Junior surgeons are quicker to master the single-port thoracoscopic lobectomy: comprehensive analysis of the learning curve and oncological outcomes

The learning curve refers to the gradual process of completing and mastering a certain skill through continuous learning. The general learning curve can be divided into two phases: fast-rise phase and platform phase. When the platform phase is reached, the surgeon’s technique is relatively skilled and stable, that is, it overcomes the learning curve. In recent years, the learning curve has been increasingly used to evaluate the acquisition of surgical skills and then guide the development of new surgical techniques [27, 28]. Learning curve studies mainly use the group-split method [15, 29]. However, there is no unified standard for group-split methods. The number of cases to overcome learning curves is relatively unclear, and several indicators of the learning curve evaluation are inconsistent between the groups.

CUSUM analysis has been used to analyze the learning curve of surgical procedures since the 1970s [30, 31]. CUSUM analysis transforms raw data into the running total of data deviations from their group mean, enabling investigators to visualize the data for trends that are not discernible using other approaches. It has been regarded as an aid for early assessment of surgical trainees and is already used in several fields [16].

Various factors can influence surgical procedures. However, most previous learning curve studies used operation time as the sole indicator [32]. The shortening of the operation time could demonstrate the proficiency of the surgical technique, and decrease in the estimated blood loss and duration of postoperative hospital stay could explain the improvement in the surgical technique [18]. Therefore, a single indicator, such as the operation time, may not result in an in-depth evaluation of the learning curve. In this study, those three indicators were combined and served as the evaluation criteria, and the learning curves were comprehensively drawn.

In the early stage, it was very difficult to carry out SPTL, due to the unskillful technique, inexperienced procedure, insufficient cooperation. Accordingly, in the initial cases, the operation time was long, the estimated blood loss was large, and the postoperative hospital stay was long as well. The CUSUM value gradually increased after accumulation. However, with improvements in surgical techniques, operative time, estimated blood loss, and duration of postoperative hospital stay all decreased. The CUSUM value gradually decreased in this period. As the slope of the learning curve transitioned from positive to negative, the exact cases reflected the mastery of the surgical procedure. In this study, 33 cases were required to overcome the SPTL learning curve in the STS group and 25 cases in the JTS group. The slopes of the learning curves in phase 1 were compared between both groups, and the degree of the slope in the JTS group was greater than that in the STS group, which meant that the learning efficiency was greater among the JTS. Comparisons of the perioperative parameters between both groups in phase 2 showed no statistically significant difference, which testified that the learning curve had been overcome. Although 8 fewer cases were required in the JTS group to overcome the learning curve, the average operation time was longer in the JTS group than in the STS group.

The reasons for better learning curves in younger surgeons are not completely defined. Senior surgeon may have a wealth of experience and a proven track record but may struggle to adapt to new techniques and technologies, due to their age, fixed mindset, and surgical mode, and minimally invasive surgery evolved from open surgery. On the other hand, junior surgeons may have more interest in innovative ideas and be more familiar with newer technologies. The basic skills are generally considered to be of great influence on learning curves; however, junior doctors can be easily trained to improve their experience with more recent methods, including video training, long-term advanced formation, self-determination training, simulator training, and webcast learning. Hence, an expert consensus about uniportal video-assisted thoracic surgery for lung cancer treatment reported that the experience of thoracotomy or multi-portal video-assisted thoracic surgery would not affect the learning curve [33].

In addition, conventional learning curve studies mainly focused on the evaluation of perioperative parameters. However, Berfield et al. suggested that the overall survival should be regarded as another indicator of the learning curve [18]. In accordance with their findings, we believe that oncology surgeons should not only perform a surgery but also pay attention to whether the surgery could bring oncological benefits. These differences might not be distinguished during the perioperative period; however, the postoperative overall survival and disease-free survival rates for the same tumor-staged operable patients could, to some extent, reflect these differences several years later. In this study, there was no difference in the 5-year overall survival rate between the two groups, which further confirmed that the surgeons successfully overcame the learning curve.

However, this study has some limitations including its single-center retrospective design and relatively small sample. Besides, bias for patient cohort selection inevitably remained. Regarding the learning curve for a new technology, we tend to start with some relatively simple cases, rather than complex cases. The failure of a newly developed surgical technique will lead to, on the one hand, grave damage to the interests of patients, and, on the other hand, it will also seriously hit the confidence of the surgeon. Moreover, the skill of the surgical procedure (especially in SPTL) depends on the whole surgical team members, which include the surgeon and the assistants. In our center, the assistants are made up of three residents, and they participate in all operations together. That is, although the assistants were not the same for every surgery, they were randomly involved in surgeries of both groups. To some extent, their effect on the whole study could be balanced or offset. Of course, controlling for several confounding factors would help decrease the selection bias. In the future, as an expanding number of scholars participate in this field of research, an increasingly objective and comprehensive exposition of this subject will be presented.

Generally, we conclude that the multidimensional CUSUM method is an effective tool for the objective evaluation of practical skills for surgeons during the learning phase of SPTL training. The data indicated that after a learning curve phase of 25–33 cases, thoracic surgeons could become increasingly skillful. Junior surgeons became competent in this new technology after about 25 cases, becoming more proficient in performing more complex surgeries. In summary, SPTL was found to have a shorter learning curve for JTSs.

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