Uraujh Yousaf-Khan

Detection of lung cancer through low-dose CT screening (NELSON): a prespecified analysis of screening test performance and interval cancers

BACKGROUND Low-dose CT screening is recommended for individuals at high risk of developing lung cancer. However, CT screening does not detect all lung cancers: some might be missed at screening, and others can develop in the interval between screens. The NELSON trial is a randomised trial to assess the effect of screening with increasing screening intervals on lung cancer mortality. In this prespecified analysis, we aimed to assess screening test performance, and the epidemiological, radiological, and clinical characteristics of interval cancers in NELSON trial participants assigned to the screening group. METHODS Eligible participants in the NELSON trial were those aged 50-75 years, who had smoked 15 or more cigarettes per day for more than 25 years or ten or more cigarettes for more than 30 years, and were still smoking or had quit less than 10 years ago. We included all participants assigned to the screening group who had attended at least one round of screening. Screening test results were based on volumetry using a two-step approach. Initially, screening test results were classified as negative, indeterminate, or positive based on nodule presence and volume. Subsequently, participants with an initial indeterminate result underwent follow-up screening to classify their final screening test result as negative or positive, based on nodule volume doubling time. We obtained information about all lung cancer diagnoses made during the first three rounds of screening, plus an additional 2 years of follow-up from the national cancer registry. We determined epidemiological, radiological, participant, and tumour characteristics by reassessing medical files, screening CTs, and clinical CTs. The NELSON trial is registered at www.trialregister.nl, number ISRCTN63545820. FINDINGS 15,822 participants were enrolled in the NELSON trial, of whom 7915 were assigned to low-dose CT screening with increasing interval between screens, and 7907 to no screening. We included 7155 participants in our study, with median follow-up of 8·16 years (IQR 7·56-8·56). 187 (3%) of 7155 screened participants were diagnosed with 196 screen-detected lung cancers, and another 34 (<1%; 19 [56%] in the first year after screening, and 15 [44%] in the second year after screening) were diagnosed with 35 interval cancers. For the three screening rounds combined, with a 2-year follow-up, sensitivity was 84·6% (95% CI 79·6-89·2), specificity was 98·6% (95% CI 98·5-98·8), positive predictive value was 40·4% (95% CI 35·9-44·7), and negative predictive value was 99·8% (95% CI 99·8-99·9). Retrospective assessment of the last screening CT and clinical CT in 34 patients with interval cancer showed that interval cancers were not visible in 12 (35%) cases. In the remaining cases, cancers were visible when retrospectively assessed, but were not diagnosed because of radiological detection and interpretation errors (17 [50%]), misclassification by the protocol (two [6%]), participant non-compliance (two [6%]), and non-adherence to protocol (one [3%]). Compared with screen-detected cancers, interval cancers were diagnosed at more advanced stages (29 [83%] of 35 interval cancers vs 44 [22%] of 196 screen-detected cancers diagnosed in stage III or IV; p<0·0001), were more often small-cell carcinomas (seven [20%] vs eight [4%]; p=0·003) and less often adenocarcinomas (nine [26%] vs 102 [52%]; p=0·005). INTERPRETATION Lung cancer screening in the NELSON trial yielded high specificity and sensitivity, with only a small number of interval cancers. The results of this study could be used to improve screening algorithms, and reduce the number of missed cancers. FUNDING Zorgonderzoek Nederland Medische Wetenschappen and Koningin Wilhelmina Fonds.

Occurrence and lung cancer probability of new solid nodules at incidence screening with low-dose CT: analysis of data from the randomised, controlled NELSON trial

BACKGROUND US guidelines now recommend lung cancer screening with low-dose CT for high-risk individuals. Reports of new nodules after baseline screening have been scarce and are inconsistent because of differences in definitions used. We aimed to identify the occurrence of new solid nodules and their probability of being lung cancer at incidence screening rounds in the Dutch-Belgian Randomized Lung Cancer Screening Trial (NELSON). METHODS In the ongoing, multicentre, randomised controlled NELSON trial, between Dec 23, 2003, and July 6, 2006, 15 822 participants who had smoked at least 15 cigarettes a day for more than 25 years or ten cigarettes a day for more than 30 years and were current smokers, or had quit smoking less than 10 years ago, were enrolled and randomly assigned to receive either screening with low-dose CT (n=7915) or no screening (n=7907). From Jan 28, 2004, to Dec 18, 2006, 7557 individuals underwent baseline screening with low-dose CT; 7295 participants underwent second and third screening rounds. We included all participants with solid non-calcified nodules, registered by the NELSON radiologists as new or smaller than 15 mm(3) (study detection limit) at previous screens. Nodule volume was generated semiautomatically by software. We calculated the maximum volume doubling time for nodules with an estimated percentage volume change of 25% or more, representing the minimum growth rate for the time since the previous scan. Lung cancer diagnosis was based on histology, and benignity was based on histology or stable size for at least 2 years. The NELSON trial is registered at trialregister.nl, number ISRCTN63545820. FINDINGS We analysed data for participants with at least one solid non-calcified nodule at the second or third screening round. In the two incidence screening rounds, the NELSON radiologists registered 1222 new solid nodules in 787 (11%) participants. A new solid nodule was lung cancer in 49 (6%) participants with new solid nodules and, in total, 50 lung cancers were found, representing 4% of all new solid nodules. 34 (68%) lung cancers were diagnosed at stage I. Nodule volume had a high discriminatory power (area under the receiver operating curve 0·795 [95% CI 0·728-0·862]; p<0·0001). Nodules smaller than 27 mm(3) had a low probability of lung cancer (two [0·5%] of 417 nodules; lung cancer probability 0·5% [95% CI 0·0-1·9]), nodules with a volume of 27 mm(3) up to 206 mm(3) had an intermediate probability (17 [3·1%] of 542 nodules; lung cancer probability 3·1% [1·9-5·0]), and nodules of 206 mm(3) or greater had a high probability (29 [16·9%] of 172 nodules; lung cancer probability 16·9% [12·0-23·2]). A volume cutoff value of 27 mm(3) or greater had more than 95% sensitivity for lung cancer. INTERPRETATION Our study shows that new solid nodules are detected at each screening round in 5-7% of individuals who undergo screening for lung cancer with low-dose CT. These new nodules have a high probability of malignancy even at a small size. These findings should be considered in future screening guidelines, and new solid nodules should be followed up more aggressively than nodules detected at baseline screening. FUNDING Zorgonderzoek Nederland Medische Wetenschappen and Koningin Wilhelmina Fonds Kankerbestrijding.

Final screening round of the NELSON lung cancer screening trial: the effect of a 2.5-year screening interval

Background In the USA annual lung cancer screening is recommended. However, the optimal screening strategy (eg, screening interval, screening rounds) is unknown. This study provides results of the fourth screening round after a 2.5-year interval in the Dutch-Belgian Lung Cancer Screening trial (NELSON). Methods Europes largest, sufficiently powered randomised lung cancer screening trial was designed to determine whether low-dose CT screening reduces lung cancer mortality by ≥25% compared with no screening after 10 years of follow-up. The screening arm (n=7915) received screening at baseline, after 1 year, 2 years and 2.5 years. Performance of the NELSON screening strategy in the final fourth round was evaluated. Comparisons were made between lung cancers detected in the first three rounds, in the final round and during the 2.5-year interval. Results In round 4, 46 cancers were screen-detected and there were 28 interval cancers between the third and fourth screenings. Compared with the second round screening (1-year interval), in round 4 a higher proportion of stage IIIb/IV cancers (17.3% vs 6.8%, p=0.02) and higher proportions of squamous-cell, bronchoalveolar and small-cell carcinomas (p=0.001) were detected. Compared with a 2-year interval, the 2.5-year interval showed a higher non-significant stage distribution (stage IIIb/IV 17.3% vs 5.2%, p=0.10). Additionally, more interval cancers manifested in the 2.5-year interval than in the intervals of previous rounds (28 vs 5 and 28 vs 19). Conclusions A 2.5-year interval reduced the effect of screening: the interval cancer rate was higher compared with the 1-year and 2-year intervals, and proportion of advanced disease stage in the final round was higher compared with the previous rounds. Trial registration number ISRCTN63545820.

Risk stratification based on screening history: the NELSON lung cancer screening study

Background Debate about the optimal lung cancer screening strategy is ongoing. In this study, previous screening history of the Dutch-Belgian Lung Cancer Screening trial (NELSON) is investigated on if it predicts the screening outcome (test result and lung cancer risk) of the final screening round. Methods 15 792 participants were randomised (1:1) of which 7900 randomised into a screening group. CT screening took place at baseline, and after 1, 2 and 2.5 years. Initially, three screening outcomes were possible: negative, indeterminate or positive scan result. Probability for screening outcome in the fourth round was calculated for subgroups of participants. Results Based on results of the first three rounds, three subgroups were identified: (1) those with exclusively negative results (n=3856; 73.0%); (2) those with ≥1 indeterminate result, but never a positive result (n=1342; 25.5%); and (3) with ≥1 positive result (n=81; 1.5%). Group 1 had the highest probability for having a negative scan result in round 4 (97.2% vs 94.8% and 90.1%, respectively, p<0.001), and the lowest risk for detecting lung cancer in round 4 (0.6% vs 1.6%, p=0.001). ‘Smoked pack-years’ and ‘screening history’ significantly predicted the fourth round test result. The third round results implied that the risk for detecting lung cancer (after an interval of 2.5 years) was 0.6% for those with negative results compared with 3.7% of those with indeterminate results. Conclusions Previous CT lung cancer screening results provides an opportunity for further risk stratifications of those who undergo lung cancer screening. Trial registration number Results, ISRCTN63545820.

Quantification of growth patterns of screen-detected lung cancers: The NELSON study

OBJECTIVES Although exponential growth is assumed for lung cancer, this has never been quantified in vivo. Aim of this study was to evaluate and quantify growth patterns of lung cancers detected in the Dutch-Belgian low-dose computed tomography (CT) lung cancer screening trial (NELSON), in order to elucidate the development and progression of early lung cancer. MATERIALS AND METHODS Solid lung nodules found at ≥3 CT examinations before lung cancer diagnosis were included. Lung cancer volume (V) growth curves were fitted with a single exponential, expressed as V=V1 exp(t/τ), with t time from baseline (days), V1 estimated baseline volume (mm3), and τ estimated time constant. The R2 coefficient of determination was used to evaluate goodness of fit. Overall volume-doubling time for the individual lung cancer is given by τ*log(2). RESULTS Forty-seven lung cancers in 46 participants were included. Forty participants were male (87.0%); mean age was 61.7 years (standard deviation, 6.2 years). Median nodule size at baseline was 99.5mm3 (IQR: 46.8-261.8mm3). Nodules were followed for a median of 770 days (inter-quartile range: 383-1102 days) before lung cancer diagnosis. One cancer (2.1%) was diagnosed after six CT examinations, six cancers (12.8%) were diagnosed after five CTs, 14 (29.8%) after four CTs, and 26 cancers (55.3%) after three CTs. Lung cancer growth could be described by an exponential function with excellent goodness of fit (R2 0.98). Median overall volume-doubling time was 348 days (inter-quartile range: 222-492 days). CONCLUSION This study based on CT lung cancer screening provides in vivo evidence that growth of cancerous small-to-intermediate sized lung nodules detected at low-dose CT lung cancer screening can be described by an exponential function such as volume-doubling time.

Baseline Characteristics and Mortality Outcomes of Control Group Participants and Eligible Non-Responders in the NELSON Lung Cancer Screening Study.

Introduction: Individuals who are younger, have a high socioeconomic background and/or have a healthy lifestyle are more inclined to participate in screening trials. This form of bias may affect the generalizability of study results to the target population. This study aimed to investigate the generalizability of the NELSON lung cancer screening trial to the Dutch population. Methods: People at high risk for developing lung cancer were identified by sending a health questionnaire to 606,409 persons aged 50–74 years, based on population registries. Eligible subjects received an invitation to participate (n = 30,051). 15,822 subjects agreed to participate and were randomized, whereas 15,137 did not respond (so-called eligible nonresponders). Baseline characteristics and mortality profiles were compared between control group participants and eligible nonresponders. Results: Participants had better self-reported health (p = 0.02), were younger, more physically active, higher educated, and more often former smokers compared with eligible nonresponders (all p < 0.001). No differences were seen in self-reported outcomes of pulmonary tests, history of lung cancer, and smoked pack-years. Mortality due to all-causes (p < 0.001) and mortality classification separately was lower among participants. However, the proportion of subjects death due to cancer was higher among participants (62.4% vs. 54.9%). Conclusion: Modest differences in baseline characteristics between participants and eligible nonresponders, led to minor differences in mortality profiles. However, group sizes were large and therefore it seems unlikely that these small differences will influence the generalizability of the NELSON trial. Results of the NELSON trial can roughly be used to predict the effect of population-based lung cancer screening.

Relationship between nodule count and lung cancer probability in baseline CT lung cancer screening: The NELSON study

OBJECTIVES To explore the relationship between nodule count and lung cancer probability in baseline low-dose CT lung cancer screening. MATERIALS AND METHODS Included were participants from the NELSON trial with at least one baseline nodule (3392 participants [45% of screen-group], 7258 nodules). We determined nodule count per participant. Malignancy was confirmed by histology. Nodules not diagnosed as screen-detected or interval cancer until the end of the fourth screening round were regarded as benign. We compared lung cancer probability per nodule count category. RESULTS 1746 (51.5%) participants had one nodule, 800 (23.6%) had two nodules, 354 (10.4%) had three nodules, 191 (5.6%) had four nodules, and 301 (8.9%) had>4 nodules. Lung cancer in a baseline nodule was diagnosed in 134 participants (139 cancers; 4.0%). Median nodule count in participants with only benign nodules was 1 (Inter-quartile range [IQR]: 1-2), and 2 (IQR 1-3) in participants with lung cancer (p=NS). At baseline, malignancy was detected mostly in the largest nodule (64/66 cancers). Lung cancer probability was 62/1746 (3.6%) in case a participant had one nodule, 33/800 (4.1%) for two nodules, 17/354 (4.8%) for three nodules, 12/191 (6.3%) for four nodules and 10/301 (3.3%) for>4 nodules (p=NS). CONCLUSION In baseline lung cancer CT screening, half of participants with lung nodules have more than one nodule. Lung cancer probability does not significantly change with the number of nodules. Baseline nodule count will not help to differentiate between benign and malignant nodules. Each nodule found in lung cancer screening should be assessed separately independent of the presence of other nodules.

Characteristics of new solid nodules detected in incidence screening rounds of low-dose CT lung cancer screening: the NELSON study

Purpose New nodules after baseline are regularly found in low-dose CT lung cancer screening and have a high lung cancer probability. It is unknown whether morphological and location characteristics can improve new nodule risk stratification by size. Methods Solid non-calcified nodules detected during incidence screening rounds of the randomised controlled Dutch-Belgian lung cancer screening (NELSON) trial and registered as new or previously below detection limit (15 mm3) were included. A multivariate logistic regression analysis with lung cancer as outcome was performed, including previously established volume cut-offs (<30 mm3, 30–<200 mm3 and ≥200 mm3) and nodule characteristics (location, distribution, shape, margin and visibility <15 mm3 in retrospect). Results Overall, 1280 new nodules were included with 73 (6%) being lung cancer. Of nodules ≥30 mm3 at detection and visible <15 mm3 in retrospect, 22% (6/27) were lung cancer. Discrimination based on volume cut-offs (area under the receiver operating characteristic curve (AUC): 0.80, 95% CI 0.75 to 0.84) and continuous volume (AUC: 0.82, 95% CI 0.77 to 0.87) was similar. After adjustment for volume cut-offs, only location in the right upper lobe (OR 2.0, P=0.012), central distribution (OR 2.4, P=0.001) and visibility <15 mm3 in retrospect (OR 4.7, P=0.003) remained significant predictors for lung cancer. The Hosmer-Lemeshow test (P=0.75) and assessment of bootstrap calibration curves indicated adequate model fit. Discrimination based on the continuous model probability (AUC: 0.85, 95% CI 0.81 to 0.89) was superior to volume cut-offs alone, but when stratified into three risk groups (AUC: 0.82, 95% CI 0.78 to 0.86), discrimination was similar. Conclusion Contrary to morphological nodule characteristics, growth-independent characteristics may further improve volume-based new nodule lung cancer prediction, but in a three-category stratification approach, this is limited. Trial registration number ISRCTN63545820; pre-results.

Relationship between the number of new nodules and lung cancer probability in incidence screening rounds of CT lung cancer screening: The NELSON study

BACKGROUND New nodules are regularly found after the baseline round of low-dose computed tomography (LDCT) lung cancer screening. The relationship between a participants number of new nodules and lung cancer probability is unknown. METHODS Participants of the ongoing Dutch-Belgian Randomized Lung Cancer Screening (NELSON) Trial with (sub)solid nodules detected after baseline and registered as new by the NELSON radiologists were included. The correlation between a participants new nodule count and the largest new nodule size was assessed using Spearmans rank correlation. To evaluate the new nodule count as predictor for new nodule lung cancer together with largest new nodule size, a multivariable logistic regression analysis was performed. RESULTS In total, 705 participants with 964 new nodules were included. In 48% (336/705) of participants no nodule had been found previously during baseline screening and in 22% (154/705) of participants >1 new nodule was detected (range 1-12 new nodules). Eventually, 9% (65/705) of the participants had lung cancer in a new nodule. In 100% (65/65) of participants with new nodule lung cancer, the lung cancer was the largest or only new nodule at initial detection. The new nodule lung cancer probability did not differ significantly between participants with 1 (10% [56/551], 95%CI 8-13%) or >1 new nodule (6% [9/154], 95%CI 3-11%, P = .116). An increased number of new nodules positively correlated with a participants largest nodule size (P < 0.001, Spearmans rho 0.177). When adjusted for largest new nodule size, the new nodule count had a significant negative association with lung cancer (odds ratio 0.59, 0.37-0.95, P = .03). CONCLUSION A participants new nodule count alone only has limited association with lung cancer. However, a higher new nodule count correlates with an increased largest new nodule size, while the lung cancer probability remains equivalent, and may improve lung cancer risk prediction by size only.

New Subsolid Pulmonary Nodules in Lung Cancer Screening: The NELSON Trial

Introduction: Low‐dose computed tomography (LDCT) lung cancer screening is recommended in the United States. While new solid nodules after baseline screening have a high lung cancer probability at small size and require lower size cutoff values than baseline nodules, there only is limited evidence on management of new subsolid nodules. Methods: Within the Dutch‐Belgian randomized controlled LDCT lung cancer screening trial (NELSON), 7557 participants underwent baseline screening between April 2004 and December 2006. Participants with new subsolid nodules detected after the baseline screening round were included. Results: In the three incidence screening rounds, 60 new subsolid nodules (43 [72%] part‐solid, 17 [28%] nonsolid) not visible in retrospect were detected in 51 participants, representing 0.7% (51 of 7295) of participants with at least one incidence screening. Eventually, 6% (3 of 51) of participants with a new subsolid nodule were diagnosed with (pre‐)malignancy in such a nodule. All (pre‐)malignancies were adenocarcinoma (in situ) and diagnostic workup (referral 950, 364, and 366 days after first detection, respectively) showed favorable staging (stage I). Overall, 67% (33 of 49) of subsolid nodules with an additional follow‐up screening were resolving. Conclusions: Less than 1% of participants in LDCT lung cancer screening presents with a new subsolid nodule after baseline. Contrary to new solid nodules, data suggest that new subsolid nodules may not require a more aggressive follow‐up.