Dataset Information

Effects of Personalized Risk Information on Patients Referred for Lung Cancer Screening with Low-Dose CT.

ABSTRACT: Background. Low-dose computed tomography (LDCT) screening for lung cancer is a preference-sensitive intervention that should ideally be individualized according to patients' likelihood of benefit and personal values. Personalized cancer risk information (PCRI) may facilitate this goal, but its effects are unknown. Objective. To evaluate the effects of providing PCRI to patients referred for LDCT screening. Design. Mixed-methods, pre-post study using surveys administered to patients before and after provision of PCRI-calculated by the PLCOm2012 risk prediction model-in shared decision-making consultations, and postvisit qualitative interviews. Setting. Centralized specialty-based LDCT screening program at a tertiary care hospital. Participants. Convenience sample of eligible patients referred for LDCT screening. Measurements. Pre- and postvisit surveys assessed patients' 1) perceived lung cancer risk, 2) uncertainty about their risk, 3) minimum risk threshold for wanting screening, 4) interest in LDCT screening, and 5) interest in smoking cessation. Qualitative interviews explored patients' perceptions of the value of PCRI. Screening uptake was assessed by chart review. Results. Sixty of 70 (86%) patients received PCRI and completed pre-post surveys, and 17 patients (28%) completed qualitative interviews. Perceived lung cancer risk decreased from 52% previsit to 31% postvisit (P < 0.0001). However, patients' minimum risk thresholds for screening decreased, their screening interest increased, and all patients completed screening. Qualitative interviews corroborated these effects, suggesting that patients discount and interpret PCRI according to preexisting beliefs and attitudes. Limitations. The study population was a relatively small, single-institution sample of patients referred for screening. Conclusions. Personalized cancer risk information decreases cancer risk perceptions of patients referred for LDCT screening, but has complex effects on screening-related judgments and decisions. The value of PCRI for patients considering LDCT screening requires further investigation.

SUBMITTER: Han PKJ

PROVIDER: S-EPMC7335264 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Effects of Personalized Risk Information on Patients Referred for Lung Cancer Screening with Low-Dose CT.

Han Paul K J PKJ Lary Christine C Black Adam A Gutheil Caitlin C Mandeville Hayley H Yahwak Jason J Fukunaga Mayuko M

Medical decision making : an international journal of the Society for Medical Decision Making 20191020 8

Background. Low-dose computed tomography (LDCT) screening for lung cancer is a preference-sensitive intervention that should ideally be individualized according to patients' likelihood of benefit and personal values. Personalized cancer risk information (PCRI) may facilitate this goal, but its effects are unknown. Objective. To evaluate the effects of providing PCRI to patients referred for LDCT screening. Design. Mixed-methods, pre-post study using surveys administered to p ...[more]

PMID: 31631776

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Project description:BACKGROUND:In the National Lung Screening Trial (NLST), screening with low-dose computed tomography (CT) resulted in a 20% reduction in lung-cancer mortality among participants between the ages of 55 and 74 years with a minimum of 30 pack-years of smoking and no more than 15 years since quitting. It is not known whether the benefits and potential harms of such screening vary according to lung-cancer risk. METHODS:We assessed the variation in efficacy, the number of false positive results, and the number of lung-cancer deaths prevented among 26,604 participants in the NLST who underwent low-dose CT screening, as compared with the 26,554 participants who underwent chest radiography, according to the quintile of 5-year risk of lung-cancer death (ranging from 0.15 to 0.55% in the lowest-risk group [quintile 1] to more than 2.00% in the highest-risk group [quintile 5]). RESULTS:The number of lung-cancer deaths per 10,000 person-years that were prevented in the CT-screening group, as compared with the radiography group, increased according to risk quintile (0.2 in quintile 1, 3.5 in quintile 2, 5.1 in quintile 3, 11.0 in quintile 4, and 12.0 in quintile 5; P=0.01 for trend). Across risk quintiles, there were significant decreasing trends in the number of participants with false positive results per screening-prevented lung-cancer death (1648 in quintile 1, 181 in quintile 2, 147 in quintile 3, 64 in quintile 4, and 65 in quintile 5). The 60% of participants at highest risk for lung-cancer death (quintiles 3 through 5) accounted for 88% of the screening-prevented lung-cancer deaths and for 64% of participants with false positive results. The 20% of participants at lowest risk (quintile 1) accounted for only 1% of prevented lung-cancer deaths. CONCLUSIONS:Screening with low-dose CT prevented the greatest number of deaths from lung cancer among participants who were at highest risk and prevented very few deaths among those at lowest risk. These findings provide empirical support for risk-based targeting of smokers for such screening. (Funded by the National Cancer Institute.).

Project description:BackgroundRandomized controlled trials have evaluated the efficacy of low-dose CT (LDCT) lung cancer screening on lung cancer (LC) outcomes.ObjectiveMeta-analyze LDCT lung cancer screening trials.MethodsWe identified studies by searching PubMed, Google Scholar, the Cochrane Registry, ClinicalTrials.gov , and reference lists from retrieved publications. We abstracted data on study design features, stage I LC diagnoses, LC and overall mortality, false positive results, harm from invasive diagnostic procedures, overdiagnosis, and significant incidental findings. We assessed study quality using the Cochrane risk-of-bias tool. We used random-effects models to calculate relative risks and assessed effect modulators with subgroup analyses and meta-regression.ResultsWe identified 9 studies that enrolled 96,559 subjects. The risk of bias across studies was judged to be low. Overall, LDCT screening significantly increased the detection of stage I LC, RR = 2.93 (95% CI, 2.16-3.98), I2 = 19%, and reduced LC mortality, RR = 0.84 (95% CI, 0.75-0.93), I2 = 0%. The number needed to screen to prevent an LC death was 265. Women had a lower risk of LC death (RR = 0.69, 95% CI, 0.40-1.21) than men (RR = 0.86, 95% CI, 0.66-1.13), p value for interaction = 0.11. LDCT screening did not reduce overall mortality, RR = 0.96 (95% CI, 0.91-1.01), I2 = 0%. The pooled false positive rate was 8% (95% CI, 4-18); subjects with false positive results had < 1 in 1000 risk of major complications following invasive diagnostic procedures. The most valid estimates for overdiagnosis and significant incidental findings were 8.9% and 7.5%, respectively.DiscussionLDCT screening significantly reduced LC mortality, though not overall mortality, with women appearing to benefit more than men. The estimated risks for false positive results, screening complications, overdiagnosis, and incidental findings were low. Long-term survival data were available only for North American and European studies limiting generalizability.

Project description:BackgroundRelatively little is known about various aspects of low-dose CT (LDCT) scan lung cancer screening in US clinical practice, including characteristics of cases diagnosed after screening. We assessed this using the Surveillance, Epidemiology, and End Results (SEER)-Medicare database.Research questionWhat were the characteristics of patients with lung cancer, including stage and survival, whose disease was diagnosed after LDCT scan screenings?Study design and methodsWe created an LDCT scan use cohort consisting of everyone in the 5% SEER-Medicare sample with ≥ 12 months of non-health maintenance organization (HMO) Part A and B coverage while 65 to 77 years of age from 2015 through 2019. LDCT scan use and lung cancer diagnosis rates were assessed in this cohort. Additionally, we created a lung cancer cohort consisting of patients who received a diagnosis between 2015 and 2017 at 65 to 78 years of age with complete (non-HMO Part A and B) coverage the year before diagnosis. The cases cohort comprised those screened or unscreened based on undergoing screening during that period; lung cancer characteristics and survival were compared between these groups.ResultsIn the LDCT scan use cohort (n = 414,358), use rates increased from 0.10 (per 100 person-years) in 2015 to 1.3 in 2019. Among those with first screenings, 39.2% underwent a subsequent screen within 18 months. The 1-year cumulative lung cancer diagnosis rate after initial screenings was 2.4%. Claims for prescreen counseling were infrequent (about 10%). Of 48,891 patients in the lung cancer cohort, 1,150 (2.4%) underwent screening. Among screened patients, 52.3%, 11.0%, 20.7%, and 16.0% received diagnoses of stages I, II, III, and IV disease, respectively. Lung cancer-specific survival through 3 years was significantly greater in screened versus unscreened patients overall and for all stages except stage II; 3-year lung cancer-specific survival was 89.0% in screened patients with stage I disease.InterpretationLDCT scan use was low but increased over time. The lung cancer yield was substantial; cases among those who underwent screening primarily were in the early stage with high survival rates. Although screening rates were unacceptably low, screening outcomes in those Medicare recipients undergoing screening were favorable.

Project description:Background:Previous studies of psychological burden in low-dose CT (LDCT) lung cancer screening trials may lack generalisability due to participation bias and control arms having elevated distress.Methods:Current and former smokers (n=787, aged 60-75) within a real-world screening demonstration pilot completed measures of lung cancer worry at three time points (T0: appointment, T1: next day, T2: 3 months) and anxiety and depression at two time points (T0 and T2). A 'screening unaware' community sample (n=383) with the same age and smoking characteristics completed these measures once (T0). Mean scores were compared by sample type and LDCT result.Results:Compared with the community sample (T0), mean scores were higher in the screening sample, and statistically significantly increased in adjusted analyses, for lung cancer worry at T0 and T2 (mean (M): 9.32; 95% CI 8.96 to 9.69 vs M: 11.34; 11.09 to 11.59 and M: 11.88; 11.49 to 12.27), for anxiety at T0 and T2 (M: 3.32; 2.94 to 3.70 vs M: 4.73; 4.42 to 5.04 and M: 5.78; 5.33 to 6.23) and depression at T2 (M: 3.85; 3.44 to 4.27 vs M: 4.15; 3.76 to 4.55). Scores were highest for those with indeterminate (eg, T2 anxiety M: 6.93; 5.65 to 8.21) and incidental findings (primary care follow-up M: 5.34; 4.67 to 6.02) and those ineligible for screening (M: 6.51; 5.25 to 7.77). Being female, younger, not in paid employment, not married/cohabiting with a partner and lower education predicted poorer psychological outcomes at T0, but not T2 after adjusting for baseline scores. Mean scores remained within 'normal' clinical ranges.Conclusion:Psychological distress was raised among high-risk individuals undergoing LDCT screening in a real-world setting, but overall differences were unlikely to be clinically meaningful. It will be critical to monitor the psychological impact of services longitudinally across diverse settings, including subgroups vulnerable to clinically elevated distress.Trial registration:The Lung Screen Uptake Trial was registered prospectively with the International Standard Registered Clinical/soCial sTudy (ISRCTN) (Number: ISRCTN21774741) on 23 September 2015 and the National Institutes of Health ClinicalTrials.gov database (NCT02558101) on 22 September 2015.

Project description:PurposeLow-dose CT screening allows early lung cancer detection, but is affected by frequent false positive results, inter/intra observer variation and uncertain diagnoses of lung nodules. Radiomics-based models have recently been introduced to overcome these issues, but limitations in demonstrating their generalizability on independent datasets are slowing their introduction to clinic. The aim of this study is to evaluate two radiomics-based models to classify malignant pulmonary nodules in low-dose CT screening, and to externally validate them on an independent cohort. The effect of a radiomics features harmonization technique is also investigated to evaluate its impact on the classification of lung nodules from a multicenter data.MethodsPulmonary nodules from two independent cohorts were considered in this study; the first cohort (110 subjects, 113 nodules) was used to train prediction models, and the second cohort (72 nodules) to externally validate them. Literature-based radiomics features were extracted and, after feature selection, used as predictive variables in models for malignancy identification. An in-house prediction model based on artificial neural network (ANN) was implemented and evaluated, along with an alternative model from the literature, based on a support vector machine (SVM) classifier coupled with a least absolute shrinkage and selection operator (LASSO). External validation was performed on the second cohort to evaluate models' generalization ability. Additionally, the impact of the Combat harmonization method was investigated to compensate for multicenter datasets variabilities. A new training of the models based on harmonized features was performed on the first cohort, then tested separately on the harmonized and non-harmonized features of the second cohort.ResultsPreliminary results showed a good accuracy of the investigated models in distinguishing benign from malignant pulmonary nodules with both sets of radiomics features (i.e., non-harmonized and harmonized). The performance of the models, quantified in terms of Area Under the Curve (AUC), was > 0.89 in the training set and > 0.82 in the external validation set for all the investigated scenarios, outperforming the clinical standard (AUC of 0.76). Slightly higher performance was observed for the SVM-LASSO model than the ANN in the external dataset, although they did not result significantly different. For both harmonized and non-harmonized features, no statistical difference was found between Receiver operating characteristic (ROC) curves related to training and test set for both models.ConclusionsAlthough no significant improvements were observed when applying the Combat harmonization method, both in-house and literature-based models were able to classify lung nodules with good generalization to an independent dataset, thus showing their potential as tools for clinical decision-making in lung cancer screening.

Dataset Information

Effects of Personalized Risk Information on Patients Referred for Lung Cancer Screening with Low-Dose CT.

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Effects of Personalized Risk Information on Patients Referred for Lung Cancer Screening with Low-Dose CT.

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