner, but with several decades of lag time [8, 9]. Lag time spread has commonly been reported to be between 8 and 40 years from initiation of smoking to diagnosis of lung cancer or smoking-related mortality [8–13]. However, given the fact that most ever-smokers historically start smoking in their teenage years [14–16] and the median age at lung cancer diagnosis is about 70 years, [17] one would expect a longer lag time than what has been reported so far. The precise lag time between smoking initiation and lung cancer diagnosis will inform epidemiologists, preventive health workers, health economists and politicians better to design preventive measures and screening and calculate the real cost of a continued tobacco epidemic.

Norway has several large, high-quality, prospective population studies that include data on smoke initiation, smoking behaviour and pack-years. Moreover, Norway has had a complete National Cancer Registry since 1951. In the present work, we investigate the median lag time from smoking debut to lung cancer diagnosis in Norway.

Materials and methods

All participants were from CONOR (Cohort of Norway), a pan-Norwegian prospective population study. CONOR is a cohort of 11 prospective studies based on a prospective population-based study design, including 180 534 individuals over the age of 19 years with extensive clinical data collected at the time of enrolment [18–20]. The participants are from various parts of Norway, both rural and urban [19]. The data were collected between 1994 and 2008 [21]. There was no double counting in the results across the 11 studies. Each survey used the same set of 50 CONOR questions that were agreed upon before the first CONOR survey in Tromsø in 1994, including questions about smoking [21]. The precise wording of the CONOR questions can be found on the Norwegian Institute of Public Health website [21]. Most of these 50 questions did not differ in the wording across the studies. The dataset from CONOR contains several questions on smoking that are identical across all studies, except one question regarding daily smoking. This question varied in the different studies, and a new variable, based on the different questions, has been produced, resulting in a common smoking variable that is valid for all CONOR surveys [22].

The analysis included only ever-smokers with key data (sex, age, time of starting smoking and cessation data, see table 1) (n=80 770). From these key data we calculated different smoking-related variables, such as “years since smoking debut until inclusion”; “years of smoking”; “quit time in years” and “median age from smoking debut to lung cancer” (table 1). An ever-smoker is defined as someone who replied positively to the question “Smoke daily now or ever?”, while those who responded negatively to this question were classified as never-smokers. Missing values are present in the data (n=15 344) (supplementary table S1). Never-smokers (n=99 764), those who developed lung cancer before initiating smoking (n=3) and those who began smoking after inclusion in CONOR (n=6) (figure 1) were excluded. Lung cancer diagnosis dates were identified through the Norwegian Cancer Registry. We identified ever-smokers who developed lung cancer over the entire prospective follow-up period as well as those who developed lung cancer before inclusion in the study since the main aim was time from smoking debut to lung cancer diagnosis. Thus, follow-up time was defined as the period from self-reported smoking debut to lung cancer diagnosis or to the end of the follow-up being lung cancer free. Lung cancer cases were identified using the International Classification of Diseases (ICD) code 162.1 and ICD-10 codes C34.0–C34.9. Individuals who developed other cancers were not excluded.

TABLE 1.

Descriptive statistics of the CONOR study population at inclusion

Variables All No lung cancer Lung cancer p-value
Sex, n 80 761 79 425 1336 <0.001
 Female 39 046 38 585 461
 Male 41 715 40 840 875
Age at inclusion, years, mean±sd, range 50.9±14.5,
19.3–97.2		 50.6±14.4,
19.3–97.2		 64.5±10.4,
32.0–87.2		 <0.001
Age at smoking start, years, mean±sd, 95% CI 18.8±5.0,
(13–32)		 18.8±5.0,
(13–32)		 18.9±4.8,
(13–30)		 0.584
Years since smoking debut until inclusion, mean±sd, range 32.1±13.7,
0.3–89.6		 31.8±13.6,
0.3–89.6		 45.6±10.2
6.3–68.8		 <0.001
Years of smoking, mean±sd, (95% CI) 22.4±12.5,
(3.0–52.0)		 22.1±12.3,
(3.0–51.0)		 39.0±12.7,
(13.0–60.0)		 <0.001
Quit time, years, mean±sd, (95% CI) 7.7±10.8,
(0–36)		 7.8±10.8,
(0–36)		 4.8±9.2,
(0–30)		 <0.001
Follow- up time from smoking debut Smoking debut to lung cancer free follow-up years Smoking debut to lung cancer diagnosis years
Female, mean±sd, (95% CI) 42.2±11.4,
(22.3–66.3)# 		47.9±9.8,
(27.4–65.0)# 		<0.001
Male, mean±sd, (95% CI) 46.3±13.3,
(22.7–70.0)# 		54.0±9.6,
(32.3–69.7)# 		<0.001
Both sexes, mean±sd, (95% CI) 44.3±12.6,
(22.5–68.5)# 		51.9±10.1,
(30.2–69.1)# 		<0.001
Female Male Both sexes
Age from smoking debut to lung cancer, years, median (95% CI) 48.6
(27.4–65.0)# 		55.5
(32.3–69.7)# 		53.3
(30.2–69.1)# 		<0.001
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All participants were ever-smokers. #: follow-up time includes time from self-reported smoking debut to either lung cancer diagnosis or lung cancer-free survival.

FIGURE 1.

FIGURE 1

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Consort flow diagram for inclusion. #: the median total follow-up time, including time of self-reported smoking debut, is 44.2 years (2.7–85.4 years).

Ethics

In accordance with the Helsinki Declaration, all participants in the CONOR gave their written consent. All studies were approved by the Norwegian Data Inspectorate and the Regional Committees for Medical Research Ethics.

Statistical analysis

Missing data were handled using multiple imputation by chained equations (MICE) [23]. A total of 200 imputed datasets were generated across five bootstrapping iterations to ensure stable convergence of the imputation procedure. Each dataset was completed separately and subsequently combined into a single augmented dataset by aggregating imputed values across datasets using the median operation. This approach enhances robustness against outliers while incorporating information from multiple imputations. Descriptive statistical analysis aimed to assess differences in key variables between ever-smokers who developed lung cancer (cases) and those who did not (controls) (table 1). This is to assess whether the key risk variables for lung cancer were significantly altered in the ever-smokers that developed lung cancer compared to the controls. The time from smoking initiation to lung cancer diagnosis was calculated in all cases (figure 1). For categorical variables such as sex, chi-square tests were used to evaluate the statistical significance of differences in the distribution of categories between individuals who developed lung cancer and controls. For the continuous variables, we applied two-sided unpaired t-tests to measure any statistically significant differences in the average values between individuals who developed lung cancer and controls. The computation of the 95% confidence intervals (CI) was based on the 2.5% and 97.5% quantile ranges. The Wilcoxon Signed Rank test was performed to assess whether the median time for developing lung cancer from smoking debut is higher than the upper limit of 40 years reported in the literature. The level of statistical significance was set to p<0.05. In addition, we conducted the nonparametric log-rank test to assess the association with lag time from smoking debut to lung cancer diagnosis across sex, different pack-years groups (<10, 10–19, <20, 20–29, 20–39, 30–39, and ≥40 pack-years) and current and former smokers. One pack-year is defined as smoking 20 cigarettes per day for a year. Also, we implemented three parametric Cox-regression analyses independently to evaluate whether there is a strong effect of the following variables: i) smoke start age, ii) smoke stop time, and iii) smoke years against time to lung cancer diagnosis. Smoke years is defined as the time from smoking debut until smoking cessation, lung cancer diagnosis or to the end of the follow-up being lung cancer free. R version 4.2.1 (23 June 2022; www.r-project.org) was used for all analyses.

Results

Association of lag time from smoking debut to lung cancer diagnosis

The dataset included 80 761 ever-smokers, 1336 (1.68%) of whom developed lung cancer during the follow-up period (figure 2). The median follow-up time from inclusion in the study was 11.9 years (0.0–20.8 years) with a total of 1 000 983 person-years. The median age of lung cancer diagnosis was 72.5 years (figure 2). The mean time and median time from smoking debut to lung cancer diagnosis was 51.9 years (95% CI 30.2–69.1; range 17.3–73.6 years) and 53.3 years (95% CI 30.2–69.1), respectively (table 1 and supplementary table S1). The median time from smoking debut until lung cancer diagnosis was >40 years across all samples and was statistically significant (p<0.001). Time to lung cancer development was significantly longer for men than for women with a median time of 55.5 years (95% CI 32.3–69.7) and 48.6 years (95% CI 27.4–65.0), respectively (p<0.001) (table 1). The same was observed between former and current smokers, irrespective of sex, with a mean time of 54.2 (range 17.3–72.9) and 50.7 years (range 17.4–73.6) (p<0.001), respectively (supplementary table S1 and figure S1). The mean time to lung cancer development from smoking debut in former and current smokers was 56.2 versus 52.7 (p<0.001) in males and 49.4 versus 47.3 years (p=0.034) in females, respectively (supplementary table S1 and figure S1).

FIGURE 2.

FIGURE 2

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The distribution of age of smoking debut and the respective age of lung cancer diagnosis. The data are retrieved from 80 761 ever-smokers in the 11 datasets of the prospective CONOR population in Norway, where 1336 developed lung cancer during their lifetime or follow-up. The y-axis depicts percentages of 50 2-year age bins.

Age at inclusion, sex, smoking years and quit time were significantly different in the population that developed lung cancer versus those that did not develop lung cancer. In contrast, “age at smoking start” did not show statistically significant differences.

Association of lung cancer risk

Results from the survival analysis underlined that the chances of developing lung cancer increase 1) the later one quits smoking (p<0.001) and 2) the longer one smokes (p<0.001) (supplementary table S3). Furthermore, the survival analysis also showed that the difference in lag time from smoking debut to lung cancer diagnosis is significantly associated with sex (p<0.001) (supplementary table S4). Smoking intensity measured as pack-years was also significantly associated with lag time overall (p<0.001), but when analysed separately the association was only observed among females (p=0.03) (supplementary tables S5 and S6). There was a significant difference in lag time from smoking debut to diagnosis of lung cancer in former versus current smokers, irrespective of sex (supplementary table S2 and figure S1); the same was observed between sexes, irrespective of smoking status (supplementary table S7 and figure S2).

Discussion

The deleterious long-term effects of smoking are well known; however, the lag time from smoking debut to lung cancer in ever-smokers, independent of smoking intensity, has not been reported. The present study of 11 Norwegian prospective population studies with personal data from >80 000 ever-smokers shows that the median lag time from starting smoking to diagnosis of lung cancer is 53 years.

The numbers of tobacco and cigarette users are increasing around the world despite tobacco control efforts [3]. Norway has for decades implemented strong measures against smoking and a complete ban on indoor smoking in public places since 2004. Still, >90% of lung cancer cases in Norway develop in people who have ever smoked [18], and the rate of occasional smoking in young adults in Norway aged 16–24 years is higher today than in 1973 [24]. To target the young generations and the older people that smoke, and to predict impact on health and expenditure, it is important to have the facts right, among them the lag time from smoking debut to lung cancer diagnosis.

Lag time from smoking debut to lung cancer diagnosis

The lag time detected in this study is significantly higher than what is reported in the literature so far. Lag time from smoking debut to lung cancer diagnosis or smoking-related mortality is commonly reported to be between 20 and 40 years [8, 9, 11, 13], even down to 8 years [12]. Previously reported lag times do not reflect the fact that the common age of smoking debut is in the teenage years [14, 15], and the median age at lung cancer diagnosis is in the range of 60–74 years [25]. The present study supports this assumption with a median time of >50 years from smoking debut to lung cancer diagnosis. In these granulated prospective population studies, the lag time from smoking debut to lung cancer diagnosis ranged from 17.3 to 73.6 years. The minimum number of years is close to the previously reported median of 20 years [8, 9] and the maximum is >70 years, which has not been reported previously. This difference from previous studies might be because many of these reports are based on modelling from historical data of smoking consumption along with lung cancer prevalence, or estimated based on national population average data, and not detailed data on an individual level. Furthermore, several of the studies used lung cancer mortality data and not lung cancer incidence data, leaving the estimation of lag time between smoking exposure and lung cancer diagnosis less precise [9, 11]. The differences could also be due to different life-time exposures of other lung cancer risk factors (e.g. asbestos, air pollution, second-hand smoking, radon, etc.) in combination with smoking. Some might argue that Norwegian smoking patterns are very different from other countries; however, the median age at diagnosis in Norway is similar to comparable Western countries, e.g. 71 years in the USA [17], 74 years in the UK [26], 70 years in Sweden [27] and Germany [28], and 69 years in Austria [29]. Furthermore, the median age of smoking debut in Norway (teenage years) is similar to that in the USA and across Europe [15, 16]. These facts align with our findings of a median lag time of around 50 years from smoking debut to lung cancer diagnosis.

Lag time and smoking status

We also observed a longer lag time between smoking exposure and lung cancer diagnosis of about 4 years among former smokers compared to current smokers, irrespective of sex. This is consistent with evidence that current smokers have a significantly higher risk of developing lung cancer at a younger age compared to former smokers [30].

Lag time and sex

Our results indicate that there is a shorter time to lung cancer development in women compared to men, irrespective of former or current smoking status. Our study showed a sex difference where women had a significantly shorter median lag time of 6.9 years (48.6 versus 55.5 years in men). This is the opposite of what has been reported in the literature, where it has been estimated that there is a 14 years longer lag time between tobacco consumption and lung cancer incidence in Norwegian women compared to men (31 and 17 years lag time, respectively) [10]. Others have also reported longer lag time between cigarette smoking and lung cancer mortality for women compared to men [10, 31]. However, all these studies have several limitations since they lack individual data on smoking start, end and intensity, and are either based on modelling from historical data or estimated based on national population average data, and not data on an individual level. In contrast, this study is based on a large population with granulated data on smoking start and stop age with a very long follow-up time where any smoking intensity is included. It might be the reason for the opposite results observed, since the lag time can be affected by several different factors such as age of smoking debut, smoking duration, type of cigarette product and histological subtypes of lung cancer [10] – information that should be available from data on an individual level.

Our results are more in line with previous studies reporting that females are more susceptible to smoking-related early lung cancer development compared to men [32, 33]. Interestingly, we also found differences in lag time from smoking debut to diagnosis of lung cancer and smoking intensity measured as pack-years overall (p<0.001), with a significant association observed among females (p=0.03), but not among males (p=0.1). Nevertheless, it is still debatable which sex is more susceptible to smoking-related lung cancer development, since other reports show that men have a higher risk for lung cancer compared to women [32, 34].

Association of lung cancer risk

This study showed that the chances of developing lung cancer increase the later one quits smoking and the longer one smokes, whereas age of smoking debut was not independently associated with lung cancer in the present cohort. The first two results correlate with previous reports [35–37], while the latter may reflect the stronger contribution of cumulative smoking exposure, including smoking intensity and duration, to lung cancer risk [37–40].

Regarding the study population characteristics (table 1), they reflected the known relationship of higher lung cancer risk to higher age, longer smoking duration and shorter smoking cessation time.

Strengths and limitations

The study has several strengths: 1) Norway has several unique prospective health studies, including the HUNT study, the Tromsø Study and the Oslo Study, totalling 11 studies with high-quality data such as age at smoke initiation, smoking habits, smoking duration and date of lung cancer diagnosis for each individual, which gives a granulated and correct estimation of the lag time, in contrast to most other studies; 2) as these 11 studies included in CONOR are from most geographical regions of Norway, both urban and rural, they represent the whole population, including indigenous Sami people and immigrants [20]; and 3) the large sample size of CONOR, the long follow-up period and prospectively collected clinical data make the findings statistically robust [20].

A few limitations of this study should be noted. 1) The smoking history data in CONOR is self-reported making the data potentially inaccurate. 2) The material is based only on residents of Norway, which may limit the applicability to other populations. 3) Exposures and environmental conditions can change during the follow-up time, making baseline measurements less accurate over long periods. In CONOR, smoking-related information was only available at baseline; therefore we were unable to account for changes in smoking behaviour during follow-up, which may lead to some degree of exposure misclassification. Consequently, in our analysis we assume that all participants maintained a consistent smoking behaviour throughout the entire duration of their smoking history. This assumption was also applied in the calculation of pack-years. However, lung cancer risk is strongly associated with smoking duration and time since smoking debut [38–40]. The data in CONOR allowed us to estimate the lag time from smoking debut to lung cancer diagnosis, which was the main focus of this study. At the time of inclusion, most ever-smokers had already had a history of several decades of smoking exposure, and while continued smoking during follow-up does contribute additional risk, ever-smokers remain at increased risk of lung cancer compared with never-smokers, even after smoking cessation [35]. 4) The required data on never-smokers were not available in our dataset, preventing us from conducting similar analyses in this group.

The results from this study provide important information regarding projecting future smoking-related diseases and mortality in a population. This essential knowledge can help health authorities to predict the future health impact of smoking on a population level and thereby plan for future healthcare including screening and tobacco control efforts.

Conclusion

Understanding the latency between smoking and lung cancer incidence is essential for effective public health interventions, policy formulation, healthcare planning and individual risk assessment. This should include ever-smokers of any smoking intensity. This study shows that the latency between smoking debut and lung cancer development is significantly longer and with a larger range than what has previously been reported. Moreover, there is a significantly shorter time from smoking debut to lung cancer development in women compared to men, and in current smokers compared to former smokers. These findings should be taken into account when planning future healthcare, prevention measures and estimation of the cost of not preventing smoking. These findings underscore the long-term consequences of smoking and why public health efforts to prevent teenage smoking are so important.

Acknowledgements

We are grateful to all participants in the CONOR study.

Footnotes

Provenance: Submitted article, peer reviewed.

Ethics statement: All studies were approved by the Norwegian Data Inspectorate and the Regional Committees for Medical Research Ethics.

Author contributors: All authors had full access to all the data in the study and had final responsibility for the decision to submit for publication. O.T.D. Nguyen: conceptualisation, investigation, writing (original draft, review and editing) and visualization. I. Fotopoulos: formal analysis, validation, data curation, writing (review and editing) and visualisation. I. Tsamardinos and V. Lagani: methodology and writing (review and editing). O.D. Røe: conceptualisation, methodology, investigation, writing (original draft, review and editing), visualisation, supervision and project administration.

Conflict of interest: None declared.

Support statement: We are thankful for the funding and support of the Central Norway Regional Health Authority, the Norwegian University of Science and Technology, and Levanger Hospital, Nord-Trøndelag Hospital Trust. The funding sources had no role in study conception, design, interpretation of the data, writing of the report or decision to submit the paper for publication. Funding information for this article has been deposited with the Open Funder Registry.

References

  • 1.Ferlay J, Colombet M, Soerjomataram I, et al. Cancer statistics for the year 2020: an overview. Int J Cancer 2021; 149: 778–789. doi: 10.1002/ijc.33588 [DOI] [PubMed] [Google Scholar]
  • 2.O'Keeffe LM, Taylor G, Huxley RR, et al. Smoking as a risk factor for lung cancer in women and men: a systematic review and meta-analysis. BMJ Open 2018; 8: e021611. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3. GBD 2019 Tobacco Collaborators. Spatial, temporal, and demographic patterns in prevalence of smoking tobacco use and attributable disease burden in 204 countries and territories, 1990–2019: a systematic analysis from the Global Burden of Disease Study 2019. Lancet 2021; 397: 2337–2360. doi: 10.1016/S0140-6736(21)01169-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Statistics Norway . Statistics on tobacco, alcohol and other drugs. Smoking. 05307: Percentage smokers (16-79 years), by age, year and sex 1973-2025. Date last updated: 23 October 2025. Date last accessed: 4 February 2026. Oslo, Statistics Norway, 2025. www.ssb.no/en/statbank/table/05307 [Google Scholar]
  • 5.Brustugun OT, Grønberg BH, Aanerud M, et al. Lung Cancer in Norway. J Thorac Oncol 2025; 20: 839–846. doi: 10.1016/j.jtho.2025.03.046 [DOI] [PubMed] [Google Scholar]
  • 6. Vedøy TF. Sosial ulikhet i bruk av tobakk. Folkehelseinstituttet, 2023. Date last accessed: 4 February 2026. Date last updated: 12 April 2023. www.fhi.no/le/royking/tobakkinorge/bruk-av-tobakk/royking-og-sosial-ulikhet/ [Google Scholar]
  • 7.Cancer Registry of Norway . Cancer in Norway 2024 – Cancer Incidence, Mortality, Survival and Prevalence in Norway. Oslo, Cancer Registry of Norway, 2025. [Google Scholar]
  • 8.Alberg AJ, Samet JM. Epidemiology of lung cancer. Chest 2003; 123: Suppl. 1, 21s–49s. doi: 10.1378/chest.123.1_suppl.21S [DOI] [PubMed] [Google Scholar]
  • 9.Islami F, Torre LA, Jemal A. Global trends of lung cancer mortality and smoking prevalence. Transl Lung Cancer Res 2015; 4: 327–338. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Chen J. A comparative analysis of lung cancer incidence and tobacco consumption in Canada, Norway and Sweden: a population-based study. Int J Environ Res Public Health 2023; 20: 6930. doi: 10.3390/ijerph20206930 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Guerra-Tort C, López-Vizcaíno E, Santiago-Pérez MI, et al. Time dependence between tobacco consumption and lung cancer mortality in Spain. Arch Bronconeumol 2004; 60: Suppl. 2, S31–S37. doi: 10.1016/j.arbres.2024.05.028 [DOI] [PubMed] [Google Scholar]
  • 12.Kafle RC, Kim DY, Holt MM. Gender-specific trends in cigarette smoking and lung cancer incidence: a two-stage age-stratified Bayesian joinpoint model. Cancer Epidemiol 2023; 84: 102364. doi: 10.1016/j.canep.2023.102364 [DOI] [PubMed] [Google Scholar]
  • 13.Weiss W. Cigarette smoking and lung cancer trends. A light at the end of the tunnel? Chest 1997; 111: 1414–1416. doi: 10.1378/chest.111.5.1414 [DOI] [PubMed] [Google Scholar]
  • 14.Barrington-Trimis JL, Braymiller JL, Unger JB, et al. Trends in the age of cigarette smoking initiation among young adults in the US from 2002 to 2018. JAMA Network Open 2020; 3: e2019022-e. doi: 10.1001/jamanetworkopen.2020.19022 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Reitsma MB, Flor LS, Mullany EC, et al. Spatial, temporal, and demographic patterns in prevalence of smoking tobacco use and initiation among young people in 204 countries and territories, 1990–2019. Lancet Public Health 2021; 6: e472–ee81. doi: 10.1016/S2468-2667(21)00102-X [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Marcon A, Pesce G, Calciano L, et al. Trends in smoking initiation in Europe over 40 years: a retrospective cohort study. PLoS One 2018; 13: e0201881. doi: 10.1371/journal.pone.0201881 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.National Cancer Institute . Cancer Stat Facts: lung and bronchus cancer. Bethesda, MD, National Cancer Institute, 2024. Date last accessed: 4 February 2026. https://seer.cancer.gov/statfacts/html/lungb.html [Google Scholar]
  • 18.Markaki M, Tsamardinos I, Langhammer A, et al. A validated clinical risk prediction model for lung cancer in smokers of all ages and exposure types: a HUNT study. EBioMedicine 2018; 31: 36–46. doi: 10.1016/j.ebiom.2018.03.027 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Naess O, Søgaard AJ, Arnesen E, et al. Cohort profile: cohort of Norway (CONOR). Int J Epidemiol 2008; 37: 481–485. doi: 10.1093/ije/dym217 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Nguyen OTD, Fotopoulos I, Markaki M, et al. Improving lung cancer screening selection: the HUNT lung cancer risk model for ever-smokers versus the NELSON and 2021 United States preventive services task force criteria in the cohort of Norway: a population-based prospective study. JTO Clin Res Rep 2024; 5: 100660. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Norwegian Institute of Public Health . About CONOR – data from several regional health studies. Oslo, Norwegian Institute of Public Health, 2016. Date last updated: 14 June 2016. Date last accessed: 4 February 2026. www.fhi.no/en/hs/conor/about-conor---data-from-several-regional-health-studies/ [Google Scholar]
  • 22.Norwegian Institute of Public Health . Documentation of the CONOR file. Oslo, Norwegian Institute of Public Health, 2012. www.fhi.no/globalassets/dokumenterfiler/studier/conor/documentation-of-the-conor-file.pdf [Google Scholar]
  • 23.van Buuren S, Groothuis-Oudshoorn K. mice: Multivariate Imputation by Chained Equations in R. J Statist Softw 2011; 45: 1–67. [Google Scholar]
  • 24.Vedøy TFSG. Utbredelse av røyking i Norge. Folkehelseinstituttet, 2023. Date last updated: 12 April 2023. Date last accessed: 4 February 2026. www.fhi.no/le/royking/tobakkinorge/bruk-av-tobakk/utbredelse-av-royking-i-norge/ [Google Scholar]
  • 25.Zahed H, Feng X, Sheikh M, et al. Age at diagnosis for lung, colon, breast and prostate cancers: an international comparative study. Int J Cancer 2024; 154: 28–40. doi: 10.1002/ijc.34671 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.National Lung Cancer Audit; National Cancer Audit Collaborating Centre . National Lung Cancer Audit: State of the Nation 2025. London, National Cancer Audit Collaborating Centre, 2025. www.natcan.org.uk/wp-content/uploads/2025/07/NLCA-State-of-the-Nation-Report-2025_V2.0.pdf [Google Scholar]
  • 27.Ekman S, Horvat P, Rosenlund M, et al. Epidemiology and survival outcomes for patients with NSCLC in Scandinavia in the preimmunotherapy Era: a SCAN-LEAF retrospective analysis from the I-O optimise initiative. JTO Clin Res Rep 2021; 2: 100165. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Frost N, Griesinger F, Hoffmann H, et al. Lung Cancer in Germany. J Thorac Oncol 2022; 17: 742–750. doi: 10.1016/j.jtho.2022.03.010 [DOI] [PubMed] [Google Scholar]
  • 29.Wass RE, Lamprecht B. Lung cancer in Austria: epidemiology and demographic trends as a basis for early detection strategies. Memo 2026; 19: 18–21. doi: 10.1007/s12254-025-01092-x [DOI] [Google Scholar]
  • 30.Campling BG, Ye Z, Lai Y, et al. Disparity in age at lung cancer diagnosis between current and former smokers. J Cancer Res Clin Oncol 2019; 145: 1243–1251. doi: 10.1007/s00432-019-02875-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Adair T, Hoy D, Dettrick Z, et al. Reconstruction of long-term tobacco consumption trends in Australia and their relationship to lung cancer mortality. Cancer Causes Control 2011; 22: 1047–1053. [DOI] [PubMed] [Google Scholar]
  • 32.Gee K, Yendamuri S. Lung cancer in females—sex-based differences from males in epidemiology, biology, and outcomes: a narrative review. Transl Lung Cancer Res 2024; 13: 163–178. doi: 10.21037/tlcr-23-744 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Hansen MS, Licaj I, Braaten T, et al. Sex differences in risk of smoking-associated lung cancer: results from a cohort of 600 000 Norwegians. Am J Epidemiol 2018; 187: 971–981. [DOI] [PubMed] [Google Scholar]
  • 34.Yu Y, Liu H, Zheng S, et al. Gender susceptibility for cigarette smoking-attributable lung cancer: a systematic review and meta-analysis. Lung Cancer 2014; 85: 351–360. doi: 10.1016/j.lungcan.2014.07.004 [DOI] [PubMed] [Google Scholar]
  • 35.Tindle HA, Stevenson Duncan M, Greevy RA, et al. Lifetime smoking history and risk of lung cancer: results from the Framingham Heart Study. J Natl Cancer Instit 2018; 110: 1201–1207. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Khuder SA, Mutgi AB. Effect of smoking cessation on major histologic types of lung cancer. Chest 2001; 120: 1577–1583. [DOI] [PubMed] [Google Scholar]
  • 37.Peto R, Darby S, Deo H, et al. Smoking, smoking cessation, and lung cancer in the UK since 1950: combination of national statistics with two case–control studies. BMJ 2000; 321: 323–329. doi: 10.1136/bmj.321.7257.323 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Remen T, Pintos J, Abrahamowicz M, et al. Risk of lung cancer in relation to various metrics of smoking history: a case–control study in Montreal. BMC Cancer 2018; 18: 1275. doi: 10.1186/s12885-018-5144-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Lubin JH, Caporaso NE. Cigarette smoking and lung cancer: modeling total exposure and intensity. Cancer Epidemiol Biomarkers Prev 2006; 15: 517–523. doi: 10.1158/1055-9965.EPI-05-0863 [DOI] [PubMed] [Google Scholar]
  • 40.Doll R, Peto R. Cigarette smoking and bronchial carcinoma: dose and time relationships among regular smokers and lifelong non-smokers. J Epidemiol Community Health (1978) 1978; 32: 303–313. doi: 10.1136/jech.32.4.303 [DOI] [PMC free article] [PubMed] [Google Scholar]

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