Pack-Years as a Stable Predictor of Cancer Incidence and Mortality: A Prospective Cohort Study from the UK Biobank

Pack-Years as a Stable Predictor of Cancer Incidence and Mortality: A Prospective Cohort Study from the UK Biobank | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Pack-Years as a Stable Predictor of Cancer Incidence and Mortality: A Prospective Cohort Study from the UK Biobank Jiaojiao Liao, Zhaoyu Wang, Yu Liu, Zhaoji Li, Hui Wang, Liyuan Tao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5760852/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background To clarify the dose-response relationship between cigarette smoking and the risk of developing or dying from multiple site-specific cancers. Methods We prospectively analyzed baseline smoking pack-years in relation to cancer incidence and mortality in the UK Biobank, with data obtained from national cancer registries. Using a competing risk model, we assessed the associations between smoking pack-years and cancer outcomes, adjusting for age, gender, ethnicity, BMI, SES, drinking habits, and family cancer history. Results The study involved 336,885 individuals with a mean age of 55.9 years (SD 8.07), 53% of whom were female. There were 33,099 (9.8%) current smokers with an average of 27.16 (SD 18.38) pack-years and 87,241 (25.9%) former smokers with an average of 21.36 (SD 18.24) pack-years. Over a median follow-up of 13.93 years, 36,964 cancer events and 11,931 cancer deaths were recorded. The incidence and mortality risks of overall cancers increased linearly with smoking pack-years. Each additional pack-year increased the risk of all cancers by 0.9% (HR = 1.009, 95% CI = 1.008–1.009) and smoking-related cancers by 1.7% (HR = 1.017, 95% CI = 1.017–1.018). Cancer mortality rose by 1.5% per pack-year (HR = 1.015, 95% CI = 1.015–1.016), particularly in lung, bladder, esophageal, liver, and stomach cancers, with HRs ranging from 1.010 to 1.028. The study highlights the linear relationship between smoking pack-years and cancer risk, especially for smoking-related cancers. However, some cancers showed no significant correlation or an opposite effect. Conclusion Pack-years of smoking provide a linear representation of smoking’s impact on cancer incidence and mortality, significantly affecting various malignancies, particularly smoking-related ones. smoking cancer pack-years incidence mortality Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Worldwide, the burden of cancer incidence and mortality is increasing rapidly [ 1 ] . Cancer remains a leading cause of death and an important barrier to increasing life expectancy in every country around the world [ 2 ] . For individuals, a cancer diagnosis represents a stressful life event [ 3 ] . Tobacco smoke can increases the risk of cancer through its content of carcinogens, such as nitrosamines, polycyclic aromatic hydrocarbons, acrylamides, volatile organics, and cadmium [ 4 ] . While cigarette smoking among U.S. adults has declined over the past five decades, in 2021, 18.7% (an estimated 46.0 million) of U.S. adults were still current users of any tobacco product [ 5 ] . Smoking is associated with the development of many kinds of cancers [ 6 , 7 ] . Lung cancer is the leading cause of cancer death globally, while cigarette smoking is the most prevalent lung cancer risk factor [ 8 ] . A meta-analysis showed that the risk of lung cancer mortality rose with pack-years, and less than 60 pack-years presented relative risks (RRs) below 10 in Chinese population [ 9 ] . In addition to lung cancer, smoking has been shown to increase the risk of dying of cancer of the oropharynx, pancreas, bladder, esophagus, stomach, liver, kidney and cervix [ 10 ] . Kelvin et al. conducted a meta-analysis of 28 prospective cohort studies containing 1,463,796 subjects from America, Europe, and Asia, showing that smokers carried a higher colorectal cancer risk than never smokers [ 11 ] . Although cigarette smoking is generally associated with a lower incidence of melanoma, Jackson et al. found that current smokers had an increased risk of melanoma-associated death (MAD) compared with former or nonsmokers with a hazard ratio (HR) of 1.48 [ 12 ] . Besides, the amount of smoking reported was associated with increased MAD risk, with an HR of 1.63 (95% CI, 1.33–2.01) for heavy smokers and 1.48 (95% CI, 1.13–1.93) for moderate smokers. The incidence of multiple myeloma did not seem to be associated with tobacco smoking [ 13 ] . Fircanis proved that cigarette smoking was a significant risk factor for the development of acute myeloid leukemia in adults [ 14 ] . While smoking is associated with the development of numerous cancers, certain cancers, such as prostate cancer (PCa), lack a clearly established correlation with smoking in terms of incidence or mortality. Some studies have reported a lower risk of PCa for smokers [ 15 , 16 ] , while a Mendelian randomization study found no such association [ 17 ] . In addition to exploring whether smoking is related to the incidence and mortality of cancers, it is also crucial to accurately depict the quantitative relationship between smoking dosage and the risk of cancers occurrence and death. Currently, measures of smoking exposure include the number of cigarettes smoked per day, the smoking duration, and pack-years. However, it is still unclear which indicator is more accurate for measuring cumulative exposure to smoking, particularly in relation to different health outcomes. In prior research, pack-years are commonly classified into distinct categories for analysis as a categorical variable [ 7 , 18 ] to examine the dose-response relationship between smoking and cancer development or death. The quantitative analysis can better reflect the cumulative harm of smoking exposure. However, how to measure the cumulative exposure continuously and quantitatively to smoking remains a significant scientific challenge. In-depth research is needed to assess the linear relationship between cumulative smoking exposure and the incidence and mortality of various cancers. Therefore, the aim of this study was to quantitatively describe the dose-response relationship between smoking and cancer risk using the UK Biobank database, and to investigate the impact of smoking on the incidence and mortality risk of overall cancer and 19 specific cancers. Methods Study design and participants This was a prospective cohort study using the UK Biobank database, which was a substantial population-based longitudinal study. Launched in 2006, the UK Biobank project collected biological specimens, health data, and lifestyle details systematically from a large group of approximately 500,000 committed volunteers throughout the United Kingdom [ 19 ] . The research received approval from the Northwest Multi-center Research Ethics Committee (reference 21/NW/0157). All participants gave their written informed consent when they enrolled initially. Further details about the UK Biobank have been documented in earlier publications [ 20 – 22 ] . The national cancer registries were also used in this study, which provides information on cancer occurrence and mortality. A total of 502,421 subjects aged 40 to 72 years were evaluated for eligibility of inclusion. After an exclusion of participants with baseline cancers (n = 23,753), newly diagnosed non-melanoma skin cancer or benign cases (n = 34,121), and those with missing data on outcomes, exposures, smoking status, lifestyle measurement, and covariates, 336,885 participants were included in the final analysis (Fig. 1 ). This study adhered to the guidelines outlined in the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting framework. Assessment of exposures Pack years of smoking was a synthetic continuous variable generated based on smoking status and history which was self-reported trough a questionnaire at baseline. The following questions were asked to determine the smoking status of former smokers: "How old were you when you first started smoking on most days?"; "About how many cigarettes did you smoke on average each day? "; "How old were you when you last smoked on most days?". The general definition of pack year [ 23 ] is the number of cigarettes smoked per day, divided by twenty, multiplied by the number of years of smoking. The number of years of smoking is calculated by subtracting the age of starting smoking from the age smoking was stopped. Assessment of outcomes Cancer cases and deaths due to cancer were determined through a linkage to the national cancer registries that included date of diagnosis, date of death, and the primary cause of death and was updated to June 1st, 2022. Diagnostic information of malignant cancers was derived using ICD-10 codes C00-C97, with an exclusion of non-melanoma skin cancer coded as C44. Participants who were diagnosed with any type of malignant cancer during follow-up were defined as cancer cases, otherwise they were followed up until end of the study period or censoring. Smoking-related cancers subtype was defined according to The Health Consequences of Smoking − 50 Years of Progress - A Report of the Surgeon General [ 24 ] and included the following cancers: oropharynx, larynx, esophagus, trachea/bronchus/lung, acute myeloid leukemia, stomach, liver, pancreas, kidney/ureter, cervix, bladder, and colorectal. Cancer death was defined if the primary cause of death was malignant cancer. If the primary cause of death was not cancer, the death was defined as a competing risk event. Measurements of sociodemographic and covariates Touchscreen questionnaire was administered at recruitment, in which information on socioeconomic status (SES) and lifestyle factors were collected. Individual SES was defined based on a latent classification analysis of household income, education qualifications, and employment status (Appendix Table 3). The participants were divided into high, medium, or low SES groups based on individual SES. In our study, BMI and alcohol consumption were assessed and were representative of lifestyle. BMI was calculated as weight in kg divided by squared height in meter and categorized into four groups of < 18.5, 18.5–24.9, 25.0-29.9, and ≥ 30 kg/m 2 . A BMI of 18.5–24.9 kg/m 2 was considered as a "healthy" BMI. According to the UK guidelines, drinking habits were categorized into safe, hazardous, and harmful consumption levels [ 25 ] . In this study, no alcohol use or safe consumption level were defined as healthy drinking. The codes used to delineate the variables were provided in Appendix Table 2. Other covariates were also obtained through questionnaires, including age at recruitment, gender, ethnicity, family history of cancer, and history of cancer screening. Ethnicity was categorized into five groups: White, mixed, Asian, or Asian British, Black or Black British, and other ethnic groups. We only consider the cancer screenings for breast cancer, colorectal cancer, prostate cancer, and cervical cancer. Statistical analysis Baseline characteristics of the participants were described by the mean (standard deviation [SD]) or median (interquartile range, IQR) for continuous variables and proportions for categorical variables according to smoking status groups. Latent classification analysis was applied on household income, education, and employment status to group the SES [ 26 ] using R package “poLCA”. We treated pack-years of cigarettes smoking as a continuous variable and used a competing risk model to evaluate the Hazard Ratios (HRs) associated with each additional pack-year on cancer incidence and mortality, adjusting for covariates including age, gender, ethnicity, BMI, SES, alcohol consumption status, and family history of cancer. In the analysis of cancer incidence, participants were followed from the time of enrollment until the date of their last follow-up, loss to follow-up, cancer diagnosis, or death, whichever came first, and deaths without cancer occurrence were considered as competing events for the cancer incidence outcome. For mortality analysis, follow-up time began at enrollment and ended at the last follow-up, loss to follow-up, or death. Deaths due to other non-cancer causes were considered as competing risk factors [ 27 ] for cancer mortality. For specific cancer types, we only examined the associations of smoking pack-years with the incidence and mortality of those with a substantial case number exceeding 100. We employed the Cox proportional hazards model to analyze the association between pack-years of smoking and the incidence and mortality risk of all cancers, stratified by smoking status. In Cox proportional hazards regression, the variable of continuous smoking pack-years was modeled using restricted cubic splines to allow a nonlinear association with the hazard of over cancer, smoking related cancer or non-smoking related cancer incidence and mortality, presented graphically. Several sensitivity analyses were conducted. Initially, participants who reported being current or former smoker but had a smoking pack-year of zero were excluded from the analysis. A COX proportional risk model was then applied to assess the association between pack-years of smoking and the risks of overall cancer incidence and mortality. Following this, competing risk model was used to separately evaluate the impact of pack-years on cancer risk and mortality among current and former smokers. Secondly, within the entire cohort, we utilized the Cox proportional hazards model instead of the competing risk model to analyze the impact of pack-years of smoking on the incidence and mortality risk of overall cancer. This analysis was performed separately across all participants, current smokers, and former smokers. Besides, we analyzed the risk of cancer incidence and death in each gender subgroup and age subgroup using a competing risk model. All tests were considered statistically significant at a two-tailed p-value of less than 0.05. Results Characteristics of the study population A total of 336,885 participants aged 55.90 ± 8.07 constituted the study cohort, with a median cancer incidence follow-up time was 13.93 (IQR, 13.05–14.70) years, while the median follow-up time of cancer mortality was 14.06 (IQR, 13.32–14.77) years. Among all participants, 178,682 (53.0%) were female and the majority were White (95.2%). At baseline, the average cigarettes smoking of the participants was 8.20 pack-years, and 33,099 (9.8%) continued to smoke, 87,241 (25.9%) reported that they had quit smoking, 216,545 (64.3%) remained as never smokers. During the follow-up, a total of 36,964 participants (11.0%) developed cancer, among which 11,931 (3.5%) died due to cancer. As shown in Table 1 , participants who had quit smoking were more likely to be older, be male, have a higher BMI, have a higher SES, have unhealthy drinking habits, have a family history of cancer, compared to the participants who continued to smoke. Table 1 Baseline Characteristics by Smoking Status at Baseline (N = 336885) Characteristics Total population (N = 336885) Current (N = 33099) Former (N = 87241) Never (N = 216545) P Pack-years, mean (SD) 8.20 (15.58) 27.16 (18.38) 21.36 (18.24) 0 (0) < 0.001 Age, mean (SD), y 55.90 (8.07) 54.30 (8.06) 57.99 (7.61) 55.29 (8.10) < 0.001 Female, n (%) 178682 (53.0) 15578 (47.1) 40013 (45.9) 123091 (56.8) < 0.001 Ethnic, n (%) < 0.001 White 320698 (95.2) 31465 (95.1) 85201 (97.7) 204032 (94.2) Mixed 1899 (0.6) 362 (1.1) 451 (0.5) 1086 (0.5) Asian or Asian British 5855 (1.8) 446 (1.3) 526 (0.6) 4883 (2.3) Black or Black British 4841 (1.4) 485 (1.5) 478 (0.5) 3878 (1.8) Other ethnic 3592 (1.1) 341 (1.0) 585 (0.7) 2666 (1.2) BMI group, n (%) < 0.001 Normal 110735 (32.9) 11922 (36.0) 21895 (25.1) 76918 (35.5) Underweight 1720 (0.5) 388 (1.2) 209 (0.2) 1123 (0.5) Over weight 143147 (42.5) 13517 (40.8) 39173 (44.9) 90457 (41.8) Obesity 81283 (24.1) 7272 (22.0) 25964 (29.8) 48047 (22.2) SES < 0.001 High SES 111366 (33.1) 6887 (20.8) 24430 (28.0) 80049 (37.0) Medium SES 155534 (46.2) 15476 (46.8) 41047 (47.1) 99011 (45.7) Low SES 69985 (20.8) 10736 (32.4) 21764 (24.9) 37485 (17.3) Healthy drinking, n (%) 141695 (42.1) 18811 (56.8) 43358 (49.7) 79526 (36.7) < 0.001 Family history of cancer, n (%) 120944 (35.9) 11608 (35.1) 33161 (38.0) 76175 (35.2) < 0.001 All cancer cases, n (%) 36964 (11.0) 4791 (14.5) 11663 (13.4) 20510 (9.5) < 0.001 All cancer death, n (%) 11931 (3.5) 5372 (16.2) 4166 (4.8) 2393 (1.1) < 0.001 Cigarettes smoking and cancer incidence According to the competitive risk models, compared to never smokers, the risk of developing cancer increased by 0.9% for each additional pack-year smoked (HR = 1.009, 95% CI = 1.008–1.009, P < .001). For smoking-related cancers, the risk increased by 1.7% per pack-year (HR = 1.017, 95% CI = 1.017–1.018, P < .001). For non-smoking-related cancers, the HR for cancer incidence was 0.998 (95% CI, 0.997–0.999) for each additional pack-year of smoking exposure. Figure 2 A showed that the risk of cancer incidence in the study subjects continuously increased with the accumulation of smoking pack-years; the risk for those who were still smoking at baseline was higher than for those who had quit smoking (Fig. 2 A). The order of cancer risk from highest to lowest was smoking-related cancers, all cancers, and non-smoking related cancers (Fig. 3 A). The incidence risk of 9 site-specific smoking-related cancers increases with cumulative pack-years of smoking (Fig. 5 ), with the hazard ratio (HR) per pack-year ranging from 1.006 to 1.028 (Fig. 4 ). For nine types of smoking-related cancers, the risk of developing cancer increased rapidly with the number of pack-years for those smoking less than 30 pack-years. However, beyond 30 pack-years, the rate of risk increase slowed down (excluding lung cancer) (Fig. 5 ). For individual cancers, smoking (pack-years) significantly increases the risk of developing of 10 site-specific cancers, listed the top three from highest to lowest HR: lung (HR = 1.028, 95%CI, 1.026–1.030, P < .001), esophageal (HR = 1.014, 95%CI, 1.012–1.016, P < .001), bladder (HR = 1.014, 95%CI, 1.011–1.016, P < .001) cancers. Smoking (pack-years) is inversely associated with the occurrence of melanoma, prostate cancer, uterine cancer, and multiple myeloma. There is insufficient evidence to link smoking (pack-years) with the occurrence of brain cancer, thyroid cancer, non-Hodgkin lymphoma, lymphoid leukemia, or ovarian cancer (Fig. 4 ). Cigarettes smoking and cancer mortality Regarding cancer mortality, the overall cancer mortality for those who were still smoking at baseline was higher than for those who had quit smoking (Fig. 2 B). The order of cancer risk from highest to lowest was smoking-related cancers, all cancers, and non-smoking related cancers (Fig. 3 B). Cigarettes smoking (pack-years) can increase the risk of death from overall cancers (HR = 1.015, 95%CI, 1.015–1.016, P < .001), smoking-related cancers (HR = 1.019, 95%CI, 1.018–1.020, P < .001), and non-smoking-related cancers (HR = 1.002, 95%CI, 0.999–1.004, P = 0.150), as illustrated in Fig. 4 . For individual cancers, each additional pack-year of smoking increases the risk of death for 10 site-specific cancers, listed the top three from highest to lowest HR: lung cancer (HR = 1.028, 95%CI, 1.026–1.030, P < .001), bladder cancer (HR = 1.015, 95%CI, 1.012–1.019, P < .001), esophageal cancer (HR = 1.014, 95%CI, 1.012–1.017, P < .001). However, smoking (pack-years) is inversely associated with the risk of death from uterine cancer (HR = 0.981, 95%CI, 0.964–0.997, P = 0.024). As shown in Fig. 6 , the mortality risk for nine types of smoking-related cancers increased steadily with the number of cumulative pack-years. Within the range of 0–30 pack-years, the increase was more rapid, while beyond 30 pack-years, the rate of increase slowed down. Sensitivity and subgroup analyses consistently demonstrated that both the risk of cancer and mortality rates rise with an increase in smoking pack-years, with a HR of 1.009. Notably, current smokers face higher risks of both cancer and mortality compared to former smokers (Appendix Table 1). In the subgroup analysis, the risks for overall cancer incidence and mortality were higher in females (Incidence: Female, HR = 1.012, 95%CI, 1.011–1.013, P < .001; Male, HR = 1.007, 95%CI, 1.006–1.008, P < .001. Mortality: Female, HR = 1.019, 95%CI, 1.019–1.020, P < .001; Male, HR = 1.013, 95%CI, 1.013–1.014, P < .001). The risk of cancer occurrence varied among different age groups ( P 60 (HR = 1.007, 95% CI, 1.007–1.008). The risk of tumor-related mortality also differed among age groups, with the highest risk in the ≤ 50 age group (HR = 1.020, 95% CI, 1.016–1.023), followed by the 50–60 age group (HR = 1.018, 95% CI, 1.016–1.019), and the lowest in those aged > 60 (HR = 1.014, 95% CI, 1.013–1.015). Discussion Smoking significantly increases the risk of developing and dying from malignant cancers. Overall, compared to non-smokers, the risk of cancer incidence and mortality among smokers increases in an approximately linear fashion with cumulative pack-years of smoking. For each additional pack-year, the risk of developing malignant cancers increases by about 0.9%, and the risk of dying from malignant cancers increases by about 1.5%. For example, a person who smokes one pack per day for 20 years has a 1.196 times higher risk of developing malignant cancers (about 20% increase) and a 1.349 times higher risk of dying from malignant cancers (about 35% increase) compared to a non-smoker. Furthermore, the HRs for overall cancer incidence and mortality were generally higher in men than in women, is consistent with the results of another study [ 7 ] . This study innovatively analyzed the association between pack-years of smoking and the incidence and mortality of cancers by treating pack-years as a continuous variable. In previous research, Chan et al. [ 7 ] divided subjects into smokers and non-smokers. They found that, compared to non-smokers, smokers had a hazard ratio (HR) of 2.40 (95% CI: 2.22–2.59) for developing lung cancer. Park et al. [ 28 ] demonstrated that the lung cancer incidence HRs for former smokers versus never smokers were 1.27 (95% CI: 1.23–1.33) for men and 1.43 (95% CI: 1.16–1.81) for women. Our study showed that each additional pack-year of smoking increased the risk of developing lung cancer, with an HR of 1.028 (95% CI: 1.026–1.030), and the HR for lung cancer mortality was also 1.028 (95% CI: 1.026–1.030). In our study, the average number of pack-years among smokers was 22.9, resulting in an average HR of 1.88. The differences in HR values might have been attributed to variations in the study populations. Consistent with our findings, a large prospective cohort study conducted by Chan et al. in China indicated that ever-smoking was associated with statistically significant higher risks of 14 cancers, including esophageal cancer, stomach cancer, liver cancer, laryngeal cancer, lung cancer, and bladder cancer, among others. For the nine types of smoking-related cancers analyzed in this study, the relationship between smoking and cancer incidence and mortality is well-established [ 29 ] and positively correlated with cumulative pack-years of smoking [ 14 ] . Lung cancer shows the highest increase in incidence risk per pack-year, followed by esophageal cancer, bladder cancer, stomach cancer, liver cancer, myeloid leukemia, pancreatic cancer, colorectal cancer, and kidney cancer. Regarding mortality risk, lung cancer is the highest, followed by bladder cancer, esophageal cancer, liver cancer, stomach cancer, kidney cancer, pancreatic cancer, colorectal cancer, and myeloid leukemia. Our findings are consistent with previous research. In our study, the association between myeloid leukemia mortality risk and pack-years of smoking was not statistically significant. Lauseker et al. [ 30 ] found that, in chronic myeloid leukemia (CML) patients, the 8-year survival probability was 87% for non-smokers and 83% for smokers, with smokers having a 2.08 times higher risk of death and a 2.11 times higher risk of disease progression. However, in CML patients treated with first line imatinib, 8-year overall survival probabilities exceeded 80%, and many deaths were due to causes unrelated to CML [ 31 ] . For non-smoking-related cancers, the overall incidence risk has an HR of 0.998 (95% CI: 0.997–0.999), and the overall mortality risk has an HR of 1.002 (95% CI: 0.999–1.004). Specifically, smoking is inversely associated with the incidence risk of melanoma, multiple myeloma, uterine cancer, and prostate cancer (HR 1), and these associations are statistically significant. We find that smoking is a risk factor for the incidence and mortality of breast cancer, consistent with some findings [ 32 , 33 ] . A meta-analysis showed that breast cancer risk increased linearly with intensity of smoking (cigarettes/day). However, our study found that the incidence and mortality risk of breast cancer increased linearly with the number of pack-years of smoking. A Mendelian randomization study by Park [ 34 ] provided supportive evidence for a potential causal association with breast cancer risk for lifetime smoking exposure but not cigarettes per day among smokers, which was consistent with our findings. Similar to our findings, previous studies have reported an inverse relationship between smoking and the incidence of melanoma [ 35 , 36 ] , though not statistically significant. Our study, however, shows a statistically significant negative correlation ( P < 0.001). This might be misleading as we did not adjust for sun exposure. Most studies suggest that there is no statistically significant association between smoking and the incidence of multiple myeloma [ 13 ] . In this study, however, smoking is found to be negatively correlated with the occurrence of multiple myeloma, although smoking does not significantly increase the risk of death from multiple myeloma among smokers. The inverse association between smoking (pack-years) and multiple myeloma might be due to unmeasured confounding factors. There is an inverse relationship between smoking and the development of endometrial carcinoma [ 37 – 39 ] and prostate cancer [ 4 , 17 , 40 ] , and our study provides new evidence supporting this association. While smoking is positively associated with prostate cancer mortality (HR = 1.003, 0.999–1.007, P = 0.120). Although this association is not statistically significant, it is increasingly clear that smoking may be associated with prostate cancer. A meta-analysis showed that smokers were 24% more likely than nonsmokers to die from prostate cancer [ 41 ] . The study has several strengths. First, the analysis is based on the UK Biobank database and the national cancer registries, which provide a large sample size and accurate data recording. Second, we analyzed pack-years of smoking as a continuous variable, revealing a stable linear relationship between the risk of cancer incidence and mortality and pack-years of smoking. Third, we employed various statistical analysis methods, including competing risk models, to ensure the robustness of our findings. Fourth, this study comprehensively analyzes nine smoking-related and ten non-smoking-related cancers, examining the incidence and mortality impacts of smoking on these cancers separately. This study also has several limitations. First, because the smoking status of the study subjects was collected at baseline, the smoking status during the period from enrollment to the outcome occurrence was unknown. Therefore, the cumulative pack-years of smoking for current smokers were inaccurate and underestimated, which could weaken the observed associations between smoking and cancer incidence and mortality. Second, a primary drawback was the sub-optimal control for variables that affect melanoma outcomes, specifically UV exposure history, skin type, and history of blistering sunburns. Third, this study only analyzed the association between smoking exposure and cancer, without examining the impact of smoking cessation on cancer. This gap highlights an area for future research to address. Conclusion The incidence and mortality risk of cancer increase in an approximately linear manner with the number of pack-years of smoking. In addition to WHO-defined smoking-related cancers, smoking also elevates the incidence and mortality risk of various non-smoking-related cancers. Although smoking is inversely correlated with the incidence of melanoma and prostate cancer, it promotes their progression and increases the mortality risk for these patients. Therefore, smoking cessation is strongly recommended. Declarations Data Availability statement The data underlying this article are available in UK Biobank, at https://www.ukbiobank.ac.uk/. Any data analysis scripts that generated the results must also be made available. Author contributions Jiaojiao Liao, MS (Conceptualization; Formal analysis; Investigation; Methodology; Project administration; Writing—original draft; Writing—review & editing), Zhaoyu Wang, MS (Conceptualization; Methodology; Writing—original draft; Writing—review & editing), Yu Liu, PhD (Conceptualization; Methodology; Writing—review & editing), Zhaoji Li, MS (Writing—original draft; Writing—review & editing), Hui Wang, MS (Writing—original draft), Liyuan Tao, PhD (Conceptualization; Project administration; Methodology; Writing—review & editing) Funding This work was supported by the Major Science and Technology Projects of Xinjiang Uygur Autonomous Region [grant numbers 2203A03007-5]; and the Beijing Natural Science Foundation [grant number L222027]. 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Threshold dose-response association between smoking pack-years and the risk of gallbladder cancer: A nationwide cohort study. Eur J Cancer , 2023, 180: 99-107. Feng H, Yang L, Ai S, et al. Association between accelerometer-measured amplitude of rest-activity rhythm and future health risk: A prospective cohort study of the uk biobank. Lancet Healthy Longev , 2023, 4(5): e200-e210. Bowden SJ, Bodinier B, Kalliala I, et al. Genetic variation in cervical preinvasive and invasive disease: A genome-wide association study. Lancet Oncol , 2021, 22(4): 548-557. Ahmadi MN, Hamer M, Gill JMR, et al. Brief bouts of device-measured intermittent lifestyle physical activity and its association with major adverse cardiovascular events and mortality in people who do not exercise: A prospective cohort study. Lancet Public Health , 2023, 8(10): e800-e810. Sudlow C, Gallacher J, Allen N, et al. Uk biobank: An open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med , 2015, 12(3): e1001779. Pack years of smoking [Z]. 2024 National Center for Chronic Disease P, Health Promotion Office on S, Health. Reports of the surgeon general. The health consequences of smoking—50 years of progress: A report of the surgeon general. Atlanta (GA); Centers for Disease Control and Prevention (US). 2014. Alcohol guidelines review: Report from the guidelines development group to the uk chief medical officers. [M/OL]. 2016[Jan 1]. Zhang YB, Chen C, Pan XF, et al. Associations of healthy lifestyle and socioeconomic status with mortality and incident cardiovascular disease: Two prospective cohort studies. Bmj , 2021, 373: n604. Zhang X, Zhang MJ, Fine J. A proportional hazards regression model for the subdistribution with right-censored and left-truncated competing risks data. Stat Med , 2011, 30(16): 1933-1951. Park B, Kim Y, Lee J, et al. Sex difference and smoking effect of lung cancer incidence in asian population. Cancers (Basel) , 2020, 13(1). Health UDo, Services H. The health consequences of smoking—50 years of progress: A report of the surgeon general [Z]. Atlanta (GA); Centers for Disease Control and Prevention (US). 2014 Lauseker M, Hasford J, Saussele S, et al. Smokers with chronic myeloid leukemia are at a higher risk of disease progression and premature death. Cancer , 2017, 123(13): 2467-2471. Pfirrmann M, Baccarani M, Saussele S, et al. Prognosis of long-term survival considering disease-specific death in patients with chronic myeloid leukemia. Leukemia , 2016, 30(1): 48-56. Gaudet MM, Carter BD, Brinton LA, et al. Pooled analysis of active cigarette smoking and invasive breast cancer risk in 14 cohort studies. Int J Epidemiol , 2017, 46(3): 881-893. Gaudet MM, Gapstur SM, Sun J, et al. Active smoking and breast cancer risk: Original cohort data and meta-analysis. J Natl Cancer Inst , 2013, 105(8): 515-525. Park HA, Neumeyer S, Michailidou K, et al. Mendelian randomisation study of smoking exposure in relation to breast cancer risk. Br J Cancer , 2021, 125(8): 1135-1145. DeLancey JO, Hannan LM, Gapstur SM, et al. Cigarette smoking and the risk of incident and fatal melanoma in a large prospective cohort study. Cancer Causes Control , 2011, 22(6): 937-942. Kessides MC, Wheless L, Hoffman-Bolton J, et al. Cigarette smoking and malignant melanoma: A case-control study. J Am Acad Dermatol , 2011, 64(1): 84-90. Terry PD, Rohan TE, Franceschi S, et al. Cigarette smoking and the risk of endometrial cancer. Lancet Oncol , 2002, 3(8): 470-480. Office on S, Health. Publications and reports of the surgeon general. The health consequences of involuntary exposure to tobacco smoke: A report of the surgeon general. Atlanta (GA); Centers for Disease Control and Prevention (US). 2006. Zhou B, Yang L, Sun Q, et al. Cigarette smoking and the risk of endometrial cancer: A meta-analysis. Am J Med , 2008, 121(6): 501-508.e503. Pirie K, Peto R, Reeves GK, et al. The 21st century hazards of smoking and benefits of stopping: A prospective study of one million women in the uk. Lancet , 2013, 381(9861): 133-141. Islami F, Moreira DM, Boffetta P, et al. A systematic review and meta-analysis of tobacco use and prostate cancer mortality and incidence in prospective cohort studies. Eur Urol , 2014, 66(6): 1054-1064. Additional Declarations No competing interests reported. Supplementary Files supplementarymaterial.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5760852","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":398255779,"identity":"4b34d505-6bd0-4213-8097-342ef6781738","order_by":0,"name":"Jiaojiao Liao","email":"","orcid":"","institution":"Peking University Third Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jiaojiao","middleName":"","lastName":"Liao","suffix":""},{"id":398255780,"identity":"28c39a29-70ac-4386-804e-bdf9464413de","order_by":1,"name":"Zhaoyu Wang","email":"","orcid":"","institution":"Peking University Third Hospital","correspondingAuthor":false,"prefix":"","firstName":"Zhaoyu","middleName":"","lastName":"Wang","suffix":""},{"id":398255781,"identity":"6ef565ed-6dd7-4991-b977-01c118795eb4","order_by":2,"name":"Yu Liu","email":"","orcid":"","institution":"China Academy of Chinese Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Liu","suffix":""},{"id":398255782,"identity":"30359e64-6858-4558-a2a3-162019547c44","order_by":3,"name":"Zhaoji Li","email":"","orcid":"","institution":"Peking University Third Hospital","correspondingAuthor":false,"prefix":"","firstName":"Zhaoji","middleName":"","lastName":"Li","suffix":""},{"id":398255783,"identity":"cc3c7b7b-9242-4d3c-849a-9d1ea45a08d9","order_by":4,"name":"Hui Wang","email":"","orcid":"","institution":"Peking University Third Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hui","middleName":"","lastName":"Wang","suffix":""},{"id":398255784,"identity":"ef1a5dde-f4a9-404d-a119-4f13a924bd28","order_by":5,"name":"Liyuan Tao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIiWNgGAWjYBACPmYYi72HwQDMOEBACxtEC1AxzxlitTDAtEjkQIUIamHnMZP4ueOPPL/k2wNFN9sY5PhuJDB+LsDrMB4zyd4zBoYzZ+clGOe2MRhL3khglp5BQIsEb5sB44bbOQYgLYkbbiQABQnZ8rfNwH7DzTNgLfVEaZEG2gI0nAesJcGAsBa2YmvZNuPkmT1Av+SckzCceeZhszQ+Lfz8hzfefNsmZ9vPfvaYcU6ZjTzf8eSDn/FpYWDgMIDbCIodIM3YgFcDMKE8gLGYH+BSMwpGwSgYBSMbAABQTUH7Mk8ehwAAAABJRU5ErkJggg==","orcid":"","institution":"Peking University Third Hospital","correspondingAuthor":true,"prefix":"","firstName":"Liyuan","middleName":"","lastName":"Tao","suffix":""}],"badges":[],"createdAt":"2025-01-04 01:38:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5760852/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5760852/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":73307913,"identity":"04b859c4-e91c-4ed8-9e9d-ea2a9d4df995","added_by":"auto","created_at":"2025-01-08 17:32:19","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":624753,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart for the selection of participants.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5760852/v1/fbcb288bf9f4e724116be51a.jpg"},{"id":73307903,"identity":"076f06fc-0a58-49d6-a0f0-0c7b1fd7bde9","added_by":"auto","created_at":"2025-01-08 17:32:18","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":363418,"visible":true,"origin":"","legend":"\u003cp\u003eRisk of all cancer incidence and mortality in current and former smokers (Note: The plots were generated using restricted cubic splines (RCS), comparing current and former smokers to never smokers, with adjustments for age, gender, ethnicity, BMI, socioeconomic status (SES), family history of cancer, and drinking habits. Panel A showed the trend of cancer incidence risk increasing with cumulative pack-years of smoking, comparing current and former smokers with never smokers. Panel B showed the trend of cancer mortality risk increasing with cumulative pack-years of smoking, comparing current and former smokers with never smokers.)\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5760852/v1/c34e16785939c7a546d5eed2.jpg"},{"id":73307920,"identity":"94efa415-fb0e-4b0a-9d24-93960a483ddc","added_by":"auto","created_at":"2025-01-08 17:32:19","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":398090,"visible":true,"origin":"","legend":"\u003cp\u003eImpact of smoking cumulative pack-years on smokingor non-smoking related cancer incidence and mortality risk in former smokers (Note: the reference is never smoker). Panel A showed the trend of cancer incidence risk increasing with cumulative pack-years of smoking, categorizing the events as all cancer, smoking related cancerand non-smoking related cancer. Panel B showed the trend of cancer mortality risk increasing with cumulative pack-years of smoking, comparing former smokers with never smokers.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5760852/v1/e2e2cf77da6df51e942ff5ea.jpg"},{"id":73308729,"identity":"2ef58711-9e1c-4bef-89c0-e19d068824a3","added_by":"auto","created_at":"2025-01-08 17:40:18","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":549554,"visible":true,"origin":"","legend":"\u003cp\u003eImpact of cigarettes smoking on all cancer and specific cancer incidence and mortality. (Note1: 1 The reference is never smokers; 2 For specific cancers, only those with 100 or more events were shown, while those with fewer than 100 were marked as \"-\".)\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5760852/v1/947023a616097392c09fdb19.jpg"},{"id":73307906,"identity":"a4f44bfd-2718-4e13-8330-9d3564b21c9f","added_by":"auto","created_at":"2025-01-08 17:32:18","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":583838,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of cigarettes smoking on the incidence of specific smoking-related cancers (Note: Cox proportional regression and restricted cubic splines (RCS) adjusted by age, gender, ethnic, BMI, SES, family history of cancer, and drinking habits. A: Esophageal cancer, B: Stomach cancer, C: Colorectal cancer, D: Liver cancer including malignancies of the liver and intrahepatic bile ducts, E: Pancreatic cancer, F: Lung cancer including bronchi and lung malignancies, G: Kidney cancer is renal cell carcinoma, excluding renal pelvic malignancies, H: Bladder cancer, I: Myeloid leukemia includes multiple myeloma and malignant plasma cell neoplasms.)\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5760852/v1/5653c9206d834c4f8f38b7bc.jpg"},{"id":73307912,"identity":"9a41f4bd-82ed-45d9-8687-d019b6094335","added_by":"auto","created_at":"2025-01-08 17:32:19","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":603369,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of cigarettes smoking on the mortality of specific smoking-related cancers （Note: Cox proportional regression and restricted cubic splines (RCS) with 3 knots adjusted by age, gender, ethnic, BMI, SES, family history of cancer, and drinking habits. A: Esophageal cancer, B: Stomach cancer, C: Colorectal cancer, D: Liver cancer including malignancies of the liver and intrahepatic bile ducts, E: Pancreatic cancer, F: Lung cancer including bronchi and lung malignancies, G: Kidney cancer is renal cell carcinoma, excluding renal pelvic malignancies, H: Bladder cancer, I: Myeloid leukemia includes multiple myeloma and malignant plasma cell neoplasms.)\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5760852/v1/8f7ba463fc698b7c40d25694.jpg"},{"id":89972268,"identity":"f31e95e7-bf46-4582-bf96-7b4205de645f","added_by":"auto","created_at":"2025-08-27 05:39:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3765401,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5760852/v1/29530dca-d1c4-4083-817f-32c63ef4085b.pdf"},{"id":73307911,"identity":"356cb7f6-9542-4ae5-ae98-1b79a4a4ff0e","added_by":"auto","created_at":"2025-01-08 17:32:19","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":33486,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-5760852/v1/487fa3f4b79c9e3edcc3f9d1.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Pack-Years as a Stable Predictor of Cancer Incidence and Mortality: A Prospective Cohort Study from the UK Biobank","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWorldwide, the burden of cancer incidence and mortality is increasing rapidly \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Cancer remains a leading cause of death and an important barrier to increasing life expectancy in every country around the world\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. For individuals, a cancer diagnosis represents a stressful life event\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTobacco smoke can increases the risk of cancer through its content of carcinogens, such as nitrosamines, polycyclic aromatic hydrocarbons, acrylamides, volatile organics, and cadmium\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. While cigarette smoking among U.S. adults has declined over the past five decades, in 2021, 18.7% (an estimated 46.0\u0026nbsp;million) of U.S. adults were still current users of any tobacco product \u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. Smoking is associated with the development of many kinds of cancers\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Lung cancer is the leading cause of cancer death globally, while cigarette smoking is the most prevalent lung cancer risk factor\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. A meta-analysis showed that the risk of lung cancer mortality rose with pack-years, and less than 60 pack-years presented relative risks (RRs) below 10 in Chinese population\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. In addition to lung cancer, smoking has been shown to increase the risk of dying of cancer of the oropharynx, pancreas, bladder, esophagus, stomach, liver, kidney and cervix\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Kelvin et al. conducted a meta-analysis of 28 prospective cohort studies containing 1,463,796 subjects from America, Europe, and Asia, showing that smokers carried a higher colorectal cancer risk than never smokers\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. Although cigarette smoking is generally associated with a lower incidence of melanoma, Jackson et al. found that current smokers had an increased risk of melanoma-associated death (MAD) compared with former or nonsmokers with a hazard ratio (HR) of 1.48\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. Besides, the amount of smoking reported was associated with increased MAD risk, with an HR of 1.63 (95% CI, 1.33\u0026ndash;2.01) for heavy smokers and 1.48 (95% CI, 1.13\u0026ndash;1.93) for moderate smokers. The incidence of multiple myeloma did not seem to be associated with tobacco smoking\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. Fircanis proved that cigarette smoking was a significant risk factor for the development of acute myeloid leukemia in adults\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWhile smoking is associated with the development of numerous cancers, certain cancers, such as prostate cancer (PCa), lack a clearly established correlation with smoking in terms of incidence or mortality. Some studies have reported a lower risk of PCa for smokers\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e, while a Mendelian randomization study found no such association\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. In addition to exploring whether smoking is related to the incidence and mortality of cancers, it is also crucial to accurately depict the quantitative relationship between smoking dosage and the risk of cancers occurrence and death.\u003c/p\u003e \u003cp\u003eCurrently, measures of smoking exposure include the number of cigarettes smoked per day, the smoking duration, and pack-years. However, it is still unclear which indicator is more accurate for measuring cumulative exposure to smoking, particularly in relation to different health outcomes. In prior research, pack-years are commonly classified into distinct categories for analysis as a categorical variable\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e to examine the dose-response relationship between smoking and cancer development or death. The quantitative analysis can better reflect the cumulative harm of smoking exposure. However, how to measure the cumulative exposure continuously and quantitatively to smoking remains a significant scientific challenge. In-depth research is needed to assess the linear relationship between cumulative smoking exposure and the incidence and mortality of various cancers.\u003c/p\u003e \u003cp\u003eTherefore, the aim of this study was to quantitatively describe the dose-response relationship between smoking and cancer risk using the UK Biobank database, and to investigate the impact of smoking on the incidence and mortality risk of overall cancer and 19 specific cancers.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eStudy design and participants\u003c/p\u003e \u003cp\u003eThis was a prospective cohort study using the UK Biobank database, which was a substantial population-based longitudinal study. Launched in 2006, the UK Biobank project collected biological specimens, health data, and lifestyle details systematically from a large group of approximately 500,000 committed volunteers throughout the United Kingdom\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. The research received approval from the Northwest Multi-center Research Ethics Committee (reference 21/NW/0157). All participants gave their written informed consent when they enrolled initially. Further details about the UK Biobank have been documented in earlier publications\u003csup\u003e[\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. The national cancer registries were also used in this study, which provides information on cancer occurrence and mortality. A total of 502,421 subjects aged 40 to 72 years were evaluated for eligibility of inclusion. After an exclusion of participants with baseline cancers (n\u0026thinsp;=\u0026thinsp;23,753), newly diagnosed non-melanoma skin cancer or benign cases (n\u0026thinsp;=\u0026thinsp;34,121), and those with missing data on outcomes, exposures, smoking status, lifestyle measurement, and covariates, 336,885 participants were included in the final analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This study adhered to the guidelines outlined in the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting framework.\u003c/p\u003e \u003cp\u003eAssessment of exposures\u003c/p\u003e \u003cp\u003ePack years of smoking was a synthetic continuous variable generated based on smoking status and history which was self-reported trough a questionnaire at baseline. The following questions were asked to determine the smoking status of former smokers: \"How old were you when you first started smoking on most days?\"; \"About how many cigarettes did you smoke on average each day? \"; \"How old were you when you last smoked on most days?\". The general definition of pack year\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e is the number of cigarettes smoked per day, divided by twenty, multiplied by the number of years of smoking. The number of years of smoking is calculated by subtracting the age of starting smoking from the age smoking was stopped.\u003c/p\u003e \u003cp\u003eAssessment of outcomes\u003c/p\u003e \u003cp\u003eCancer cases and deaths due to cancer were determined through a linkage to the national cancer registries that included date of diagnosis, date of death, and the primary cause of death and was updated to June 1st, 2022. Diagnostic information of malignant cancers was derived using ICD-10 codes C00-C97, with an exclusion of non-melanoma skin cancer coded as C44. Participants who were diagnosed with any type of malignant cancer during follow-up were defined as cancer cases, otherwise they were followed up until end of the study period or censoring. Smoking-related cancers subtype was defined according to The Health Consequences of Smoking \u0026minus;\u0026thinsp;50 Years of Progress - A Report of the Surgeon General\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e and included the following cancers: oropharynx, larynx, esophagus, trachea/bronchus/lung, acute myeloid leukemia, stomach, liver, pancreas, kidney/ureter, cervix, bladder, and colorectal. Cancer death was defined if the primary cause of death was malignant cancer. If the primary cause of death was not cancer, the death was defined as a competing risk event.\u003c/p\u003e \u003cp\u003eMeasurements of sociodemographic and covariates\u003c/p\u003e \u003cp\u003eTouchscreen questionnaire was administered at recruitment, in which information on socioeconomic status (SES) and lifestyle factors were collected. Individual SES was defined based on a latent classification analysis of household income, education qualifications, and employment status (Appendix Table\u0026nbsp;3). The participants were divided into high, medium, or low SES groups based on individual SES. In our study, BMI and alcohol consumption were assessed and were representative of lifestyle. BMI was calculated as weight in kg divided by squared height in meter and categorized into four groups of \u0026lt;\u0026thinsp;18.5, 18.5\u0026ndash;24.9, 25.0-29.9, and \u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e. A BMI of 18.5\u0026ndash;24.9 kg/m\u003csup\u003e2\u003c/sup\u003e was considered as a \"healthy\" BMI. According to the UK guidelines, drinking habits were categorized into safe, hazardous, and harmful consumption levels\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. In this study, no alcohol use or safe consumption level were defined as healthy drinking. The codes used to delineate the variables were provided in Appendix Table\u0026nbsp;2.\u003c/p\u003e \u003cp\u003eOther covariates were also obtained through questionnaires, including age at recruitment, gender, ethnicity, family history of cancer, and history of cancer screening. Ethnicity was categorized into five groups: White, mixed, Asian, or Asian British, Black or Black British, and other ethnic groups. We only consider the cancer screenings for breast cancer, colorectal cancer, prostate cancer, and cervical cancer.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eBaseline characteristics of the participants were described by the mean (standard deviation [SD]) or median (interquartile range, IQR) for continuous variables and proportions for categorical variables according to smoking status groups. Latent classification analysis was applied on household income, education, and employment status to group the SES\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e using R package \u0026ldquo;poLCA\u0026rdquo;.\u003c/p\u003e \u003cp\u003eWe treated pack-years of cigarettes smoking as a continuous variable and used a competing risk model to evaluate the Hazard Ratios (HRs) associated with each additional pack-year on cancer incidence and mortality, adjusting for covariates including age, gender, ethnicity, BMI, SES, alcohol consumption status, and family history of cancer. In the analysis of cancer incidence, participants were followed from the time of enrollment until the date of their last follow-up, loss to follow-up, cancer diagnosis, or death, whichever came first, and deaths without cancer occurrence were considered as competing events for the cancer incidence outcome. For mortality analysis, follow-up time began at enrollment and ended at the last follow-up, loss to follow-up, or death. Deaths due to other non-cancer causes were considered as competing risk factors\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e for cancer mortality. For specific cancer types, we only examined the associations of smoking pack-years with the incidence and mortality of those with a substantial case number exceeding 100.\u003c/p\u003e \u003cp\u003eWe employed the Cox proportional hazards model to analyze the association between pack-years of smoking and the incidence and mortality risk of all cancers, stratified by smoking status. In Cox proportional hazards regression, the variable of continuous smoking pack-years was modeled using restricted cubic splines to allow a nonlinear association with the hazard of over cancer, smoking related cancer or non-smoking related cancer incidence and mortality, presented graphically.\u003c/p\u003e \u003cp\u003eSeveral sensitivity analyses were conducted. Initially, participants who reported being current or former smoker but had a smoking pack-year of zero were excluded from the analysis. A COX proportional risk model was then applied to assess the association between pack-years of smoking and the risks of overall cancer incidence and mortality. Following this, competing risk model was used to separately evaluate the impact of pack-years on cancer risk and mortality among current and former smokers.\u003c/p\u003e \u003cp\u003eSecondly, within the entire cohort, we utilized the Cox proportional hazards model instead of the competing risk model to analyze the impact of pack-years of smoking on the incidence and mortality risk of overall cancer. This analysis was performed separately across all participants, current smokers, and former smokers.\u003c/p\u003e \u003cp\u003eBesides, we analyzed the risk of cancer incidence and death in each gender subgroup and age subgroup using a competing risk model. All tests were considered statistically significant at a two-tailed p-value of less than 0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eCharacteristics of the study population\u003c/p\u003e \u003cp\u003eA total of 336,885 participants aged 55.90\u0026thinsp;\u0026plusmn;\u0026thinsp;8.07 constituted the study cohort, with a median cancer incidence follow-up time was 13.93 (IQR, 13.05\u0026ndash;14.70) years, while the median follow-up time of cancer mortality was 14.06 (IQR, 13.32\u0026ndash;14.77) years. Among all participants, 178,682 (53.0%) were female and the majority were White (95.2%). At baseline, the average cigarettes smoking of the participants was 8.20 pack-years, and 33,099 (9.8%) continued to smoke, 87,241 (25.9%) reported that they had quit smoking, 216,545 (64.3%) remained as never smokers. During the follow-up, a total of 36,964 participants (11.0%) developed cancer, among which 11,931 (3.5%) died due to cancer. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, participants who had quit smoking were more likely to be older, be male, have a higher BMI, have a higher SES, have unhealthy drinking habits, have a family history of cancer, compared to the participants who continued to smoke.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline Characteristics by Smoking Status at Baseline (N\u0026thinsp;=\u0026thinsp;336885)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal population\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;336885)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCurrent\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;33099)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFormer\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;87241)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;216545)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePack-years, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.20 (15.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.16 (18.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.36 (18.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, mean (SD), y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e55.90 (8.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54.30 (8.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57.99 (7.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55.29 (8.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e178682 (53.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15578 (47.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40013 (45.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e123091 (56.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnic, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e320698 (95.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31465 (95.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e85201 (97.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e204032 (94.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1899 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e362 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e451 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1086 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian or Asian British\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5855 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e446 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e526 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4883 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack or Black British\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4841 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e485 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e478 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3878 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther ethnic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3592 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e341 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e585 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2666 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI group, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e110735 (32.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11922 (36.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21895 (25.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76918 (35.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1720 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e388 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e209 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1123 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOver weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e143147 (42.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13517 (40.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e39173 (44.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90457 (41.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e81283 (24.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7272 (22.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25964 (29.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48047 (22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh SES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e111366 (33.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6887 (20.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24430 (28.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80049 (37.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium SES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e155534 (46.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15476 (46.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41047 (47.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e99011 (45.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow SES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e69985 (20.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10736 (32.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21764 (24.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37485 (17.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealthy drinking, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e141695 (42.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18811 (56.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43358 (49.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e79526 (36.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily history of cancer, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e120944 (35.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11608 (35.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33161 (38.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76175 (35.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll cancer cases, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36964 (11.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4791 (14.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11663 (13.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20510 (9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll cancer death, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11931 (3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5372 (16.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4166 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2393 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCigarettes smoking and cancer incidence\u003c/p\u003e \u003cp\u003eAccording to the competitive risk models, compared to never smokers, the risk of developing cancer increased by 0.9% for each additional pack-year smoked (HR\u0026thinsp;=\u0026thinsp;1.009, 95% CI\u0026thinsp;=\u0026thinsp;1.008\u0026ndash;1.009, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001). For smoking-related cancers, the risk increased by 1.7% per pack-year (HR\u0026thinsp;=\u0026thinsp;1.017, 95% CI\u0026thinsp;=\u0026thinsp;1.017\u0026ndash;1.018, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001). For non-smoking-related cancers, the HR for cancer incidence was 0.998 (95% CI, 0.997\u0026ndash;0.999) for each additional pack-year of smoking exposure.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA showed that the risk of cancer incidence in the study subjects continuously increased with the accumulation of smoking pack-years; the risk for those who were still smoking at baseline was higher than for those who had quit smoking (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). The order of cancer risk from highest to lowest was smoking-related cancers, all cancers, and non-smoking related cancers (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). The incidence risk of 9 site-specific smoking-related cancers increases with cumulative pack-years of smoking (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), with the hazard ratio (HR) per pack-year ranging from 1.006 to 1.028 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). For nine types of smoking-related cancers, the risk of developing cancer increased rapidly with the number of pack-years for those smoking less than 30 pack-years. However, beyond 30 pack-years, the rate of risk increase slowed down (excluding lung cancer) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFor individual cancers, smoking (pack-years) significantly increases the risk of developing of 10 site-specific cancers, listed the top three from highest to lowest HR: lung (HR\u0026thinsp;=\u0026thinsp;1.028, 95%CI, 1.026\u0026ndash;1.030, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), esophageal (HR\u0026thinsp;=\u0026thinsp;1.014, 95%CI, 1.012\u0026ndash;1.016, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), bladder (HR\u0026thinsp;=\u0026thinsp;1.014, 95%CI, 1.011\u0026ndash;1.016, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001) cancers. Smoking (pack-years) is inversely associated with the occurrence of melanoma, prostate cancer, uterine cancer, and multiple myeloma. There is insufficient evidence to link smoking (pack-years) with the occurrence of brain cancer, thyroid cancer, non-Hodgkin lymphoma, lymphoid leukemia, or ovarian cancer (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCigarettes smoking and cancer mortality\u003c/p\u003e \u003cp\u003eRegarding cancer mortality, the overall cancer mortality for those who were still smoking at baseline was higher than for those who had quit smoking (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). The order of cancer risk from highest to lowest was smoking-related cancers, all cancers, and non-smoking related cancers (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Cigarettes smoking (pack-years) can increase the risk of death from overall cancers (HR\u0026thinsp;=\u0026thinsp;1.015, 95%CI, 1.015\u0026ndash;1.016, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), smoking-related cancers (HR\u0026thinsp;=\u0026thinsp;1.019, 95%CI, 1.018\u0026ndash;1.020, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), and non-smoking-related cancers (HR\u0026thinsp;=\u0026thinsp;1.002, 95%CI, 0.999\u0026ndash;1.004, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.150), as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. For individual cancers, each additional pack-year of smoking increases the risk of death for 10 site-specific cancers, listed the top three from highest to lowest HR: lung cancer (HR\u0026thinsp;=\u0026thinsp;1.028, 95%CI, 1.026\u0026ndash;1.030, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), bladder cancer (HR\u0026thinsp;=\u0026thinsp;1.015, 95%CI, 1.012\u0026ndash;1.019, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), esophageal cancer (HR\u0026thinsp;=\u0026thinsp;1.014, 95%CI, 1.012\u0026ndash;1.017, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001). However, smoking (pack-years) is inversely associated with the risk of death from uterine cancer (HR\u0026thinsp;=\u0026thinsp;0.981, 95%CI, 0.964\u0026ndash;0.997, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.024). As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, the mortality risk for nine types of smoking-related cancers increased steadily with the number of cumulative pack-years. Within the range of 0\u0026ndash;30 pack-years, the increase was more rapid, while beyond 30 pack-years, the rate of increase slowed down.\u003c/p\u003e \u003cp\u003eSensitivity and subgroup analyses consistently demonstrated that both the risk of cancer and mortality rates rise with an increase in smoking pack-years, with a HR of 1.009. Notably, current smokers face higher risks of both cancer and mortality compared to former smokers (Appendix Table\u0026nbsp;1). In the subgroup analysis, the risks for overall cancer incidence and mortality were higher in females (Incidence: Female, HR\u0026thinsp;=\u0026thinsp;1.012, 95%CI, 1.011\u0026ndash;1.013, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001; Male, HR\u0026thinsp;=\u0026thinsp;1.007, 95%CI, 1.006\u0026ndash;1.008, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001. Mortality: Female, HR\u0026thinsp;=\u0026thinsp;1.019, 95%CI, 1.019\u0026ndash;1.020, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001; Male, HR\u0026thinsp;=\u0026thinsp;1.013, 95%CI, 1.013\u0026ndash;1.014, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001). The risk of cancer occurrence varied among different age groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), with the highest risk in the 50\u0026ndash;60 age group (HR\u0026thinsp;=\u0026thinsp;1.010, 95% CI, 1.009\u0026ndash;1.011), followed by those aged\u0026thinsp;\u0026le;\u0026thinsp;50 (HR\u0026thinsp;=\u0026thinsp;1.008, 95% CI, 1.005\u0026ndash;1.010), and the lowest in those aged\u0026thinsp;\u0026gt;\u0026thinsp;60 (HR\u0026thinsp;=\u0026thinsp;1.007, 95% CI, 1.007\u0026ndash;1.008). The risk of tumor-related mortality also differed among age groups, with the highest risk in the \u0026le;\u0026thinsp;50 age group (HR\u0026thinsp;=\u0026thinsp;1.020, 95% CI, 1.016\u0026ndash;1.023), followed by the 50\u0026ndash;60 age group (HR\u0026thinsp;=\u0026thinsp;1.018, 95% CI, 1.016\u0026ndash;1.019), and the lowest in those aged\u0026thinsp;\u0026gt;\u0026thinsp;60 (HR\u0026thinsp;=\u0026thinsp;1.014, 95% CI, 1.013\u0026ndash;1.015).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eSmoking significantly increases the risk of developing and dying from malignant cancers. Overall, compared to non-smokers, the risk of cancer incidence and mortality among smokers increases in an approximately linear fashion with cumulative pack-years of smoking. For each additional pack-year, the risk of developing malignant cancers increases by about 0.9%, and the risk of dying from malignant cancers increases by about 1.5%. For example, a person who smokes one pack per day for 20 years has a 1.196 times higher risk of developing malignant cancers (about 20% increase) and a 1.349 times higher risk of dying from malignant cancers (about 35% increase) compared to a non-smoker. Furthermore, the HRs for overall cancer incidence and mortality were generally higher in men than in women, is consistent with the results of another study\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. This study innovatively analyzed the association between pack-years of smoking and the incidence and mortality of cancers by treating pack-years as a continuous variable. In previous research, Chan et al.\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e divided subjects into smokers and non-smokers. They found that, compared to non-smokers, smokers had a hazard ratio (HR) of 2.40 (95% CI: 2.22\u0026ndash;2.59) for developing lung cancer. Park et al.\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e demonstrated that the lung cancer incidence HRs for former smokers versus never smokers were 1.27 (95% CI: 1.23\u0026ndash;1.33) for men and 1.43 (95% CI: 1.16\u0026ndash;1.81) for women. Our study showed that each additional pack-year of smoking increased the risk of developing lung cancer, with an HR of 1.028 (95% CI: 1.026\u0026ndash;1.030), and the HR for lung cancer mortality was also 1.028 (95% CI: 1.026\u0026ndash;1.030). In our study, the average number of pack-years among smokers was 22.9, resulting in an average HR of 1.88. The differences in HR values might have been attributed to variations in the study populations.\u003c/p\u003e \u003cp\u003eConsistent with our findings, a large prospective cohort study conducted by Chan et al. in China indicated that ever-smoking was associated with statistically significant higher risks of 14 cancers, including esophageal cancer, stomach cancer, liver cancer, laryngeal cancer, lung cancer, and bladder cancer, among others. For the nine types of smoking-related cancers analyzed in this study, the relationship between smoking and cancer incidence and mortality is well-established\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e and positively correlated with cumulative pack-years of smoking \u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. Lung cancer shows the highest increase in incidence risk per pack-year, followed by esophageal cancer, bladder cancer, stomach cancer, liver cancer, myeloid leukemia, pancreatic cancer, colorectal cancer, and kidney cancer. Regarding mortality risk, lung cancer is the highest, followed by bladder cancer, esophageal cancer, liver cancer, stomach cancer, kidney cancer, pancreatic cancer, colorectal cancer, and myeloid leukemia. Our findings are consistent with previous research. In our study, the association between myeloid leukemia mortality risk and pack-years of smoking was not statistically significant. Lauseker et al.\u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e found that, in chronic myeloid leukemia (CML) patients, the 8-year survival probability was 87% for non-smokers and 83% for smokers, with smokers having a 2.08 times higher risk of death and a 2.11 times higher risk of disease progression. However, in CML patients treated with first line imatinib, 8-year overall survival probabilities exceeded 80%, and many deaths were due to causes unrelated to CML\u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFor non-smoking-related cancers, the overall incidence risk has an HR of 0.998 (95% CI: 0.997\u0026ndash;0.999), and the overall mortality risk has an HR of 1.002 (95% CI: 0.999\u0026ndash;1.004). Specifically, smoking is inversely associated with the incidence risk of melanoma, multiple myeloma, uterine cancer, and prostate cancer (HR\u0026thinsp;\u0026lt;\u0026thinsp;1). However, smoking is positively associated with both the incidence and mortality risk of breast cancer (HR\u0026thinsp;\u0026gt;\u0026thinsp;1), and these associations are statistically significant.\u003c/p\u003e \u003cp\u003eWe find that smoking is a risk factor for the incidence and mortality of breast cancer, consistent with some findings\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e. A meta-analysis showed that breast cancer risk increased linearly with intensity of smoking (cigarettes/day). However, our study found that the incidence and mortality risk of breast cancer increased linearly with the number of pack-years of smoking. A Mendelian randomization study by Park\u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e provided supportive evidence for a potential causal association with breast cancer risk for lifetime smoking exposure but not cigarettes per day among smokers, which was consistent with our findings.\u003c/p\u003e \u003cp\u003eSimilar to our findings, previous studies have reported an inverse relationship between smoking and the incidence of melanoma\u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e, though not statistically significant. Our study, however, shows a statistically significant negative correlation (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This might be misleading as we did not adjust for sun exposure. Most studies suggest that there is no statistically significant association between smoking and the incidence of multiple myeloma\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. In this study, however, smoking is found to be negatively correlated with the occurrence of multiple myeloma, although smoking does not significantly increase the risk of death from multiple myeloma among smokers. The inverse association between smoking (pack-years) and multiple myeloma might be due to unmeasured confounding factors. There is an inverse relationship between smoking and the development of endometrial carcinoma\u003csup\u003e[\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/sup\u003e and prostate cancer\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/sup\u003e, and our study provides new evidence supporting this association. While smoking is positively associated with prostate cancer mortality (HR\u0026thinsp;=\u0026thinsp;1.003, 0.999\u0026ndash;1.007, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.120). Although this association is not statistically significant, it is increasingly clear that smoking may be associated with prostate cancer. A meta-analysis showed that smokers were 24% more likely than nonsmokers to die from prostate cancer\u003csup\u003e[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe study has several strengths. First, the analysis is based on the UK Biobank database and the national cancer registries, which provide a large sample size and accurate data recording. Second, we analyzed pack-years of smoking as a continuous variable, revealing a stable linear relationship between the risk of cancer incidence and mortality and pack-years of smoking. Third, we employed various statistical analysis methods, including competing risk models, to ensure the robustness of our findings. Fourth, this study comprehensively analyzes nine smoking-related and ten non-smoking-related cancers, examining the incidence and mortality impacts of smoking on these cancers separately.\u003c/p\u003e \u003cp\u003eThis study also has several limitations. First, because the smoking status of the study subjects was collected at baseline, the smoking status during the period from enrollment to the outcome occurrence was unknown. Therefore, the cumulative pack-years of smoking for current smokers were inaccurate and underestimated, which could weaken the observed associations between smoking and cancer incidence and mortality. Second, a primary drawback was the sub-optimal control for variables that affect melanoma outcomes, specifically UV exposure history, skin type, and history of blistering sunburns. Third, this study only analyzed the association between smoking exposure and cancer, without examining the impact of smoking cessation on cancer. This gap highlights an area for future research to address.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe incidence and mortality risk of cancer increase in an approximately linear manner with the number of pack-years of smoking. In addition to WHO-defined smoking-related cancers, smoking also elevates the incidence and mortality risk of various non-smoking-related cancers. Although smoking is inversely correlated with the incidence of melanoma and prostate cancer, it promotes their progression and increases the mortality risk for these patients. Therefore, smoking cessation is strongly recommended.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data underlying this article are available in UK Biobank, at https://www.ukbiobank.ac.uk/. Any data analysis scripts that generated the results must also be made available.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJiaojiao Liao, MS (Conceptualization; Formal analysis; Investigation; Methodology; Project administration; Writing\u0026mdash;original draft; Writing\u0026mdash;review \u0026amp; editing), Zhaoyu Wang, MS (Conceptualization; Methodology; Writing\u0026mdash;original draft; Writing\u0026mdash;review \u0026amp; editing), Yu Liu, PhD (Conceptualization; Methodology; Writing\u0026mdash;review \u0026amp; editing), Zhaoji Li, MS (Writing\u0026mdash;original draft; Writing\u0026mdash;review \u0026amp; editing), Hui Wang, MS (Writing\u0026mdash;original draft), Liyuan Tao, PhD (Conceptualization; Project administration; Methodology; Writing\u0026mdash;review \u0026amp; editing)\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Major Science and Technology Projects of Xinjiang Uygur Autonomous Region [grant numbers 2203A03007-5]; and the Beijing Natural Science Foundation [grant number L222027].\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no potential conflicts of interest.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSung H, Ferlay J, Siegel RL, et al. 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A systematic review and meta-analysis of tobacco use and prostate cancer mortality and incidence in prospective cohort studies. \u003cem\u003eEur Urol\u003c/em\u003e, 2014, 66(6): 1054-1064.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"smoking, cancer, pack-years, incidence, mortality","lastPublishedDoi":"10.21203/rs.3.rs-5760852/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5760852/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eTo clarify the dose-response relationship between cigarette smoking and the risk of developing or dying from multiple site-specific cancers.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe prospectively analyzed baseline smoking pack-years in relation to cancer incidence and mortality in the UK Biobank, with data obtained from national cancer registries. Using a competing risk model, we assessed the associations between smoking pack-years and cancer outcomes, adjusting for age, gender, ethnicity, BMI, SES, drinking habits, and family cancer history.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe study involved 336,885 individuals with a mean age of 55.9 years (SD 8.07), 53% of whom were female. There were 33,099 (9.8%) current smokers with an average of 27.16 (SD 18.38) pack-years and 87,241 (25.9%) former smokers with an average of 21.36 (SD 18.24) pack-years. Over a median follow-up of 13.93 years, 36,964 cancer events and 11,931 cancer deaths were recorded. The incidence and mortality risks of overall cancers increased linearly with smoking pack-years. Each additional pack-year increased the risk of all cancers by 0.9% (HR\u0026thinsp;=\u0026thinsp;1.009, 95% CI\u0026thinsp;=\u0026thinsp;1.008\u0026ndash;1.009) and smoking-related cancers by 1.7% (HR\u0026thinsp;=\u0026thinsp;1.017, 95% CI\u0026thinsp;=\u0026thinsp;1.017\u0026ndash;1.018). Cancer mortality rose by 1.5% per pack-year (HR\u0026thinsp;=\u0026thinsp;1.015, 95% CI\u0026thinsp;=\u0026thinsp;1.015\u0026ndash;1.016), particularly in lung, bladder, esophageal, liver, and stomach cancers, with HRs ranging from 1.010 to 1.028. The study highlights the linear relationship between smoking pack-years and cancer risk, especially for smoking-related cancers. However, some cancers showed no significant correlation or an opposite effect.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003ePack-years of smoking provide a linear representation of smoking\u0026rsquo;s impact on cancer incidence and mortality, significantly affecting various malignancies, particularly smoking-related ones.\u003c/p\u003e","manuscriptTitle":"Pack-Years as a Stable Predictor of Cancer Incidence and Mortality: A Prospective Cohort Study from the UK Biobank","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-08 17:32:13","doi":"10.21203/rs.3.rs-5760852/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e9c9030f-cbf9-4141-ab8e-14b46295236c","owner":[],"postedDate":"January 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-27T05:23:34+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-08 17:32:13","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5760852","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5760852","identity":"rs-5760852","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}