Abstract
Key Messages
Proficiency in robotic thyroid surgery requires different case volumes by approach: axillary (34-46 cases), transoral (31 cases), and facelift (32 cases), with transoral and facelift approaches potentially having faster learning curves.
Complication rates during the learning process varied across surgical approaches: axillary (16.7%), transoral (11.1%), and facelift (16.2%), with inconsistent evidence regarding complication reduction throughout the learning curve.
Surgeon-specific factors significantly influence learning curves, with prior robotic/endoscopic experience and anatomical familiarity potentially accelerating proficiency acquisition, highlighting the need for standardized training protocols.
Introduction
Numerous minimally invasive surgical approaches have been developed in the past decades, especially in Asian countries,1,2 to minimize postoperative anterior cervical scar formation. 3 The minimally invasive surgical approaches primarily consist of endoscopic or robotic procedures with axillary, areolar, oral, or hairline incisions. 4 Nowadays, the Da Vinci robot (Intuitive®, Sunnyvale, CA, USA) is particularly used for minimal invasive thyroid surgeries due to its increasing availability in Western countries, and its usefulness for other oncological head and neck procedures.5,6 Regarding the paradigm shift toward minimally invasive surgical techniques, there is a need to enhance the surgical training of these techniques, 7 with learning curve analyses suggesting proficiency after 25 to 50 cases in transoral robotic head and neck procedures. 6 An increasing number of studies investigated the learning curve in robotic or endoscopic minimally invasive thyroid procedures in the past decade, with overall meta-analyses and largest studies supporting proficiency for robotic and endoscopic thyroid surgeries for 30 procedures, and 6 to 15 annual cases, respectively.8,9 In practice, the surgical approach may significantly influence the learning curve of surgeons regarding their personal experience and background. 10 It may be hypothesized that otolaryngologists—head and neck surgeons are more proficient for transoral and facelift approaches rather than axillary or areolar approaches, which should influence the learning curve.
The aim of this systematic review was to investigate the learning curves of robotic thyroid surgeries considering the surgical approach.
Materials and Methods
The systematic review was conducted by 2 investigators according to the Preferred Reporting Items for a Systematic Review and Meta-Analysis (PRISMA) checklist. 11 The criteria for considering studies were based on the population, intervention, comparison, outcome, timing, and setting (PICOTS) framework. 12
The secondary outcomes consisted of demographics (number of patients, biological sex, mean/median age), the team location (to avoid overlap), tumor features (eg, histology, stages), surgical outcomes considered for learning curve analysis (docking, console, and total operative times, hospital stay, conversion), and complications.
Search Strategy
The following databases were considered by the 2 investigators for relevant peer-reviewed papers related to learning outcomes of robotic thyroid procedures: PubMed, Scopus, and Cochrane Library. The University librarian and the first author conducted the literature search independently, using the following MeSH keywords for the search strategy: Learning; Thyroid; Surgery; and Outcome. The following non-MeSH keywords were used: Transoral; Robot; and Robotic. Both investigators reviewed studies reporting database abstracts, available full-texts, or titles with the search terms for relevance, and the reference lists of some articles were explored for additional pertinent studies. Duplicates were excluded. In addition to primary and secondary outcomes, the studies that met the inclusion criteria were analyzed for the number of patients, study design, periods of case recruitment, and the author center to identify potential overlapped investigations and considering the study with the largest number of patients. This systematic review did not require the approval of the Elsan Ethic Committee. There was no disagreement to resolve by a third expert.
Bias Analysis
The bias analysis was carried out with the MINORS tool that is a standardized and valid instrument for assessing the quality of clinical studies. 14 MINORS includes items rated 0 if absent, 1 when reported but inadequate, and 2 when reported and adequate. The following items are included in the MINORS: (1) aim of the study [clearly stated (2), unclear (1), or absent (0)]; (2) inclusion of patients [consecutive (2) or not (0) inclusion]; (3) prospective data collection [perfectly prospective (2), retrospective analysis of prospectively collected data (1), or absent (0)]; (4) appropriateness of endpoints [evaluation of learning curve consisting of the evolution of more than one surgical feature (eg, complications, operative time, conversion) (2), evaluation of a single outcome (1), no reported outcome (0)]; and (5) adequate follow-up period consisting of the minimum number of cases for achieving valid data for the learning process [at least 50 cases (2), 31-49 cases (1), or fewer than 30 (0)]. The item related to the prospective study size calculation was considered for prospective studies and rated as adequate (2), mentioned as unnecessary or not provided (1), or absent (0). The ideal MINORS score was 16 for non-comparative studies and 24 for comparative studies. 14 Similar to a review assessing the learning curve of TORS head and neck procedures, 6 the following outcomes were added to the bias analysis: specification about a potential training/preparation program prior to the implementation of robotic program; experience of surgeons with endoscopic or robotic approach; and description of statistical methods used for evaluating the learning process/inflection point [mentioned and detailed (2), mentioned without details (1), unmentioned (0)].
Results
Of the 450 identified studies, 34 studies met our inclusion criteria (Figure 1).15 -48 Fourteen studies were excluded for overlap (n = 6), lack of details or learning curve (n = 4), low number of cases (n = 2), or for mixed learning findings of endoscopic and robotic approaches without providing details for robotic cases (n = 2) (Figure 1). Twenty-three studies reported learning curve/findings of robotic axillary or bilateral axillary-breast approaches (Table 1),15 -37 including 10 comparative studies between 2 robotic approaches (Table 1). Learning process of transoral robotic approach was explored in 9 studies (Table 2),24,27,28,30,38-42 with 4 studies comparing transoral approach with another robotic approach.24,27,28,30 Four studies reported learning curves of facelift (hairline) robotic thyroidectomy,35,43,44,45 with one comparing axillary versus facelift approach 35 (Table 3). Finally, 3 teams investigated the learning curves of robotic thyroid procedures combining several surgical approaches (Table 3).46 -48 Of the 34 studies, 3 were prospective studies25,28,33, others being retrospective comparative or non-comparative series.
PRISMA flowchart.
Features of Studies Reporting Learning Curve of Robotic Axillary Approaches for Thyroid Surgery.
Abbreviations: AX, axillary approach; BA, breast approach; BABA, bilateral axillo-breast approach; C/LND, central/lateral neck dissection; CT, console time; CTs, controls; DT, docking time; ET-BAA, endoscopic bilateral areolar approach; FD, flap dissection; FL, facelift approach; LLP, lower lip paresthesia; MNC, minimum number of cases for achieving proficiency; OT, operative time; P1/P2, phase1/2; PT, partial thyroidectomy; TO, transoral; TT, total thyroidectomy.
(age) = median.
No stat.
Features of Studies Reporting Learning Curve of Transoral Robotic Thyroid Surgery.
Abbreviations: AX, axillary approach; BA, breast approach; BABA, bilateral axillo-breast approach; C/LND, central/lateral neck dissection; CT, console time; CTs, controls; DT, docking time; ET-BAA, endoscopic bilateral areolar approach; FD, flap dissection; FL, facelift approach; LLP, lower lip paresthesia; MNC, minimum number of cases for achieving proficiency; OT, operative time; P1/P2, phase1/2; PT, partial thyroidectomy; TO, transoral; TT, total thyroidectomy.
(age) = median.
Features of Studies Reporting Learning Curve of Facelift and Combined Robotic Approaches for Thyroid Surgery.
Abbreviations: AX, axillary approach; BA, breast approach; BABA, bilateral axillo-breast approach; C/LND, central/lateral neck dissection; CT, console time; CTs, controls; DT, docking time; ET-BAA, endoscopic bilateral areolar approach; FD, flap dissection; FL, facelift approach; LLP, lower lip paresthesia; MNC, minimum number of cases for achieving proficiency; OT, operative time; P1/P2, phase1/2; PT, partial thyroidectomy; TO, transoral; TT, total thyroidectomy.
(age) = median.
Demographics, Patients, and Inclusion Criteria
Most studies included primarily female patients (Tables 1-3). The mean age of patients ranged from 34.4 to 46.2 years old, without substantial differences across surgical approach groups. There was substantial heterogeneity across studies in terms of inclusion criteria (disorders, stage, procedures) considered in the learning process analysis (Table 4).
Indications and Features of Patients Included in Studies.
Abbreviations: BL, benign lesion; FTC, follicular thyroid carcinoma; ND, node dissection; NR, not reported; PT, partial thyroidectomy (lobectomy ± isthmectomy); PTC, papillary thyroid carcinoma; TT, total thyroidectomy.
Among the studies investigating the learning curve of unilateral axillary or bilateral axillary-breast approaches (4084 patients), the primary surgical procedures consisted of total thyroidectomy in 2395 cases and lobectomy in 1698 cases, respectively, with, when provided, node dissection in 1919 cases. The majority of studies included both benign and malignant thyroid lesions. However, 7 studies reported learning process of oncological cases exclusively,15,19,26,27,28,31,37 while Lorincz et al investigated the learning curve of thyroid procedure for only benign lesions. 32 The stage of thyroid cancer was mostly cT1 and cT3, cN0.
A total of 845 patients underwent transoral robotic thyroid procedures, accounting for 107 and 533 total and partial thyroidectomies, and 649 node dissections. Only 2 studies focused on oncological thyroid procedures,27,40 while others included variable proportion of benign versus malignant thyroid procedures (Table 4). Most carcinoma cases were classified cT1, and cT3, cN0.
Among the 111 patients treated by facelift robotic partial (n = 66) or total (n = 45) thyroidectomies, 35 underwent node dissections, and, when provided, the authors considered exclusively cT1N0 carcinoma (Table 4). Three studies reported data of patients who underwent combined approaches (1398 patients) for benign or malignant lesions. There was a balance between the cN0 and cN+ cases in this group, with a majority of cT1 and cT3 carcinomas. Most patients had node dissection (Table 4).
In all the approach groups, most carcinomas were papillary thyroid carcinoma. Importantly, heterogeneity among included articles in inclusion/exclusion criteria, especially types of procedures (partial/total thyroidectomy with/without node dissection) and indications where the learning curve was calculated, outcome measures, and the non-normal distribution of measured outcomes in papers, precluded statistically pooling the data into a formal meta-analysis, thereby limiting the analysis to a qualitative rather than quantitative summary of the available information. Note that the heterogeneity across studies for inclusion and exclusion criteria precludes meta-analysis.
Learning Curves and Minimum Number for Proficiency
Axillary approaches
Given their distinct surgical techniques between gasless transaxillary approach and bilateral axillary-breast approach, with different incision patterns and dissection planes, their learning curves were presented separately, while acknowledging their shared characteristic of remote access through the axillary/chest region.
The learning curve of partial thyroidectomy performed through gasless axillary approach was reported in 3 studies16 -18 (738 patients), while BABA in 2 studies21,31 (617). The gasless axillary approach was associated with a mean of 57.9 cases for achieving proficiency. Although the limited number of studies (N = 2), 25 to 30 cases appeared to be the minimum number for proficiency for bilateral axillary-breast approach. The learning curve of total thyroidectomy performed by bilateral axillary-breast approach was described in 8 studies (n = 1296 patients).17,20,21,22,23,25,26,31 The mean minimum number of cases for reaching proficiency was 34 cases, ranging from 20 to 50 cases.
The learning curve of total thyroidectomy performed by bilateral axillary-breast approach was described in 8 studies (n = 1296 patients).17,20,21,22,23,25,26,31 The mean minimum number of cases for reaching proficiency was 34 cases, ranging from 20 to 50 cases. Of the learning curves of total thyroidectomy studies, Sun et al reported that the learning curve and minimum number of cases for proficiency were similar for total thyroidectomy with and without node dissection. 23 Kim et al suggested that the learning curve is longer for reaching proficiency considering complication (n = 75 cases) stability rather than operative time (n = 50 cases). 26 Except for one study without such information, 22 the learning curve was established for a single surgeon in all of these studies reporting learning process of partial and total thyroidectomies (Table 1). The other studies, which described overall learning curve features of both partial and total thyroidectomies, with or without node dissection, reported a similar range of number of cases for achieving proficiency in terms of operative time and/or complication (19-45 cases).15,33,34,37
Several studies compared axillary approaches with transoral or facelift approaches (Table 1). While they did not provide a minimum number of cases, Terris et al reported that the learning curve of facelift approach was faster compared to axillary approach. 35 Similar findings were found in favor of transoral over axillary approaches in 2 studies concerning the learning curve of transoral robotic approach versus bilateral axillary-breast approach,24,30 which was not corroborated by Kim et al 28 and Chae et al 27 who compared transoral versus bilateral axillary-breast approach, as well. From a methodological standpoint, the cumulative sum chart (CUSUM) approach, which is the standardized learning curve calculation method, was used in 10 studies.15 -18,21,25,26,28,31,34
Transoral approach
Of the 10 studies investigating the learning curve of transoral robotic approach, 5 studies (n = 531 patients) determined the minimum number of cases for reaching proficiency that was 31 cases (15-55 cases).28,38 -41 Wen et al distinguished the minimum number of cases for partial (n = 16) and total (n = 21) thyroidectomies associated with node dissection. 39 In this study, the learning curve was calculated on the procedures of several surgeons. Chen et al determined the minimum number for total thyroidectomies to be 25 cases, 41 while the other studies combined both partial and total thyroidectomies (Table 2).
Lee et al compared the learning curve of transoral robotic versus endoscopic thyroidectomies and reported that the learning process of robotic approach is faster compared to endoscopic approach (25 vs 71 cases). 40 In a comparative study, Kim et al did not observe significant difference in the learning curves of transoral robotic approaches using Da Vinci Xi versus Da Vinci Si robots. 42 The CUSUM approach was considered in 4 studies.28,38-40
Facelift approach
Of the 5 studies reporting learning curve features of facelift robotic thyroid procedures, 3 determined the minimum number of cases for achieving proficiency.44,45 Lira et al suggested that a surgeon needs to perform 50 cases for achieving the learning process of partial or total thyroidectomies with node dissection, 44 while Han et al found that 15 cases were enough for total thyroidectomy. 45 In a study combining the surgical outcome of transaxillary, transoral, and facelift thyroid procedures, Kandil et al determined the minimum number of cases for reaching proficiency to be 21 for facelift robotic approach. 48 Russell et al did not identify the minimum number of cases for reaching proficiency in a study including 20 patients treated with facelift versus transoral endoscopic approaches. 43 Terris et al compared facelift versus axillary approaches, but the low number of cases did not allow calculation of the minimum number of cases to reach the proficiency (Table 3). 35 Considering the 3 above-mentioned studies, the mean number of cases for achieving proficiency should be 32 cases (122 patients; range: 15-50 cases). The CUSUM approach was used in 2 studies.44,45 However, given the limited number of studies (n = 4) and small total patient cohort (n = 131), these findings regarding facelift approach learning curves should be interpreted with caution and considered preliminary pending validation in larger prospective cohorts.
Combined approaches
Three studies reported data of combined approaches, that is, transoral/axillary46,47 or transoral, axillary, and facelift 48 approaches (Table 3). Among them, Zhou et al reported that the surgeon may reach stability in terms of operative time after having performed 11 cases of combined transoral and axillary total thyroidectomy with node dissection. 47 Oh et al reported a significant decrease of operative time throughout 5 consecutive periods of 1 year and 1000 performed cases, but they did not establish the minimum number of cases required to achieve proficiency. 46 Only Zhou et al and Kandil et al used the CUSUM approach.46,48
Complications
Table 5 reported the complications occurring during the learning process of robotic thyroid procedures. Complications were assessed in 3620 patients who underwent axillary thyroid procedures. The mean complication rate of axillary approaches was 16.7%, with transient hypoparathyroidism (10.5%), and transient recurrent laryngeal nerve paralysis (3.3%) as the primary complications. The mean complication rate of transoral robotic thyroid approach group was 11.1%. Among the 825 patients who underwent transoral robotic thyroid procedures with provided complication details, transient hypoparathyroidism and transient recurrent laryngeal nerve paralysis accounted for 2.3% and 1.7% of cases. The complication data related to facelift thyroid approach were provided for 68 patients (mean complication rate: 16.2%). Three patients (4.4%) reported burn skin flap, while seroma and transient recurrent laryngeal nerve paralysis occurred in 1 case (1.5%), respectively. Of the 1398 patients who were treated with combined robotic approaches, transient recurrent laryngeal nerve paralysis (1.3%), local wound infection (1.3%), and transient hypoparathyroidism (1.1%) were the most prevalent complications. The mean complication rate was 6.2%. Although the complication rates depend on the method used to systematically document complications, the transversal analysis suggests that complications occurred in 6.2% to 16.7% of cases, with 2 studies reporting a significant decrease over the learning process34,38 and 2 reporting no change.17,26
Complications Occurring Throughout Learning Processes.
This table includes only studies providing complication during the learning process. The findings of studies investigating the complications in 2 approaches were included in both approach groups.
Abbreviations: BABA, bilateral axillary-breast approach; BLE, bleeding; BP, brachial plexus; CV, conversion; ECC, Ecchymosis; EM, emphysema; HS, hypertrophic scarring; NC, necrosis; Oeso, esophageal; PBN, plexus branchial neuropraxia; Perf., perforation; RLN, recurrent laryngeal nerve; TO, transoral.
Studies comparing complications between approach groups and, therefore, included in 2 approach group data of this table regarding the complication of specific approach.
Bias Analysis
The bias analysis is provided in Table 6. The mean MINORS was 8.6 ± 2.5 (maximum of 14). The low MINORS was related to the design of most studies (retrospective chart-review), the lack of prospective data collection, and moderate quality of endpoints used for assessing the learning curve. Importantly, only 2 studies considered a study size calculation prior to starting their analyses.24,28 Concerning the contributing factors to learning curve analyses, the training of the surgeon/team performing the surgical procedures assessed for learning curve was fully reported in 2 studies.41,43 Complete information related to the surgical experience of surgeon(s), including endoscopic, robotic, conventional thyroid/head, and neck procedures, was reported in 9 studies.18,21,27,38,39,40,41,43,47 While most studies evaluated the learning curve of a single surgeon, Park et al was the only team reporting the learning curve of 2 fellows-in-training without extensive endoscopic or robotic experience. 33 Interestingly, the authors demonstrated that the minimum number of cases for reaching proficiency in terms of operative time and complications was similar in both fellows (19 cases) regardless of small differences for console and flap dissection times. There was no study comparing the learning curve of novice versus experienced surgeon, which consists of a major limitation for the establishment of learning curve findings.
Bias Analysis.
Abbreviation: E/R, endoscopic/robotic.
Discussion
The paradigm shifts toward minimally invasive thyroid surgical techniques and the increased availability of Da Vinci robot make important the evaluation of the learning curves of the numerous thyroid procedures. Despite substantial heterogeneity across studies, this systematic review identified that proficiency may be achieved for 31 to 46 cases according to the surgical approach and the definition and criteria used for learning curve outcomes. Precisely, it seems that unilateral or bilateral axillary-breast approaches reported the highest mean number of minimum cases (n = 34-46) compared to transoral (n = 31) and facelift (n = 32) approaches. Although this finding needs to be confirmed in further controlled studies, the faster learning process of facelift and transoral approaches could be attributed to the better knowledge of anatomic neck structures versus axillary/chest ones by otolaryngologists and/or head and neck surgeons performing thyroid surgeries, which may lead to faster flap dissection and related operative time. The interpretation of such results needs to be prudent because some contributing factors may influence the learning curve, including the surgeon and operating room training and experience, the indications (inclusion criteria), and surgical outcomes, all of them reporting substantial heterogeneity across studies.
The training and the experience of the surgeon with robotic and/or endoscopic procedures may substantially influence the learning curve outcomes. In a multicenter study of 2612 patients, Lee et al observed that the learning curve for robotic thyroidectomy was shorter than that for endoscopic thyroidectomy, which was potentially attributed to the habits and experience of surgeons in using Da Vinci robot rather than laparoscopic instruments and platform that are more commonly used in thoracic or digestive surgeries. 49 The same team reported in another study that the learning curve for inexperienced surgeons to perform robotic thyroidectomy was 35 to 40 operations, whereas that for endoscopic thyroidectomy using a gasless transaxillary approach was 55 to 60 operations. 50 Similar observations were reported by Kang et al who reported that endoscopic procedures are limited for untrained head and neck surgeons by video camera platform instability, two-dimensional imaging, motion of straight endoscopic instruments, and unsatisfactory operator ergonomics. 37 In that vein, Kuo et al have suggested that prior experience with robotic or endoscopic extra cervical approaches may refine the skill proficiency in the transoral endoscopic thyroid surgery build-up period. 51 Although most studies included in this review evaluated the learning curve of a single experienced surgeon, the lack of information about the surgeon training and experience may limit the establishment of minimum number of cases for reaching proficiency, especially for young surgeons.
The potential influence of experience was investigated in an extensive review of the outcomes of learning curves for robotic thyroidectomy in the Republic of Korea, which categorized patients into 2 groups: those treated by surgeons with and without experience in robotic thyroid surgery. 50 In this study, the acquisition of proficiency in robotic thyroidectomy demonstrates distinct learning trajectories, with cumulative case thresholds of 50 procedures for total thyroidectomy and 40 procedures for subtotal thyroidectomy. Upon surpassing these procedural benchmarks, surgeons without prior robotic experience achieved operative durations and perioperative metrics comparable to those of experienced practitioners. This convergence in technical parameters indicates the successful acquisition of the required skills and spatial orientation necessary for the competent execution of robotic-assisted thyroid resection. 50
The indications and inclusion criteria are additional influencing factors for learning curve. In the present review, the learning curve was evaluated on benign lesions only, malignant lesions, or both according to studies, whereas approximately half of studies included both lobectomy and total thyroidectomy into a single learning curve calculation. Moreover, in some studies, the learning curves were primarily calculated on thyroid procedures combined with central or lateral neck dissections.16,24,26-28,31,37,38,40,47 This heterogeneity was highlighted in the summary provided in Table 4, where the learning curve of transoral robotic thyroidectomy was evaluated on 845 patients who underwent total (n = 107) and partial (n = 533) thyroidectomies, while the learning curve of studies of axillary approaches was primarily calculated on patients with total thyroidectomy (n = 2395/4093). Other patient-related outcomes were suggested to influence the learning curves, including the body mass index, 34 and the feedback of instructors. 50
To date, the type of robot appears to have a minimal impact on learning curve because most teams used the Da Vinci S, Si, or Xi. However, with the spread of the Da Vinci Single-Port, the learning curves of axillary, transoral, and facelift thyroid procedures may be lower than those for the other robot versions. Indeed, Kim reported that single-port transaxillary robotic thyroidectomy should be associated with enhanced precision, due to its articulated instruments and the high definition of the three-dimensional visualization, leading to meticulous dissection, minimizing the risk of complications such as recurrent laryngeal nerve injury and hypocalcemia. 52
Note that a recent systematic review by Wang et al compared learning curves between endoscopic and robotic thyroidectomy, reporting faster learning curves for robotic approaches (IRR = 0.64) and identifying CUSUM analysis and surgical approach as influential factors. 53 While their analysis focused on comparing robotic versus endoscopic techniques across mixed surgical approaches, our review specifically examined approach-stratified learning curves within robotic thyroidectomy, revealing that transoral (31 cases) and facelift (32 cases) approaches require fewer cases for proficiency compared to axillary approaches (34-46 cases). This approach-specific granularity is clinically significant as Wang et al demonstrated that retroauricular and transoral approaches had smaller learning curves than bilateral axillo-breast and transaxillary approaches in both robotic and endoscopic thyroidectomy. Our findings complement their work by providing approach-specific complication profiles during the learning process, showing transoral procedures have lower complication rates (11.1%) compared to axillary (16.7%) approaches. These converging findings from independent analyses strengthen the evidence that surgical approach selection should consider not only final outcomes but also learning trajectory efficiency and surgeon-specific anatomical expertise.
This review has several important limitations that warrant careful interpretation of findings. First, the scarcity of facelift approach studies (n = 4, 131 patients) requires particularly cautious interpretation of learning curve estimates for this technique, with conclusions considered preliminary pending larger prospective validation studies. Second, substantial heterogeneity across all included studies—in inclusion criteria (benign vs malignant lesions, procedure types), surgeon experience, patient characteristics, and surgical procedures—precluded meaningful meta-analytic synthesis due to high risk of compromising validity and interpretative value of pooled estimates, thereby limiting our analysis to qualitative synthesis which reduces statistical strength of approach comparisons. Third, learning curve definitions lacked standardization across studies. Similar to other surgical fields, proficiency endpoints varied substantially—including operative time stability, complication reduction, conversion rates, or composite measures—limiting direct comparability. Even among studies using CUSUM methodology, proficiency thresholds differed based on investigator-defined rather than consensus criteria. This heterogeneity likely explains the wide ranges in reported minimum case numbers for proficiency (15-66 cases). Future research should establish consensus definitions for learning curve endpoints in robotic thyroidectomy, incorporating validated competency frameworks that integrate technical performance metrics with patient safety outcomes.
Conclusion
The number of cases required to achieve proficiency in robotic thyroid surgeries may depend on the surgical approach, with transoral approaches and, tentatively, facelift approaches (based on limited evidence) suggested as faster than axillary ones. The heterogeneities across studies for inclusion and exclusion criteria, and surgeon experience, limit the establishment of definitive proficiency data. Future prospective studies are needed to standardize learning definitions and analyze how surgeon-specific factors (experience, age, prior training) impact the learning curves.
Footnotes
Acknowledgements
The librarian for the review conduction.
Author Contributions
Jérôme R. Lechien: design, acquisition of data, data analysis and interpretation, drafting, final approval, and accountability for the work; final approval of the version to be published; agreement to be 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.
Declaration of Conflicting Interests
The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author received no financial support for the research, authorship, and/or publication of this article.
Ethical Approval
The IRB was not required.
