Learning curve in robotic-assisted lobectomy for non-small cell lung cancer is not steep after experience in video-assisted lobectomy; single-surgeon experience using cumulative sum analysis

Andersson, Saana; Ilonen, Ilkka; Pälli, Otto H.; Salo, Jarmo A.; Räsänen, Jari

doi:10.1016/j.ctarc.2021.100362

Cited by 10 publications

(9 citation statements)

References 28 publications

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“…CUSUM analysis was utilized for five studies ( 13 , 15 , 18 , 21 , 29 ), whereas other studies report trendline regression (similar in principle to CUSUM) ( 9 ) or plateaus in improvement across specific outcomes ( 10 - 12 , 19 ). To the author’s knowledge, there are no means of aggregating these statistical methods, other than through accepting their individual constraints, and aggregating them as a whole.…”

Section: Discussionmentioning

confidence: 99%

“…The majority of studies (twelve) were drawn from North America, with the remainder from Europe (three), China (three), Japan (two) Korea (one) and the Middle East (one). Upon quality assessment, twelve studies were deemed to be of high quality (9,13,(15)(16)(17)(19)(20)(21)(22)25,26,29), nine of medium quality (10,11,14,18,23,24,27,28,30) and one of low quality (12). Risk of bias assessment illustrated low-risk in the majority of studies, with only four demonstrating minor concerns (11,23,28,30) (see Figure S2).…”

Section: Study Characteristicsmentioning

confidence: 99%

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The learning curve of the robotic-assisted lobectomy—a systematic review and meta-analysis

Wilson-Smith¹,

Anning²,

Muston³

et al. 2023

Ann Cardiothorac Surg

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Background Early studies have illustrated the robotic lobectomy to be safe, oncologically effective, and economically feasible as a therapeutic modality in the treatment of thoracic malignancies. The ‘challenging’ learning curve seemingly associated with the robotic approach, however, continues to be an often-cited factor to its ongoing uptake, with the overwhelming volume of these surgeries being performed in centers of excellence where extensive experience with minimal access surgery is the norm. An exact quantification of this learning curve challenge, however, has not been made, begging the question of whether this is an outdated assumption, versus fact. This systematic review and meta-analysis sort to clarify the learning curve for robotic-assisted lobectomy based on the existing literature. Methods An electronic search of four databases was performed to identify relevant studies outlining the learning curve of robotic lobectomy. The primary endpoint was a clear definition of operator learning (e.g., cumulative sum chart, linear regression, outcome-specific analysis, etc.) which could be subsequently aggregated or reported. Secondary endpoints of interest included post-operative outcomes and complication rates. A meta-analysis using a random effects model of proportions or means was applied, as appropriate. Results The search strategy identified twenty-two studies relevant for inclusion. A total of 3,246 patients (30% male) receiving robotic-assisted thoracic surgery (RATS) were identified. The mean age of the cohort was 65.3±5.0 years. Mean operative, console and dock time was 190.5±53.8, 125.8±33.9 and 10.2±4.0 minutes, respectively. Length of hospital stay was 6.1±4.6 days. Technical proficiency with the robotic-assisted lobectomy was achieved at a mean of 25.3±12.6 cases. Conclusions The robotic-assisted lobectomy has been illustrated to have a reasonable learning curve profile based on the existing literature. Current evidence on the oncologic efficacy and purported benefits of the robotic approach will be bolstered by the results of upcoming randomized trials, which will be critical in supporting RATS uptake.

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Section: Discussionmentioning

confidence: 99%

Section: Study Characteristicsmentioning

confidence: 99%

The learning curve of the robotic-assisted lobectomy—a systematic review and meta-analysis

Wilson-Smith¹,

Anning²,

Muston³

et al. 2023

Ann Cardiothorac Surg

View full text Add to dashboard Cite

show abstract

“…The learning curve of robotic lobectomy has already been the subject of evaluation, since 2002 [ 12 ] when Veronesi et al reported that the learning phase for the technique included the first 18 cases. Following the most recent literature, we realize that the acquisition of competence and effectiveness (learning curve) in robotic lobectomy occurs after at least 14 cases [ 19 ] and ranges between 14 and 60 cases in the various reports [ 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 ].…”

Section: Discussionmentioning

confidence: 99%

“…Up to now, a number of studies have systematically analyzed the learning curve of minimally invasive (VATS or RATS) lobectomy [ 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 ]; all of these papers considered different parameters concerning the quality, the effectiveness and the radicality of the surgical act. So far, no studies have focused on the surgeon’s wellness and comfort during the surgical act.…”

Section: Introductionmentioning

confidence: 99%

Learning Curve of Robotic Lobectomy for the Treatment of Lung Cancer: How Does It Impact on the Autonomic Nervous System of the Surgeon?

Mazzella

Mohamed

Maisonneuve

et al. 2023

JPM

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Objective: Our purpose is to define the learning curve for robot-assisted thoracoscopic surgery lobectomy by reporting the experience of a single surgeon. Material and methods: We progressively collected the data concerning the surgical performance of a single male thoracic surgeon, from the beginning of his robotic activity as first operator from January 2021 to June 2022. We evaluated several pre-, intra- and postoperative parameters concerning patients and intraoperative cardiovascular and respiratory outcomes of the surgeon, recorded during surgical interventions, in order to evaluate his cardiovascular stress. We used cumulative sum control charts (CUSUM) to analyze the learning curve. Results: A total of 72 lung lobectomies were performed by a single surgeon in this period. Analyzing the CUSUM of several parameters, the inflection point identifying the transition beyond the surgeon learning phase was reached at cases 28, 22, 27 and 33 when considering operating time, mean heart rate, max heart rate and mean respiratory rate, respectively. Conclusions: The learning curve for robotic lobectomy seems to be safe and feasible with a correct robotic training program. The analysis of a single surgeon from the beginning of his robotic activity demonstrates that confidence, competence, dexterity and security are achieved after about 20–30 procedures, without compromising efficiency and oncological radicality.

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“…The previous literature consistently showed a lower conversion rate for RATS than for VATS [15,16]. Furthermore, the maximal utilization of robotic techniques makes it possible to perform sleeve resection with decreased bleeding loss, early tube removal, shorter operative time, and similar survival compared to VATS and thoracotomy [17][18][19].…”

Section: Discussionmentioning

confidence: 99%

Early Outcomes of Robotic Versus Video-Assisted Thoracoscopic Anatomical Resection for Lung Cancer

Park

Kang

et al. 2022

J Chest Surg

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Background:We compared the safety and effectiveness of robotic anatomical resection and video-assisted thoracoscopic surgery (VATS). Methods: A retrospective analysis was conducted of the records of 4,283 patients, in whom an attempt was made to perform minimally invasive anatomical resection for lung cancer at Seoul National University Hospital from January 2011 to July 2020. Of these patients, 138 underwent robotic surgery and 4,145 underwent VATS. Perioperative outcomes were compared after propensity score matching including age, sex, height, weight, pulmonary function, smoking status, performance status, comorbidities, type of resection, combined bronchoplasty/angioplasty, tumor size, clinical T/N category, histology, and neoadjuvant treatment. Results: In total, 137 well-balanced pairs were obtained. There were no cases of 30-day mortality in the entire cohort. Conversion to thoracotomy was required more frequently in the VATS group (VATS 6.6% vs. robotic 0.7%, p=0.008). The complete resection rate (VATS 97.8% vs. robotic 98.5%, p=1.000) and postoperative complication rate (VATS 17.5% vs. robotic 19.0%, p=0.874) were not significantly different between the 2 groups. The robotic group showed a slightly shorter hospital stay (VATS 5.8±3.9 days vs. robotic 5.0±3.6 days, p=0.052). N2 nodal upstaging (cN0/pN2) was more common in the robotic group than the VATS group, but without statistical significance (VATS 4% vs. robotic 12%, p=0.077). Conclusion: Robotic anatomical resection in lung cancer showed comparable early outcomes when compared to VATS. In particular, robotic resection presented a lower conversion-to-thoracotomy rate. Furthermore, a robotic approach might improve lymph node harvesting in the N2 station.

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Learning curve in robotic-assisted lobectomy for non-small cell lung cancer is not steep after experience in video-assisted lobectomy; single-surgeon experience using cumulative sum analysis

Cited by 10 publications

References 28 publications

The learning curve of the robotic-assisted lobectomy—a systematic review and meta-analysis

The learning curve of the robotic-assisted lobectomy—a systematic review and meta-analysis

Learning Curve of Robotic Lobectomy for the Treatment of Lung Cancer: How Does It Impact on the Autonomic Nervous System of the Surgeon?

Early Outcomes of Robotic Versus Video-Assisted Thoracoscopic Anatomical Resection for Lung Cancer

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