European practice patterns and barriers to smoking cessation after a cancer diagnosis in the setting of curative versus palliative cancer treatment

Oncologists' communication about tobacco and alcohol use during treatment for esophagogastric cancer: a qualitative observational study of simulated consultations

PURPOSE

Tobacco and alcohol use influence cancer risk as well as treatment outcomes, specifically for esophageal and gastric cancer patients. Therefore, it is an important topic to discuss during consultations. This study aims to uncover medical, radiation, and surgical oncologists' communication about substance use, i.e., tobacco and alcohol use, in simulated consultations about curative and palliative esophagogastric cancer treatment.

METHODS

Secondary analyses were performed on n = 40 standardized patient assessments (SPAs) collected in three Dutch clinical studies. Simulated patients with esophagogastric cancer were instructed to ask about smoking or alcohol use during treatment. The responses of the 40 medical, radiation, and surgical oncologists were transcribed verbatim, and thematic analysis was performed in MAXQDA.

RESULTS

Oncologists consistently advocated smoking cessation during curative treatment. There was more variation in their recommendations and arguments in the palliative compared to the curative setting and when addressing alcohol use instead of smoking. Overall, oncologists were less stringent regarding behavior change in the palliative than in the curative setting. Few oncologists actively inquired about the patient's perspective on the substance use behavior, the recommended substance use change, or the support offered.

CONCLUSION

Clear guidelines for oncologists on when and how to provide unequivocal recommendations about substance use behavior change and support to patients are needed. Oncologists might benefit from education on how to engage in a conversation about smoking or alcohol.

Improving referral rates for smoking cessation: A multifaceted intervention aimed at radiation oncologists

Objective

Continuation of smoking after a cancer diagnosis increases the burdensome side effects from cancer treatment, and decreases the chances of cure. Smoking cessation may improve oncological outcomes in cancer patients. This study aims to evaluate if radiation oncologists can be motivated by a smoking cessation awareness intervention to discuss smoking status more frequently and increase the referral rate for smoking cessation-support.Study design and Setting:A multifaceted approach was used to improve awareness: First, current practice was evaluated by a retrospective chart review of 282 patients referred for radiotherapy to ascertain smoking status, discussion of smoking cessation support and referral rates. Secondly, radiation oncologists were interviewed about their motives and barriers to discuss smoking status and smoking cessation support. The results were fed back in a teaching lecture to the doctors involved. Finally, the effect of this smoking cessation awareness intervention was prospectively evaluated in 100 patients.

Results

After the smoking cessation awareness intervention, smoking cessation was more frequently discussed compared to baseline (77% (10/13)) and 39.5% (17/43) respectively. The referral rate for smoking cessation increased from 2.3% (1/43) to 69.2% (9/13).

Conclusion

Without an active smoking prevention awareness policy, referral for smoking cessation support for cancer patients by radiation oncologists is low. A relatively short and simple smoking awareness intervention for radiation oncologist may result in a more frequent discussion with patients about smoking cessation and an even larger increase in referrals for smoking cessation support.

Practice patterns, experiences, and challenges of German oncology health care staff with smoking cessation in patients with cancer: a cross-sectional survey study

PURPOSE

Often, cancer patients do not receive education about the negative consequences of smoking on the treatment outcome. To support cancer patients in the process of smoking cessation, it is essential to involve oncology staff. This study aims to learn about the experiences and attitudes from the point of view of oncology staff and, thus, how a smoking intervention should be designed. The study aims to engage all oncology staff due to the unclear responsibility for providing smoking cessation education, support, and motivating cancer patients to quit smoking.

METHODS

N = 354 German oncology staff (oncologists, nurses, psycho-oncologists, others) filled out a 5-point Likert scale-based questionnaire regarding practices, potential barriers, and attitudes towards smoking cessation between October 2021 and June 2022. The questionnaire was developed by Derksen et al. (2020), translated and slightly modified for the use of this study. It was distributed to all leading oncology staff in our Cancer Center Network with a request to share with all oncology staff. Flyers were also handed out in all oncology wards and outpatient clinics in the same Cancer Center Network.

RESULTS

Most oncology staff ask cancer patients about their current smoking status (curative, M = 2.27; SD = 1.59; palliative, M = 2.90; SD = 1.83), but they rarely treat or refer patients for a smoking cessation intervention (curative, M = 4.78; SD = 1.20; palliative, M = 4.99; SD = 1.06). Smoking behavior of curative cancer patients is addressed more than that of palliative cancer patients (d =  - 37). Regression analyses of key dependent variables showed that profession, setting, and the belief that continued smoking affects treatment outcome explained the variance of asking patients if they smoke, advising to stop smoking and lack of time (without profession).

CONCLUSION

Involving oncology staff in motivating cancer patients who smoke to quit and referring them to smoking cessation services should take the different attitudes and knowledge of the staff into account to improve treatment that supports tobacco cessation.

IMPLICATIONS FOR CANCER SURVIVORS

Cancer patients have special needs when it comes to a cessation program. In the long term, survivors will benefit from tailored smoking cessation education and services provided by oncology staff to help them quit smoking after a cancer diagnosis.

Tobacco use and cancer-related symptom burden: Analysis of the US Population Assessment of Tobacco and Health Study

BACKGROUND

Understanding the relationship between tobacco use and symptom burden may inform tobacco treatment interventions tailored to the needs of individuals with cancer.

METHODS

The study included 1409 adult cancer survivors from Wave 5 of the US Food and Drug Administration Population Assessment of Tobacco and Health (PATH) Study. A multivariate analysis of variance controlling for age, sex, and race/ethnicity assessed the association of cigarette smoking and vaping on cancer-related symptom burden (fatigue, pain, emotional problems) and quality of life (QoL). Generalized linear mixed models controlling for the same factors were used to assess associations among symptom burden, QoL, and quit-smoking intentions, quit-smoking likelihood, and past 12-month smoking quit attempts.

RESULTS

Weighted rates of current cigarette smoking and vaping were 14.21% and 2.88%, respectively. Current smoking was associated with greater fatigue (p < .0001; partial η 2  = .02), pain (p < .0001; partial η 2  = .08), emotional problems (p < .0001; partial η 2  = .02), and worse QoL (p < .0001; partial η 2  = .08). Current vaping was associated with greater fatigue (p = .001; partial η 2  = .008), pain (p = .009; partial η 2  = .005), and emotional problems (p = .04; partial η 2  = .003), but not worse QoL (p = .17). Higher cancer symptom burden was not associated with reduced interest in quitting, likelihood of quitting, or odds of past year quit attempts (p > .05 for each).

CONCLUSIONS

Among adults with cancer, current smoking and vaping were associated with greater symptom burden. Survivors' interest in and intentions to quit smoking were not related to symptom burden. Future research should examine the role of tobacco cessation in improving symptom burden and QoL.

Smoking patterns and the intention to quit in German patients with cancer: study protocol for a cross-sectional observational study

INTRODUCTION

Patients who continue to smoke cigarettes after a cancer diagnosis can experience poorer treatment tolerance and outcomes than those who quit immediately. Identifying risk factors specific to patients with cancer who smoke, as well as their smoking behaviours (eg, frequency of use, types of tobacco products), dependency level and quit intentions, is necessary to better inform patients and encourage quitting smoking after a cancer diagnosis. This study aims to examine the occurrence of smoking in patients with cancer treated at specialised oncology departments and outpatient clinics based within the metropolitan region of Hamburg, Germany, and presents an analysis of their smoking patterns. This understanding is the first step in developing an adequate smoking cessation intervention and shall contribute to a sustainable improvement in the treatment results, long-term survival and quality of life of patients with cancer.

METHODS AND ANALYSIS

A questionnaire will be administered to patients with cancer (N=865) aged 18 years and above in the catchment area of Hamburg, Germany. Data acquisition includes sociodemographic, medical and psychosocial data as well as information on current smoking patterns. To identify the associations between smoking patterns and sociodemographic characteristics, disease-related variables, and psychological risk factors, descriptive statistics and multiple logistic as well as multinomial regressions will be performed.

ETHICS AND DISSEMINATION

This study was registered at Open Science Framework (https://doi.org/10.17605/OSF.IO/PGBY8). It was approved by the ethics committee of the local psychological Ethic committee at the centre of psychosocial medicine Hamburg, Germany (LPEK) (tracking number: LPEK-0212). The study will be carried out in accordance with the Code of Ethics of the Declaration of Helsinki. The results will be published in peer-reviewed scientific journals.

Building staff capability, opportunity, and motivation to provide smoking cessation to people with cancer in Australian cancer treatment centres: development of an implementation intervention framework for the Care to Quit cluster randomised controlled trial

Few rigorous studies provide a clear description of the methodological approach of developing an evidence-based implementation intervention, prior to implementation at scale. This study describes the development, mapping, rating, and review of the implementation strategies for the Care to Quit smoking cessation trial, prior to application in nine cancer services across Australia. Key stakeholders were engaged in the process from conception through to rating, reviewing and refinement of strategies and principles. An initial scoping review identified 21 barriers to provision of evidence-based smoking cessation care to patients with cancer, which were mapped to the Theoretical Domains Framework and Behaviour Change Wheel (BCW) to identify relevant intervention functions. The mapping identified 26 relevant behaviour change techniques, summarised into 11 implementation strategies. The implementation strategies were rated and reviewed against the BCW Affordability, Practicality, Effectiveness and cost-effectiveness, Acceptability, Side-effects/safety, and Equity criteria by key stakeholders during two interactive workshops to facilitate a focus on feasible interventions likely to resonate with clinical staff. The implementation strategies and associated intervention tools were then collated by form and function to provide a practical guide for implementing the intervention. This study illustrates the rigorous use of theories and frameworks to arrive at a practical intervention guide, with potential to inform future replication and scalability of evidence-based implementation across a range of health service settings.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10742-022-00288-6.

Effectiveness, Cost-effectiveness, and Cost-Utility of a Digital Smoking Cessation Intervention for Cancer Survivors: Health Economic Evaluation and Outcomes of a Pragmatic Randomized Controlled Trial

Background

Smoking cessation (SC) interventions may contribute to better treatment outcomes and the general well-being of cancer survivors.

Objective

This study aims to evaluate the effectiveness, cost-effectiveness, and cost-utility of a digital interactive SC intervention compared with a noninteractive web-based information brochure for cancer survivors.

Methods

A health economic evaluation alongside a pragmatic 2-arm parallel-group randomized controlled trial was conducted with follow-ups at 3, 6, and 12 months. The study was conducted in the Netherlands over the internet from November 2016 to September 2019. The participants were Dutch adult smoking cancer survivors with the intention to quit smoking. In total, 165 participants were included and analyzed: 83 (50.3%) in the MyCourse group and 82 (49.7%) in the control group. In the intervention group, participants had access to a newly developed, digital, minimally guided SC intervention (MyCourse-Quit Smoking). Control group participants received a noninteractive web-based information brochure on SC. Both groups received unrestricted access to usual care. The primary outcome was self-reported 7-day smoking abstinence at the 6-month follow-up. Secondary outcomes were quality-adjusted life years gained, number of cigarettes smoked, nicotine dependence, and treatment satisfaction. For the health economic evaluation, intervention costs, health care costs, and costs stemming from productivity losses were assessed over a 12-month horizon.

Results

At the 6-month follow-up, the quit rates were 28% (23/83) and 26% (21/82) in the MyCourse and control groups, respectively (odds ratio 0.47, 95% CI 0.03-7.86; P=.60). In both groups, nicotine dependence scores were reduced at 12 months, and the number of smoked cigarettes was reduced by approximately half. The number of cigarettes decreased more over time, and the MyCourse group demonstrated a significantly greater reduction at the 12-month follow-up (incidence rate ratio 0.87; 95% CI 0.76-1.00; P=.04). Intervention costs were estimated at US $193 per participant for the MyCourse group and US $74 for the control group. The mean per-participant societal costs were US $25,329 (SD US $29,137) and US $21,836 (SD US $25,792), respectively. In the cost-utility analysis, MyCourse was not preferred over the control group from a societal perspective. With smoking behavior as the outcome, the MyCourse group led to marginally better results per reduced pack-year against higher societal costs, with a mean incremental cost-effectiveness ratio of US $52,067 (95% CI US $32,515-US $81,346).

Conclusions

At 6 months, there was no evidence of a differential effect on cessation rates; in both groups, approximately a quarter of the cancer survivors quit smoking and their number of cigarettes smoked was reduced by half. At 12 months, the MyCourse intervention led to a greater reduction in the number of smoked cigarettes, albeit at higher costs than for the control group. No evidence was found for a differential effect on quality-adjusted life years.

Trial Registration

The Netherlands Trial Register NTR6011; https://www.trialregister.nl/trial/5434

International Registered Report Identifier (IRRID)

RR2-10.1186/s12885-018-4206-z

Impact of deep learning-determined smoking status on mortality of cancer patients: never too late to quit

Background

Persistent smoking after cancer diagnosis is associated with increased overall mortality (OM) and cancer mortality (CM). According to the 2020 Surgeon General's report, smoking cessation may reduce CM but supporting evidence is not wide. Use of deep learning-based modeling that enables universal natural language processing of medical narratives to acquire population-based real-life smoking data may help overcome the challenge. We assessed the effect of smoking status and within-1-year smoking cessation on CM by an in-house adapted freely available language processing algorithm.

Materials and methods

This cross-sectional real-world study included 29 823 patients diagnosed with cancer in 2009-2018 in Southwest Finland. The medical narrative, International Classification of Diseases-10th edition codes, histology, cancer treatment records, and death certificates were combined. Over 162 000 sentences describing tobacco smoking behavior were analyzed with ULMFiT and BERT algorithms.

Results

The language model classified the smoking status of 23 031 patients. Recent quitters had reduced CM [hazard ratio (HR) 0.80 (0.74-0.87)] and OM [HR 0.78 (0.72-0.84)] compared to persistent smokers. Compared to never smokers, persistent smokers had increased CM in head and neck, gastro-esophageal, pancreatic, lung, prostate, and breast cancer and Hodgkin's lymphoma, irrespective of age, comorbidities, performance status, or presence of metastatic disease. Increased CM was also observed in smokers with colorectal cancer, men with melanoma or bladder cancer, and lymphoid and myeloid leukemia, but no longer independently of the abovementioned covariates. Specificity and sensitivity were 96%/96%, 98%/68%, and 88%/99% for never, former, and current smokers, respectively, being essentially the same with both models.

Conclusions

Deep learning can be used to classify large amounts of smoking data from the medical narrative with good accuracy. The results highlight the detrimental effects of persistent smoking in oncologic patients and emphasize that smoking cessation should always be an essential element of patient counseling.

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Deep learning/universal language modeling was used to extract smoking status of cancer patients. Good accuracy was observed.

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Those who continue smoking after cancer diagnosis had increased CM compared to never smokers.

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Recent within-1-year cessation reduced this mortality.

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Detrimental effects of smoking were observed in multiple types of early- and advanced-stage cancers, including the elderly.

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We conclude that smoking cessation support should always be included in cancer care.