Learning curves for minimally invasive major lung resections: facts and action points!

Introduction: the reasons for and consequences of the steady raise of video-assisted thoracic surgery (VATS) and robot-assisted thoracic surgery (RATS)

Over the past 2 decades, minimally invasive approaches by VATS and RATS have increasingly been applied to major lung resections. The annual report of the European Society of Thoracic Surgeons (ESTS) database 2022 obviated that the percentage of VATS lobectomies rose from 9.7% in the period 2007–2013 to 49.9% in the period 2014–2021 (1). A similar swing has been observed on data from the United States National Cancer Database: in 2017, 40% of lobectomies were performed by VATS, 20% by RATS, and yet 40% by thoracotomy (2). After 2 decades of VATS being mostly performed through 3 or 4 ports following the triangulation principals of abdominal laparoscopy, over the last decade a second generation of minimally invasive surgical techniques have emerged and seem to slowly replace the initial VATS techniques (3). These aim at reducing the invasiveness by further reducing the number and size of ports or their relocation (e.g., sub-xyphoid and subcostal VATS). This happens as worldwide many still have not embraced “classical” VATS at all (1,2). The consequence is a large spectrum of learning needs: many established surgeons still need to learn minimally invasive techniques from scratch whereas others, more or less experienced in VATS, may explore switches from multi-port VATS to uniportal VATS or RATS (again either multi- or uniportal) while during the same time learn new advanced techniques such as segmentectomies or sleeve resections by VATS. At the same time young surgical trainees need to be trained from scratch. They seek training in VATS but need to get a sufficient exposure to conventional open surgery in order to be able to deal with intraoperative accidents and exceptional situations where VATS is not possible. As a result, universities and surgical training centers face a myriad of situations, and trainees with very different learning objectives.

This major change in surgical approach is not only due to technical improvements of supplies, but also in marketing and patient awareness. It appears also as consequence of the National Lung Screening Trial, which demonstrated the benefit of lung cancer screening in a population at risk (4). However, until today apart from Poland, no other country has yet established a formal governmental screening program (5), with the majority of pulmonary and general physicians confessing a “wild” screening amongst patients at risk (6). Hence, compared to former decades, surgical series are marked by an increasing proportion of early-stage lung cancers that further justify utilization of minimally invasive approaches. Completed randomized studies argument in favor of reduction of pain and complications, improved recovery with earlier discharge, improved physical function and earlier return to work, while preserving even oncologic outcome of VATS compared to thoracotomy (7-9).

However, the result in terms of surgical outcome parameters is not only due to smaller incisions. For instance, there is little difference proven in outcomes of RATS, where 5–6 incisions are required, compared to standard 3-port VATS or single-port VATS (10). We should stay aware that the global concept of perioperative care has undergone capital changes, not always formalized as a programmatic enhanced recovery track, that contribute to reduced complication rates and shorter hospital stays (10). Economic factors such as reduction of hospital beds and inherent nursing staff encourage utilization of minimally invasive approaches, even if the cost per procedure is increased with supplies and equipment. Cost and maintenance are considerably increased with RATS, in particular (11).

These major changes that incurred in surgical approach, impact on surgical training and create an additional challenge for training programs aiming to obtain an optimal competence level for their trainees. Contemporary training curricula need a flexible design and frequent revisions to match with the ever-growing innovative technology and changing perimeters of specialties. Methodology of training surgical skills needs to be adapted accordingly, considering the increasing complexity not only at the individual, but also at the team-level. Simulation training is a key player for the future where the classic “see one, do one, teach one” is no longer applicable. Assessment tools need to follow innovation, and there again the simulation setting should be considered (11,12).

Competition between trainees and trainers is an unforeseen additional challenge. The trainee enters the program with the endeavor to learn from inception the innovative approaches. However, there is a conflict with the confirmed consultant, who faces the triple challenge to learn before he can teach, to satisfy the demand of his patients, and to bear potential sources of pressure by social media, hospital administrators and even the industry (12) (Tables 1,2).

Within the learning process, one should not forget the institutional learning process. Efficient surgery requires team training to a different professional environment (11,13). Scrub nurses need to be familiarized with new instrumentation and devices. Assistants, residents, and fellows play a major role and need specific training. Anesthetists need to get aware of intraoperative peculiarities: while the management of double lumen intubation is widespread, other confounding factors appeared, such as thoracic CO₂ insufflation (14). In addition, alternative concepts have appeared such as non-intubated anesthesia, where the patient is breathing spontaneously under sedation (15). The whole team needs training for unforeseen intra-operative catastrophes to guarantee appropriate communication and handling (15). Other aspects concern management of post-operative analgesia and enhanced recovery after surgery programs, where floor nurses and physiotherapists are concerned on first line and need specific training (10).

Finally, the program should also be coordinated with the pharmacy and the administration to guarantee supply with equipment, instrumentation, and disposables.

To analyze all the potential aspects of learning to efficiently perform minimally invasive lung resections would extend beyond the possible scope of any single study. We investigated the literature on this topic in order to identify potential action-points and new training pathways while scrutinizing the specific surgical challenges that surgeons with various degrees of previous experience face when trying to learn any of the many available techniques for minimally invasive lung cancer resection.

Learning curves (LCs) in general

From a theoretical point of view, we expect a significant difference between a surgical trainee, starting from scratch, and a certified consultant moving to VATS or RATS after several hundreds or thousands of lung resections.

As mentioned, increasing sophistication of surgical techniques implies that the classic “see one, do one, teach one” is no longer applicable, because two different generations learn together at the same time (Table 3).

The trainee should take advantage of observing as many procedures as possible and set as the first goal to become comfortable with surgical anatomy. A second goal is learning appropriate utilization of tools and equipment. The experienced consultant has the advantage of knowing the anatomy and appropriate handling of tissues. While the thoracic consultant most often has had exposure to minor VATS procedures or laparoscopic surgery such as fundoplication, the trainee will take advantage to develop endoscopic surgical skills by practicing on a black box, where several exercises are available in the sense of the fundamental laparoscopic skills certification (16-18). Both the trainee and the consultant need to go through different steps, as outlined by the Copenhagen Group (Table 2), while the way may be shorter for the consultant.

Looking at reported statements, we may summarize to the following:

• The spectrum for trainees is broad, with estimates ranging from 50 to 200 cases (19). Determinant factors are the trainee’s inborn manual skills, previous experience in general surgery, volume of exposure, ability to observe senior surgeons and appropriate understanding of surgical anatomy.
• Consultants would need 30–50 cases to be familiar with the technique (19,20). Depending on previous experience with minor VATS or laparoscopic surgery, the switch to VATS from major resections may be facilitated.

However, the learning process cannot be reduced to a nude number of procedures. Competence is met as soon as a surgeon is reproducing an operation appropriately, matching with quality criteria. For major lung resections, lobectomies and anatomical segmentectomies, the time-honored goals to achieve are (I) individual dissection and transection of hilar structures and (II) complete homolateral node clearance. While operating time is the mostly used quality parameter taken into consideration as mark of mastering, other parameters should be considered: number of harvested nodes, blood loss, conversion rate, duration of drainage, complication rates and duration of hospital stay.

The definitions of “competency” and “proficiency” also require discussion. Li et al. provided a practical definition, with “competency” meaning to be able to perform a procedure safely and effectively, and “proficiency” being efficient and consistent in addition to being competent (21). Efficiency in this sense is defined as refining performance to decrease a target variable such as operating time, and consistency as eliminating outliers in terms of this target variable (22).

Despite hundreds of papers already published on LCs for various VATS and RATS techniques, the discussion on competency and proficiency remains active. Most available studies focus only on single-surgeon early experiences while studies that would explore sufficiently large databases to identify markers of proficiency or mastery are lacking. In other domains such as minimally invasive pancreatectomy large multi-institutional database studies showed that various signs of competence (e.g., conversion, operative durations, reduced blood loss) are reached at different points whereas a plateau in Text-Book outcome (TBO) is reached only after 84 distal pancreatectomies (23). Interestingly, this study found that for the complication of pancreatic fistula, no plateau was ever reached suggesting that some complications are more driven by patient characteristics than by any surgical experience. Distal pancreatectomy seems to us not to be technically more difficult than VATS lobectomy and thus one may assume that similar findings would be made if such studies were to be done for lung surgery.

LC: a deeper glance!

The lack of clear definitions and methods in the domain of LC analysis for surgical procedures is a limitation of the whole LC concept. Several approaches exist and previously published papers on surgical LC are very heterogenous in their definitions and techniques (24).

Most dedicated studies utilize the so-called CUSUM analysis to assess the LC. This acronym stands for “cumulative sum control chart”, a statistical method utilized for quality control. Briefly, the analysis detects changes in the mean value of a variable quality parameter among those mentioned above. A change in the mean, graphically represented in a time slope, indicates increase, stability or decrease of the quality parameter (24).

Alternatively, the Bayesian inference model has been utilized to compare variable quality markers (20).

In the most frequently statistical approach for CUSUM analysis, we expect in general a bimodal LC. It is usually stated that a first plateau is reached when the quality of the operation is reproducible (end of phase 1 or A of the learning process), attesting competence. A second plateau signing proficiency is reached when quality parameters of patient outcome such as operating time or duration of air leak are decreasing (end of phase 2 or B and beginning of phase 3 or C). As such, the typical CUSUM curve is dome shaped. The increasing part breaks at the level of competence; the horizontal part of the dome breaks at the level of proficiency. However, this frequently assessment tool should be considered with caution. There are various ways of reporting and analyzing cumulative sum methods with surgical LC data (21,24). It has been criticized that in the available literature on surgical LCs the use of CUSUM may not always have been statistically correct (25). The findings of individual studies may not be generalizable and the cut-off values thus should rather be used as guides rather than as precise cut-offs. Wooddall et al. provided a comprehensive review of the various statistical methods for CUSUM, but concluded that curve-fitting methods might be more suitable for the study of surgical LCs (25). While providing useful visual aids, they are often prone to overinterpretation and should be used with criticism.

It remains difficult to generate a general statement about the LC for trainees, which obviously depends on many factors such as individual abilities, case load, access to skills lab, and quality of coaching. On the opposite, there is some well-documented evidence of learning requirements for confirmed consultants.

Mazzella et al. evaluated the LC of an experienced senior consultant switching from open to VATS lobectomy on hands of the first 120 consecutive lobectomies (20). The latter were pooled by consecutive groups of 30 patients and compared with a Bayesian inference model to detect a significant difference between groups. Competence was defined as stability of number of lymph nodes harvested and was reached after the first 30 cases. Proficiency, defined as a consistent decline of operative time, duration of air leak, duration of drainage and hospital stay, was reached after 90 cases (20).

This bimodal LC has been confirmed in another study, analyzing the LC of an experienced 3-port VATS surgeon switching to uniportal VATS. The authors chose CUSUM analysis and outcome parameters were length of procedure, intra-operative blood loss, conversion rate (to 3-port or thoracotomy), and number of nodes retrieved. The level of competence was reached after 60 procedures; following a transition period covered by 80 additional cases, the level of proficiency was reached, for a total of 140 cases (26).

Another intriguing report on a single surgeon’s professional development with single-port VATS lobectomies demonstrated as previously the bimodal progression with a phase A leading to competence (estimated at 52 cases), a phase B leading to proficiency (estimated at a total of 152 cases) and a stable curve during phase C, when the CUSUM methodology had been applied to the 220 first cases. However, when considering the total experience of 550 cases, phase C leads to an additional inflexion after a total of 244 cases, followed by a phase D with a stable curve (27).

The same dynamics of the learning process are observed with VATS sleeve lobectomy screened with CUSUM analysis: the learning surgeon reached competence after 30, and proficiency after 90 procedures (28).

In addition, the performance of VATS segmentectomies bears an additional separate LC for those familiar with VATS lobectomies (29,30).

Taken all together, we may summarize that reaching a minimal competence level for lobectomies requires a minimal exposure to at least 30 procedures as an operating surgeon, but that real proficiency requires at least 80 to 90 such procedures with an additional LC hereafter for specific procedures such as difficult lower lobe segmentectomies (29,30). Hamada et al. reported that in a center where three surgeons performed 252 VATS segmentectomies over a 10-year period and despite large previous experience in open segmentectomies, it took the lead surgeon 3 years before his LC analysis showed signs of mastery (30). Thus, training in minimally thoracic surgery would need to be limited to high-volume centers that can guarantee sufficient exposure related to the duration of training. The question could be raised whether senior surgeons performing a low number of yearly lobectomies by thoracotomy per year, should switch to VATS: it would take them at least 2 years to perform such operations adequately. Although there is no proven threshold, we would empirically set one at 20 to 30. The point to be made here is the mere fact that if the senior surgeon himself needs 2 to 3 years to become proficient with VATS, how could he then enable trainees to become confident with the technique during a residency. This question equally addresses the switch from 3-portal to uniportal VATS—where evidence remains controversial (31) or from VATS to RATS (32,33). Finally, sleeve lobectomies are infrequent operations even in high-volume units (1). Is it ethically acceptable to potentially lower quality of surgery for training purposes? The current development of indications for anatomic segmentectomies unravels a similar problem.

LC does not only mirror individual surgeon’s progression, but also institutional experience. Lee et al. demonstrated that for a group of five surgeons switching to VATS, both number of nodes retrieved, and number of stations harvested increased in a bimodal progression, with a set-off at 100 procedures, followed by a second after 400 procedures (34). These dynamics were observed when considering all stages taken together, as well as for stage cTIA only (34). When analyzing progression of one single surgeon, the setoffs were identified once again at 30 and 90 procedures respectively. In this study, the learning process did not affect long-term survival: comparison of two even groups defined by the date of surgery (early group and late group) demonstrated similar survival (34).

CUSUM analysis may also be utilized as a way to audit proficiency of a department, as demonstrated by Puri et al. Data retrieved from the Society of Thoracic Surgeons database allowed to observe three different patterns of institutional CUSUM curves: a horizontal pattern of the curve ascertains that proficiency has been reached and is sustained; a dome-shaped shows that proficiency has been reached with increasing experience; an ascending curve shows that competence and/or proficiency have not yet been reached (35).

It is commonly stated that RATS has the advantage of a shorter LC. Two review articles indicated the number of 20 to 40 at least for surgeons with established VATS experience switching to RATS (33,36). However, this is finally in the same range than the 30 cases required to reach initial competence with VATS. The question if the LC is as forgiving for novices has not been studied in great depth.

Comparing their first 26 RATS to their 26 first VATS cases, Augustin et al. concluded that RATS differs by longer operating time, higher intraoperative blood loss, and increased cost (37). Lee et al. concluded that considering clinical outcomes, there is no significant advantage for an experienced VATS surgeon to switch to RATS and insist on a longer LC for upper lobectomies (38). Andersson et al. compared 75 first RATS lobectomies performed after 75 first VATS lobectomies in a single surgeon’s experience. LCs were evaluated by CUSUM analysis and proficiency was identified after 54 VATS lobectomies with a subsequent 45 cases needed for RATS competence (32). Previous VATS experience led to a significantly lower conversion rate in the RATS group, but all outcome parameters (mortality, complications, reoperations, length of stay) were similar. They concluded that RATS has a LC of its own regardless of previous surgical experience (32).

Another approach is evaluating the LC through its medico-economic impact. The total cost of RATS segmentectomy, considered as the sum of the cost per procedure due to disposables, and the cost per hospital stay, was analyzed in a CUSUM chart and identified a set-off after 30 procedures; CUSUM analysis of operating time identified the level of competence at 27 procedures and again a level of proficiency around 90 procedures (39). Finally, LC may also be analyzed through its impact on the autonomic nervous system of the surgeon. Mazzella et al. monitored cardiovascular stress of a surgeon by recording vital parameters such as pulse rate, respiratory rate, arterial pressure, temperature and oxygen saturation during the initial experience with RATS lobectomy. Once again, they identified a set-off close to 30 procedures (40).

Few studies have specifically addressed LC issues for surgeons moving directly from open surgery to RATS (41,42). One study from Japan suggested that the LC might be somewhat shorter for RATS than for VATS (42). Gallagher et al. reported that for a surgeon with open but no VATS lobectomy experience, the bi-modal curve was at least as long with 40 cases required before the conversion rate dropped and 60 cases before the operative durations diminished (41). It appears that regardless of the approach, VATS or RATS, the LC leading to minimal competence is repeatedly identified around a minimum of 30 procedures while real proficiency is reached only much later.

Accelerating the learning process and assessment of competence

The bulk of knowledge and skills to be mastered by our trainees is without any doubt higher than for those who, like the senior author, have been trained in the 1980s. In addition, restriction of working hours by European regulations, well accepted by the younger generation looking for an improved work-life balance, mathematically reduce duration of exposure to surgical procedures. Consequently, there is a need for substitutes to gain surgical experience, where simulation training takes a central place (18). While it is far beyond the scope of this paper to make an exhaustive review on modern simulation and virtual reality (VR) applications, nowadays it seems obvious in surgical teaching that these technologies need to be embraced to accelerate learning while reducing the number of patients exposed to potential harm. Basic laparoscopic skills practiced on black box trainers improve surgical performance in laparoscopic procedures and are particularly beneficial in the early postgraduate period of a residency (16,17). Jensen et al. led a randomized trial comparing “Fundamentals of Laparoscopy” (FLS) training to VR (43). Evaluation of the operating time for lobectomy on a pig heart-lung block demonstrated an advantage in favor of FSL training. The comprehension of surgical anatomy is promoted with utilization of 3D reconstruction of the diseased lung, and particularly recommended when segmentectomy is planned for: the latter process allows to plan and rehearse a given operation, but also to set up a 3D anatomic library for education (44-46). 3D imaging-generated augmented reality may enhance surgical navigation (47).

Another fundamental need is evaluation and monitoring the progression of learners, which may rely on several assessment tools. As mentioned, the pig heart-lung bloc in a black box is a cost-effective way to go. A more sophisticated alternative relies on reviewing of operative records. Jensen et al. have established an evaluation tool for VATS (VATSAT score), where external reviewers rate 8 items between 1 (poor) and 5 (excellent). The items include localization of the tumor, hilar, vascular, and bronchial dissection, node dissection, respect for tissues and technical skills in general (43). This scoring system was applied to a cohort of trainees and consultants with a pass mark established at 31; while 1 beginner passed, 2 experts failed. The scoring system has been validated on the distribution of VATSAT scores, where the median value for beginners was 22, compared to 37 for experts (48). The same scoring system can be utilized to evaluate trainees’ performance on VR simulators (49).

A collaborative ESTS-European Respiratory Society (ERS)-European Association for Cardio-Thoracic Surgery (EACTS) task force group has delimited the perimeter of the specialty “thoracic surgery” throughout Europe by the Delphi methodology and has set up a syllabus where mandatory modules concerning the core substance common to all training programs, and optional modules concerning more specialized issues such as pediatric thoracic surgery, esophageal surgery, transplantation, and extracorporeal support. The syllabus lists the different procedures that a trainee in thoracic surgery should master at the end of training (50). However, it remains to the responsibility of individual training programs to define when competence should be reached within the curriculum. A simple way to evaluate competence is the Zwisch scale—otherwise said: a comprehensive adaptation of Miller’s pyramid (Table 4) (51). With this simple tool, the individual progression along the LC monitored, still matched Halstedt’s time-honored principle of progressive autonomy.

The remaining question is the potential risk of harm to patients due to operations performed by learners. In the early phase of the LC, conversions remain relatively frequent events. The Copenhagen group has demonstrated a dramatic decrease of the conversion rate with increasing activity and experience: the conversion rate went down from 23% in 2000 to 2% in 2011 (52).

The question remains if future trainees, who will be exclusively exposed to VATS techniques, will lack competence in open surgery techniques to safely deal with emergent situations and complications. This even more applies to robotics where emergency conversion can be more challenging; the operator needs to scrub in, and instrument manipulation is so critical that requires team rehearsals. Will future surgeons be able to operate at all if their robot is out of order? One may even be worried that some procedures that cannot be done other than by VATS might not be done at all, thus leading to a loss of chance in some situations. But who will be at place, able to judge this? In abdominal surgery due to an earlier evolution towards “all by laparoscopy” this question has already been answered partially. Upcoming generations of surgeons will be able to do almost anything by VATS [“the sky is the limit” (53)].

Conversion however is not a feature of trainees alone: a multicenter study showed that, when considering conversion for major bleeding, 10 out of 16 events had been caused by surgeons with an experience above 200 procedures (54). However, conversion in an unprepared patient increases significantly post-operative morbi-mortality: mortality may be increased from 0.2% without conversion to 6.8% with conversion; complication rate raised from 16.8% to 40.9%; hospital stay shifted from 7 to 11 days (55). Adequate preparation of trainees based on simulation training may significantly reduce the need for conversion: the Copenhagen group reported on the first 29 VATS lobectomies performed by a well-prepared trainee, where the consultant had to take over the lead in two cases only; none required conversion (56). Participation in a database at a national level has demonstrated gradual improvement of outcomes over time, as for instance decrease of operative mortality for lobectomy (57). Shouldn’t we consider benchmarking of operations performed by trainees specifically and create a subset in the ESTS database?

Who has learned may forget

Ebbinghaus’ counterpart of the LC is the forgetting curve. Acquired knowledge may vanish from our memory over time. CUSUM analysis can indicate a need for remediation upon skill degradation due to, e.g., long absence (58).

Little research has been dedicated so far to this aspect in thoracic surgery. Markar et al. analyzed the UK national database for minimally invasive esophagectomy and identified various time intervals between procedures to be negatively influencing conversions rates but also re-intervention rates and even 30- and 90-day mortality rates hereby finding strong arguments for centralization of such complex procedures (59). Short intervals between learning episodes together with expert proctoring may be the key for short LCs for novices in uniportal VATS lung cancer resections when performed in units with very high case load (60).

Skill retention measures may thus be necessary, e.g., through continuous professional development activities. Analogously, pilots need to redo simulation and a type rating exam on a plane type they have not flown on a certain number of hours during a given interval.

For VATS lobectomy some expert consensus fixed the annual minimum number of procedures to maintain proficiency at 20 (for many even 40) (22). As seen in the above discussion, simulation-based (re-)training should not mean performing a predetermined number of cases. Due to the individuality of LCs, it should focus on reaching an established proficiency level (61). This also requires simulation tools to implement proficiency-based curricula (58).

Limitations

We acknowledge that our discussion lacks space to address in depth all possible aspects of individual and team-training for every possible technical variant of minimally invasive lung surgery. With several hundred individual studies already published on VATS and RATS LCs, a systematic literature review could be useful. Our study does not replace such a narrative review and we acknowledge any potential biases in our selection of publications we consider the most relevant for the topic.

Conclusions

Moving from open surgery to minimally invasive approaches with video-thoracoscopic or robot assistance, cannot be summarized to the LC of a single surgeon, outside of the trainee evolving in a high-volume center with established VATS or RATS program. Regardless the approach or the type of procedure, or the quality indicators on scrutiny, most authors describe a set-off indicating competence that appears after 30 procedures with proficiency being reached much later. When a program is starting from scratch, it is mandatory to train the whole operative team for standard procedures, but also for a variety of complications that may occur. The individual novice surgeon should take advantage of FLS-type simulation training to acquire basic skills, which account for faster progression. The few first operations will certainly benefit from support and proctoring by an experienced expert and avoid deleterious consequences for the patient. However, we should be aware that the learning process is a life-long one, because there are other set-off points after reaching proficiency. As any switch from one VATS technique to another requires an additional specific LC, ever-evolving technology will care for additional adaptations and learning during the work-life of thoracic surgeons.

Obviously, despite hundreds of papers published on LC for VATS and RATS, many questions remain open, and we orientate our endeavors on large multicentric and database studies in an ultimate attempt to identify the hallmarks of proficiency and mastery.

We can so far conclude that signs of early competence and safe performance have been reached in most studies within a short LC of approximately 30 VATS lobectomies. However, fast evolving technology will repeatedly challenge not only surgical trainees, but also confirmed consultants in their life-long learning and recertification processes. Any new technique will require an additional dedicated LC. Accordingly, we need an environment that guarantees adequate surgical exposure. A safe way to go is to set emphasis on simulation training, VR, and proctoring techniques, which in addition reduce the risk for harm to patients during LC. Another option to consider is centralization of lung cancer treatment in highly specialized and high volume regional of national centers, considering that low volume units cannot offer an adequate caseload to get across the LC both individual surgeons and operating room teams.

Acknowledgments

Funding: None.

Footnote

Provenance and Peer Review: This article was commissioned by the Guest Editors (Leizl Joy Nayahangan, Lars Konge and René Horsleben Petersen) for the series “Simulation-Based Education in Cardiac and Thoracic Surgery” published in Shanghai Chest. The article has undergone external peer review.

Peer Review File: Available at https://shc.amegroups.com/article/view/10.21037/shc-23-12/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://shc.amegroups.com/article/view/10.21037/shc-23-12/coif). The series “Simulation-Based Education in Cardiac and Thoracic Surgery” was commissioned by the editorial office without any funding or sponsorship. G.D. has been an Associate Editor (General Thoracic) of European Journal of Cardiothoracic Surgery (EJCTS) since October 2023, and was an Associate Editor of Interactive Cardiovascular and Thoracic Surgery (ICVTS) in 2022 and until October 2023, and UEMS Section of Thoracic Surgery: National Representative for Luxembourg. The authors have no other conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. ESTS. Silver Book. 2022. Available online: https://www.ests.org/_userfiles/pages/files/database_reports/ests_2022_silver_book.pdf
2. Potter AL, Spasojevic A, Raman V, et al. The Increasing Adoption of Minimally Invasive Lobectomy in the United States. Ann Thorac Surg 2023;116:222-9. [Crossref] [PubMed]
3. Sihoe ADL. Video-assisted thoracoscopic surgery as the gold standard for lung cancer surgery. Respirology 2020;25:49-60. [Crossref] [PubMed]
4. National Lung Screening Trial Research Team. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med 2011;365:395-409. [Crossref] [PubMed]
5. Rzyman W, Szurowska E, Adamek M. Implementation of lung cancer screening at the national level: Polish example. Transl Lung Cancer Res 2019;8:S95-S105. [Crossref] [PubMed]
6. Raz DJ, Wu GX, Consunji M, et al. Perceptions and Utilization of Lung Cancer Screening Among Primary Care Physicians. J Thorac Oncol 2016;11:1856-62. [Crossref] [PubMed]
7. Bendixen M, Jørgensen OD, Kronborg C, et al. Postoperative pain and quality of life after lobectomy via video-assisted thoracoscopic surgery or anterolateral thoracotomy for early stage lung cancer: a randomised controlled trial. Lancet Oncol 2016;17:836-44. [Crossref] [PubMed]
8. Lim E, Harris RA, McKeon HE, et al. Impact of video-assisted thoracoscopic lobectomy versus open lobectomy for lung cancer on recovery assessed using self-reported physical function: VIOLET RCT. Health Technol Assess 2022;26:1-162. [Crossref] [PubMed]
9. Long H, Tan Q, Luo Q, et al. Thoracoscopic Surgery Versus Thoracotomy for Lung Cancer: Short-Term Outcomes of a Randomized Trial. Ann Thorac Surg 2018;105:386-92. [Crossref] [PubMed]
10. Sesti J, Langan RC, Bell J, et al. A Comparative Analysis of Long-Term Survival of Robotic Versus Thoracoscopic Lobectomy. Ann Thorac Surg 2020;110:1139-46. [Crossref] [PubMed]
11. Swanson SJ, Miller DL, McKenna RJ Jr, et al. Comparing robot-assisted thoracic surgical lobectomy with conventional video-assisted thoracic surgical lobectomy and wedge resection: results from a multihospital database (Premier). J Thorac Cardiovasc Surg 2014;147:929-37. [Crossref] [PubMed]
12. Thimbleby H. Technology and the future of healthcare. J Public Health Res 2013;2:e28. [Crossref] [PubMed]
13. Jensen K, Ringsted C, Hansen HJ, et al. Simulation-based training for thoracoscopic lobectomy: a randomized controlled trial: virtual-reality versus black-box simulation. Surg Endosc 2014;28:1821-9. [Crossref] [PubMed]
14. Gjeraa K, Dieckmann P, Jensen K, et al. Effects of shared mental models in teams performing video-assisted thoracoscopic surgery lobectomy. Surg Endosc 2022;36:6007-15. [Crossref] [PubMed]
15. Tacconi F, Pompeo E. Non-intubated video-assisted thoracic surgery: where does evidence stand? J Thorac Dis 2016;8:S364-75. [Crossref] [PubMed]
16. Sroka G, Feldman LS, Vassiliou MC, et al. Fundamentals of laparoscopic surgery simulator training to proficiency improves laparoscopic performance in the operating room-a randomized controlled trial. Am J Surg 2010;199:115-20. [Crossref] [PubMed]
17. Haidari TA, Nayahangan LJ, Bjerrum F, et al. Consensus on technical procedures for simulation-based training in thoracic surgery: an international needs assessment. Eur J Cardiothorac Surg 2023;63:ezad058. [Crossref] [PubMed]
18. Baste JM, Bottet B, Selim J, et al. Implementation of simulation-based crisis training in robotic thoracic surgery: how to improve safety and performance? J Thorac Dis 2021;13:S26-34. [Crossref] [PubMed]
19. Schmiederer IS, Kearse LE, Jensen RM, et al. The fundamentals of laparoscopic surgery in general surgery residency: fundamental for junior residents' self-efficacy. Surg Endosc 2022;36:8509-14. [Crossref] [PubMed]
20. Mazzella A, Olland A, Falcoz PE, et al. Video-assisted thoracoscopic lobectomy: which is the learning curve of an experienced consultant? J Thorac Dis 2016;8:2444-53. [Crossref] [PubMed]
21. Li X, Wang J, Ferguson MK. Competence versus mastery: the time course for developing proficiency in video-assisted thoracoscopic lobectomy. J Thorac Cardiovasc Surg 2014;147:1150-4. [Crossref] [PubMed]
22. Yan TD, Cao C, D'Amico TA, et al. Video-assisted thoracoscopic surgery lobectomy at 20 years: a consensus statement. Eur J Cardiothorac Surg 2014;45:633-9. [Crossref] [PubMed]
23. Lof S, Claassen L, Hannink G, et al. Learning Curves of Minimally Invasive Distal Pancreatectomy in Experienced Pancreatic Centers. JAMA Surg 2023;158:927-33. [Crossref] [PubMed]
24. Harrysson IJ, Cook J, Sirimanna P, et al. Systematic review of learning curves for minimally invasive abdominal surgery: a review of the methodology of data collection, depiction of outcomes, and statistical analysis. Ann Surg 2014;260:37-45. [Crossref] [PubMed]
25. Woodall WH, Rakovich G, Steiner SH. An overview and critique of the use of cumulative sum methods with surgical learning curve data. Stat Med 2021;40:1400-13. [Crossref] [PubMed]
26. Vieira A, Bourdages-Pageau E, Kennedy K, et al. The learning curve on uniportal video-assisted thoracic surgery: An analysis of proficiency. J Thorac Cardiovasc Surg 2020;159:2487-2495.e2. [Crossref] [PubMed]
27. Li WH, Cheng H, Gan XF, et al. Learning curve of uniportal video-assisted thoracoscopic lobectomy: an analysis of the proficiency of 538 cases from a single centre. Interact Cardiovasc Thorac Surg 2022;34:799-807. [Crossref] [PubMed]
28. Deng J, Jiang L, Li S, et al. The learning curve of video-assisted thoracoscopic sleeve lobectomy in a high-volume pulmonary center. JTCVS Tech 2021;9:143-52. [Crossref] [PubMed]
29. Chen L, Shen Y, Duan S, et al. Learning curve for uniportal video-assisted thoracoscopic anatomical segmentectomy. Ann Transl Med 2022;10:12. [Crossref] [PubMed]
30. Hamada A, Oizumi H, Kato H, et al. Learning curve for port-access thoracoscopic anatomic lung segmentectomy. J Thorac Cardiovasc Surg 2018;156:1995-2003. [Crossref] [PubMed]
31. Harris CG, James RS, Tian DH, et al. Systematic review and meta-analysis of uniportal versus multiportal video-assisted thoracoscopic lobectomy for lung cancer. Ann Cardiothorac Surg 2016;5:76-84. [Crossref] [PubMed]
32. Andersson SE, Ilonen IK, Pälli OH, et al. 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. Cancer Treat Res Commun 2021;27:100362. [Crossref] [PubMed]
33. Wilson-Smith AR, Anning N, Muston B, et al. The learning curve of the robotic-assisted lobectomy-a systematic review and meta-analysis. Ann Cardiothorac Surg 2023;12:1-8. [Crossref] [PubMed]
34. Lee PC, Kamel M, Nasar A, et al. Lobectomy for Non-Small Cell Lung Cancer by Video-Assisted Thoracic Surgery: Effects of Cumulative Institutional Experience on Adequacy of Lymphadenectomy. Ann Thorac Surg 2016;101:1116-22. [Crossref] [PubMed]
35. Puri V, Gaissert HA, Wormuth DW, et al. Defining Proficiency for The Society of Thoracic Surgeons Participants Performing Thoracoscopic Lobectomy. Ann Thorac Surg 2019;107:202-8. [Crossref] [PubMed]
36. Power AD, D'Souza DM, Moffatt-Bruce SD, et al. Defining the learning curve of robotic thoracic surgery: what does it take? Surg Endosc 2019;33:3880-8. [Crossref] [PubMed]
37. Augustin F, Bodner J, Maier H, et al. Robotic-assisted minimally invasive vs. thoracoscopic lung lobectomy: comparison of perioperative results in a learning curve setting. Langenbecks Arch Surg 2013;398:895-901. [Crossref] [PubMed]
38. Lee BE, Korst RJ, Kletsman E, et al. Transitioning from video-assisted thoracic surgical lobectomy to robotics for lung cancer: are there outcomes advantages? J Thorac Cardiovasc Surg 2014;147:724-9. [Crossref] [PubMed]
39. Le Gac C, Gondé H, Gillibert A, et al. Medico-economic impact of robot-assisted lung segmentectomy: what is the cost of the learning curve? Interact Cardiovasc Thorac Surg 2020;30:255-62. [PubMed]
40. Mazzella A, Mohamed S, Maisonneuve P, et al. Learning Curve of Robotic Lobectomy for the Treatment of Lung Cancer: How Does It Impact on the Autonomic Nervous System of the Surgeon? J Pers Med 2023;13:193. [Crossref] [PubMed]
41. Gallagher SP, Abolhoda A, Kirkpatrick VE, et al. Learning Curve of Robotic Lobectomy for Early-Stage Non-Small Cell Lung Cancer by a Thoracic Surgeon Adept in Open Lobectomy. Innovations (Phila) 2018;13:321-7. [Crossref] [PubMed]
42. Fukui T, Kawaguchi K, Tsubouchi H, et al. ˂Editors' Choice˃ Learning curve of robotic lobectomy for lung malignancies by certified thoracic surgeons. Nagoya J Med Sci 2021;83:227-37. [PubMed]
43. Jensen K, Petersen RH, Hansen HJ, et al. A novel assessment tool for evaluating competence in video-assisted thoracoscopic surgery lobectomy. Surg Endosc 2018;32:4173-82. [Crossref] [PubMed]
44. Tokuno J, Chen-Yoshikawa TF, Nakao M, et al. Creation of a video library for education and virtual simulation of anatomical lung resection. Interact Cardiovasc Thorac Surg 2022;34:808-13. [Crossref] [PubMed]
45. Tokuno J, Chen-Yoshikawa TF, Nakao M, et al. Resection Process Map: A novel dynamic simulation system for pulmonary resection. J Thorac Cardiovasc Surg 2020;159:1130-8. [Crossref] [PubMed]
46. Le Moal J, Peillon C, Dacher JN, et al. Three-dimensional computed tomography reconstruction for operative planning in robotic segmentectomy: a pilot study. J Thorac Dis 2018;10:196-201. [Crossref] [PubMed]
47. Baste JM, Soldea V, Lachkar S, et al. Development of a precision multimodal surgical navigation system for lung robotic segmentectomy. J Thorac Dis 2018;10:S1195-204. [Crossref] [PubMed]
48. Petersen RH, Gjeraa K, Jensen K, et al. Assessment of competence in video-assisted thoracoscopic surgery lobectomy: A Danish nationwide study. J Thorac Cardiovasc Surg 2018;156:1717-22. [Crossref] [PubMed]
49. Haidari TA, Bjerrum F, Christensen TD, et al. Assessing VATS competence based on simulated lobectomies of all five lung lobes. Surg Endosc 2022;36:8067-75. [Crossref] [PubMed]
50. Massard G, Tabin N, Mitchell S, et al. A harmonized European training syllabus for thoracic surgery: report from the ESTS-ERS task force. Eur J Cardiothorac Surg 2018;54:214-20. [Crossref] [PubMed]
51. Meyerson SL, Sternbach JM, Zwischenberger JB, et al. Resident Autonomy in the Operating Room: Expectations Versus Reality. Ann Thorac Surg 2017;104:1062-8. [Crossref] [PubMed]
52. Petersen RH, Hansen HJ. Learning curve associated with VATS lobectomy. Ann Cardiothorac Surg 2012;1:47-50. [PubMed]
53. Khatkov I, Fingerhut A. Pushing the Limits of Laparoscopic Surgery: "How High Is the Sky?" or "When Conversion Is Not Needed". Surg Innov 2016;23:5-6. [Crossref] [PubMed]
54. Decaluwe H, Petersen RH, Hansen H, et al. Major intraoperative complications during video-assisted thoracoscopic anatomical lung resections: an intention-to-treat analysis. Eur J Cardiothorac Surg 2015;48:588-98; discussion 599. [Crossref] [PubMed]
55. Seitlinger J, Olland A, Guinard S, et al. Conversion from video-assisted thoracic surgery (VATS) to thoracotomy during major lung resection: how does it affect perioperative outcomes? Interact Cardiovasc Thorac Surg 2021;32:55-63. [Crossref] [PubMed]
56. Konge L, Petersen RH, Hansen HJ, et al. No extensive experience in open procedures is needed to learn lobectomy by video-assisted thoracic surgery. Interact Cardiovasc Thorac Surg 2012;15:961-5. [Crossref] [PubMed]
57. Falcoz PE, Puyraveau M, Rivera C, et al. The impact of hospital and surgeon volume on the 30-day mortality of lung cancer surgery: A nation-based reappraisal. J Thorac Cardiovasc Surg 2014;148:841-8; discussion 848. [Crossref] [PubMed]
58. Hashimoto DA, Aggarwal R. Learning curves for simulators. In: Dasgupta P, Ahmed K, Jaye P, et al. editors. Surgical Simulation. Anthem Press; 2014:63-72.
59. Markar SR, Ni M, Mackenzie H, et al. The effect of time between procedures upon the proficiency gain period for minimally invasive esophagectomy. Surg Endosc 2020;34:2703-8. [Crossref] [PubMed]
60. Wu CF, Paradela M, Wu CY, et al. Novice training: The time course for developing competence in single port video-assisted thoracoscopic lobectomy. Medicine (Baltimore) 2020;99:e19459. [Crossref] [PubMed]
61. Feldman LS, Cao J, Andalib A, et al. A method to characterize the learning curve for performance of a fundamental laparoscopic simulator task: defining "learning plateau" and "learning rate". Surgery 2009;146:381-6. [Crossref] [PubMed]