Materials and methods
Eligibility criteria
Literature search and study selection
Data collection
Outcomes
Risk of bias
Results
Study selection
Study characteristics
Author, year | Country | Study design | Technique | Centers | Surgeons | Patients | Exclusion criteria | Learning curve study aim |
---|---|---|---|---|---|---|---|---|
Kim (2014) [14] | South Korea | Retrospective | R-TME | 1 | 1 | 167 | None | Primary aim |
Akmal (2012) [23] | South Korea | Prospective | R-TME | 1 | 1 | 80 | None | Primary aim |
Foo (2015) [24] | Hong Kong | Prospective | R-TME | 1 | 1 | 39 | Abdominoperineal resection, Hartmann resection | Primary aim |
Sng (2013) [52] | South Korea | Retrospective | R-TME | 1 | 1 | 197 | Low rectal tumor, > 5 cm size Male, T4b, anterior invasion | Primary aim |
Jiménez-Rodriguez (2013) [13] | Spain | Not mentioned | R-TME | 1 | 3 | 43 | None | Primary aim |
Yamaguchi (2015) [53] | Japan | Retrospective | R-TME | 1 | 1 | 80 | None | Primary aim |
Kim (2014) [54] | South Korea | Retrospective | R-TME | 1 | 2 | 200 | None | Primary aim |
Odermatt (2017) [55] | United Kingdom | Retrospective | R-TME | 1 | 2 | 90 | None | Primary aim |
Kawai (2018) [56] | Japan | Retrospective | R-TME | 1 | 1 | 131 | None | Primary aim |
Park (2014) [15] | South Korea | Retrospective | R-TME | 1 | 1 | 130 | Synchronous procedure Lateral lymph node dissection | Primary aim |
Byrn (2014) [28] | United States | Retrospective | R-TME | 1 | 1 | 51 | History of laparotomy for abdominopelvic surgery Large risk of conversion, extreme age or comorbidities | Primary aim |
Morelli (2016) [29] | Italy | Retrospective | R-TME | 1 | 1 | 50 | None | Secondary aim |
Kim (2012) [25] | South Korea | Prospective | R-TME | 1 | 1 | 62 | Acute surgery, acute obstruction History of abdominal surgery, severe cardiopulmonary disease | Primary aim |
Kuo (2014) [30] | Taiwan | Retrospective | R-TME | 1 | 1 | 36 | None | Secondary aim |
D’Annibale (2013) [31] | Italy | Retrospective | R-TME | 1 | 1 | 50 | None | Secondary aim |
Lee (2020) [35] | South Korea | Retrospective | R-TME | 1 | 1 | 506 | No adenocarcinoma, palliative intent | Primary aim |
Olthof (2020) [32] | The Netherlands | Retrospective | R-TME | 1 | 2 | 100 | None | Primary aim |
Aghayeva (2020) [33] | Turkey | Retrospective | R-TME | 1 | unclear | 96 | Abdominoperineal resection Missing value for operative time | Primary aim |
Gachabayov (2020) [57] | USA, South Korea, Spain, Taiwan, Italy, Russia | Not mentioned | R-TME | 5 | 5 | 235 | None | Primary aim |
Noh (2020) [34] | South Korea | Retrospective | R-TME | 1 | 5 | 662 | Abdominoperineal resection, other synchronous surgical procedures Palliative intent, R2 resection for macroscopic residual disease | Primary aim |
Koedam (2018) [8] | The Netherlands | Not mentioned | TaTME | 1 | 3 | 138 | None | Primary aim |
Lee (2018) [9] | United States | Retrospective | TaTME | 1 | 4 | 87 | High rectum carcinoma Benign lesions or lesions fit for local excision | Primary aim |
Mege (2018) [36] | France | Retrospective | TaTME | 1 | 1 | 34 | Tumor in mid or high rectum, Abdominoperineal resection | Primary aim |
Rubinkiewicz (2020) [37] | Poland | Retrospective | TaTME | 1 | 1 | 66 | None | Primary aim |
Persiani,2020[38] | Italy | Retrospective | TaTME | 1 | 1 | 121 | TaTME for IBD or locoregional recurrence after previous rectal surgery High rectal cancer | Primary aim |
Caycedo-Marulanda (2020) [48] | Canada | Retrospective | TaTME | 1 | 1 | 100 | High rectal cancer | Primary aim |
Zeng (2021) [50] | China | Retrospective | TaTME | 1 | 1 | 171 | T4b, stage IV tumors, emergency surgery | Primary aim |
Oostendorp, 2021 [49] | The Netherlands | Retrospective | TaTME | 6 | Unclear | 624 | None | Primary aim |
Balik (2010) [39] | Turkey | Retrospective | L-TME | 1 | 3 | 284 | Emergency surgery, inoperability | Primary aim |
Tsai (2015) [40] | Taiwan | Retrospective | L-TME | 1 | 1 | 39 | Abdominoperineal resection, Hartmann resection Conversion and single port laparoscopy | Primary aim |
Bege (2010) [11] | France | Prospective | L-TME | 1 | 1 | 127 | T4 or fixed tumor, synchronous liver resection Abdominoperineal resection Medical contraindication or refusal for laparoscopy | Primary aim |
Lujan (2014) [41] | Spain | Retrospective | L-TME | 1 | 2 | 120 | BMI > 35, carcinoma in lower 1/3 of the rectum | Primary aim |
Kayano (2011) [58] | Japan | Not mentioned | L-TME | 1 | 1 | 250 | Combined resections (cholecystectomy, hepatectomy, hysterectomy) | Primary aim |
Agha, 2008[42] | Germany | Retrospective | L-TME | 1 | 6 | 300 | Acute resection, transanal local resections Local recurrent disease | Secondary aim |
Ito (2009) [59] | Japan | Not mentioned | L-TME | 1 | Multiple | 200 | T3-T4 tumor, T2 carcinoma in middle or lower rectum | Secondary aim |
Son (2010) [12] | South Korea | Retrospective | L-TME | 1 | 1 | 431 | Inoperable disease | Primary aim |
Fukunaga (2008) [26] | Japan | Prospective | L-TME | 1 | 1 | 97 | Emergency resection, abdominoperineal resection, obstruction Morbid obesity, prior major lower abdominal surgery Tumor occupying most of the pelvis, carcinoma below peritoneal deflection Lateral lymph node dissection, | Secondary aim |
Kim (2014) [10] | South Korea | Retrospective | L-TME | 1 | 1 | 512 | Palliative resection, Abdominoperineal resection, Hartmann resection | Primary aim |
Park (2009) [27] | South Korea | Prospective | L-TME | 1 | 1 | Unknown | None | Secondary aim |
Kuo (2013) [43] | Taiwan | Retrospective | L-TME | 1 | 2 | 28 | Low anterior resection without need for intersphincteric resection | Secondary aim |
Wu (2017) [44] | China | Retrospective | L-TME | 1 | 3 | 281 | ASA 4, BMI > 35, Neoadjuvant therapy, pregnancy History of major abdominal surgery, malignancy within 5 years Metastatic or in situ disease, palliative resection, emergency resection | Primary aim |
Melich (2015) [45] | South Korea | Retrospective | R-TME vs L-TME | 1 | 1 | 92 vs 106 | Combined procedure | Primary aim |
Morelli (2018) [46] | Italy | Retrospective | R-TME Si vs R-TME Xi | 1 | 1 | 40 vs 40 | None | Secondary aim |
Park (2014) [47] | South Korea | Retrospective | R-TME vs L-TME | 1 | 1 | 89 vs 89 | Synchronous operation Lateral lymph node dissection | Primary aim |
Wang (2021) [51] | China | Retrospective | R-TME vs L-TME | 1 | 1 | 40 vs 65 | Combined resections, palliative resections, ASA IV, previous abdominal pelvic surgery | Primary aim |
Risk of bias
Author/year | Clearly stated aim | Inclusion of consecutive patients | Prospective collection of data | Endpoints appropriate to the aim | Unbiased assessment of endpoints | FU appropriate for study aim | Loss to follow up < 5% | Prospective calculation of the study size | Adequate control group | Contemporary groups | Baseline equivalence of groups | Adequate statistical analyses |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Kim (2014) [14] | 2 | 0 | 1 | 2 | 1 | 0 | 0 | 0 | NA | NA | NA | 2 |
Akmal (2012) [23] | 2 | 2 | 2 | 1 | 0 | NA | 0 | 0 | NA | NA | NA | 1 |
Foo (2015) [24] | 2 | 1 | 2 | 1 | 2 | NA | 0 | 0 | NA | NA | NA | 2 |
Sng (2013) [52] | 2 | 1 | 1 | 1 | 2 | NA | 0 | 0 | NA | NA | NA | 2 |
Jiménez-Rodriguez (2013) [13] | 2 | 2 | 0 | 2 | 1 | 0 | 0 | 0 | NA | NA | NA | 2 |
Yamaguchi (2015) [53] | 2 | 2 | 1 | 1 | 2 | NA | 0 | 0 | NA | NA | NA | 2 |
Kim (2014) [54] | 2 | 2 | 1 | 1 | 2 | NA | 0 | 0 | NA | NA | NA | 2 |
Odermatt (2017) [55] | 2 | 2 | 1 | 2 | 2 | 2 | 0 | 0 | NA | NA | NA | 2 |
Kawai (2018) [56] | 2 | 2 | 1 | 1 | 2 | NA | 0 | 0 | NA | NA | NA | 2 |
Park (2014) [15] | 2 | 2 | 1 | 2 | 2 | 1 | 0 | 0 | NA | NA | NA | 2 |
Byrn (2014) [28] | 1 | 1 | 1 | 1 | 0 | NA | 0 | 0 | NA | NA | NA | 1 |
Morelli (2016) [29] | 2 | 2 | 1 | 1 | 1 | NA | 0 | 0 | NA | NA | NA | 2 |
Kim (2012) [25] | 2 | 2 | 2 | 1 | 2 | NA | 0 | 0 | NA | NA | NA | 1 |
Kuo (2014) [30] | 2 | 0 | 1 | 1 | 1 | NA | 0 | 0 | NA | NA | NA | 1 |
D’Annibale (2013) [31] | 2 | 2 | 1 | 1 | 1 | NA | 0 | 0 | NA | NA | NA | 1 |
Lee (2020) [35] | 2 | 2 | 1 | 2 | 2 | 2 | 0 | 0 | NA | NA | NA | 2 |
Olthof (2020) [32] | 2 | 2 | 1 | 2 | 2 | NA | 0 | 0 | NA | NA | NA | 2 |
Aghayeva (2020) [33] | 2 | 2 | 1 | 1 | 2 | NA | 0 | 0 | NA | NA | NA | 2 |
Gachabayov (2020) [57] | 2 | 2 | 0 | 1 | 2 | NA | 0 | 0 | NA | NA | NA | 2 |
Noh (2020) [34] | 2 | 2 | 1 | 2 | 2 | 2 | 0 | 0 | NA | NA | NA | 2 |
Koedam (2018) [8] | 2 | 2 | 0 | 2 | 2 | 2 | 0 | 0 | NA | NA | NA | 2 |
Lee (2018) [9] | 2 | 2 | 1 | 2 | 1 | 2 | 0 | 2 | NA | NA | NA | 2 |
Caycedo-Marulanda (2020) [48] | 2 | 2 | 1 | 1 | 2 | 2 | 0 | 0 | NA | NA | NA | 2 |
Mege (2018) [36] | 2 | 2 | 1 | 1 | 1 | NA | 0 | 0 | NA | NA | NA | 1 |
Rubinkiewicz (2020) [37] | 2 | 2 | 1 | 2 | 1 | NA | 0 | 0 | NA | NA | NA | 2 |
Persiani (2020) [38] | 2 | 2 | 2 | 2 | 2 | 2 | 0 | 0 | NA | NA | NA | 2 |
Zeng (2021) [50] | 2 | 2 | 1 | 1 | 2 | NA | 0 | 0 | NA | NA | NA | 2 |
Oostendorp (2021) [49] | 2 | 2 | 1 | 2 | 2 | 2 | 0 | 0 | NA | NA | NA | 1 |
Balik (2010) [39] | 2 | 0 | 1 | 1 | 2 | 1 | 0 | 0 | NA | NA | NA | 1 |
Tsai (2015) [40] | 2 | 1 | 1 | 1 | 1 | NA | 0 | 0 | NA | NA | NA | 1 |
Bege (2010) [11] | 1 | 1 | 2 | 2 | 1 | 1 | 0 | 0 | NA | NA | NA | 2 |
Lujan (2014) [41] | 2 | 1 | 1 | 1 | 1 | 2 | 0 | 0 | NA | NA | NA | 1 |
Kayano (2011) [58] | 2 | 2 | 0 | 1 | 1 | 0 | 0 | 0 | NA | NA | NA | 1 |
Agha (2008) [42] | 1 | 0 | 1 | 1 | 1 | NA | 0 | 0 | NA | NA | NA | 1 |
Ito (2009) [59] | 2 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | NA | NA | NA | 1 |
Son (2010) [12] | 2 | 2 | 1 | 2 | 1 | 0 | 0 | 0 | NA | NA | NA | 2 |
Fukunaga (2008) [26] | 1 | 1 | 2 | 1 | 1 | NA | 0 | 0 | NA | NA | NA | 1 |
Kim (2014) [10] | 2 | 1 | 0 | 2 | 2 | 2 | 2 | 0 | NA | NA | NA | 2 |
Park (2009) [27] | 1 | 0 | 2 | 2 | 2 | 2 | 0 | 0 | NA | NA | NA | 1 |
Kuo (2013) [43] | 2 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | NA | NA | NA | 1 |
Wu (2017) [44] | 2 | 1 | 1 | 1 | 1 | NA | 0 | 0 | NA | NA | NA | 2 |
Melich (2015) [45] | 2 | 2 | 1 | 2 | 1 | 0 | 0 | 0 | 2 | 2 | 1 | 2 |
Morelli (2018) [46] | 2 | 2 | 1 | 1 | 1 | NA | 0 | 0 | 2 | 1 | 1 | 1 |
Park (2014) [47] | 2 | 1 | 1 | 1 | 2 | NA | 0 | 0 | 2 | 2 | 1 | 2 |
Wang (2021) [51] | 2 | 1 | 1 | 1 | 2 | NA | 0 | 0 | 2 | 2 | 2 | 1 |
Statistical methods of learning curve analyses
Author, year | Technique | Learning curve characteristics | Learning curve analysis | Conclusion according to article | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Analysis | Previous experience with surgical technique | Variable (IOC) | Analysis | Variable (POC) | Analysis | CRM rate | Analysis | Operative time | Analysis | Other variable | Analysis | Length | |||
Kim (2014) [14] | R-TME | Per surgeon | Not mentioned | – | – | – | – | – | – | Operative time Console time | MAAD: 33 MAAS: 72 | Combination: Conversion, IOC, POC, CRM + , OT > 2 SD | RA-CUSUMD: 32 | 32 | |
Akmal (2012) [23] | R-TME | Per surgeon | Not mentioned | – | – | – | – | – | – | – | – | – | – | ||
Foo (2015) [24] | R-TME | Per surgeon | 30 robotic RR assisted < 5 open/lap RR | – | – | – | – | – | – | Operative time | CUSUMD: 8 CUSUMS: 25 | – | – | 25 | |
Sng (2013) [52] | R-TME | Per surgeon | > 2000 lap CRR > 1000 lap RR | – | – | – | – | – | – | Console time | CUSUMD: 35 CUSUMS: 128 | – | – | 35 | |
Jiménez-Rodriguez (2013) [13] | R-TME | Per institute | Long experience in lap Robot training | – | – | – | – | – | – | Operative time | CUSUMD: 11 CUSUMS: 21 | Combination: Conversion, IOC, POC, mortality | CUSUMD: 11 CUSUMS: 23 | 23 | |
Yamaguchi (2015) [53] | R-TME | Per surgeon | Expert in RR | – | – | – | – | – | – | Operative time | CUSUMD: 25 CUSUMS: 50 | – | – | 25 | |
Kim (2014) [54] | R-TME | Per surgeon | Surg A 200 open CRR, < 30 lap Surg B 800 open CRR, > 300 lap Robot training | – | – | – | – | – | – | Operative time | – | – | – | – | |
Odermatt (2017) [55] | R-TME | Per surgeon | Surg A: 1500 CRR Surg B: 400 CRR Robot training | – | – | Morbidity (CD 3b-5) | – | – | – | Operative time | CUSUMD: 7 (Surg A) CUSUMD: 15 (Surg B) | – | – | 15 | |
Kawai (2018) [56] | R-TME | Per surgeon | Substantial lap CRR Robot training | – | – | – | Console time | CUSUMD: 19 CUSUMS: 78 | – | – | 19 | ||||
Park (2014) [15] | R-TME | Per surgeon | 2 year CRC fellowship 6 lap, 10 open CRR | – | – | – | – | – | – | Operative time | CUSUMD: 44 CUSUMS: 78 | Combination: Conversion, R1, < 12 LN, LR, POC | RA-CUSUMD: 75 | 75 | |
Byrn (2014) [28] | R-TME | Per surgeon | 1 year staff level experience of lap pelvic dissection | – | – | – | – | – | – | Operative time | SGA: - | – | – | – | |
Morelli (2016) [29] | R-TME | Per surgeon | > 500 lap procedures | – | – | – | – | – | – | Operative time | CUSUMD: 19 | – | – | 19 | |
Kim (2012) [25] | R-TME | Per surgeon | > 20 year experience in open RR | – | – | – | – | – | – | Operative time | SGA: 20 | – | – | 20 | |
Kuo (2014) [30] | R-TME | Per surgeon | Not mentioned | – | – | – | – | – | – | Operative time | MAA: 19 | – | – | 19 | |
D’Annibale (2013) [31] | R-TME | Per institute | Not mentioned | – | – | – | – | – | – | Operative time | Sequence: 25 CUSUMD: 22 | – | – | – | |
Lee (2020) [35] | R-TME | Per surgeon | 3000 lap TMEs | – | – | Morbidity (CD 3–5) | RA-CUSUMS: 191 | CRM + DRM + | RA-CUSUMS: 418 | – | – | Combination: Conversion, CD 3–5, R1, < 12 LN or < 8 LN (CRT) | RA-CUSUMD: 177 | 177 | |
Olthof (2020) [32] | R-TME | Per Institute | Intuitive training program Experienced colorectal center | – | – | CCI Major morbidity (CD 3–5) | CUSUM: 40 CUSUM: 40 | Operative time | CUSUM: 20 | Anastomotic leakage | CUSUM: 30–40 | 40 | |||
Aghayeva (2020) [33] | R-TME | Per institute | Not mentioned | – | – | – | – | – | – | Operative time | CUSUMD: 52 | – | – | 52 | |
Gachabayov (2020) [57] | R-TME | Per surgeon | Not mentioned | – | – | – | – | – | – | Operative time | CUSUMD: 8–25 CUSUMS: 12–56 | – | – | – | |
Noh (2020) [34] | R-TME | Per surgeon | Not mentioned Different previous lap experience | – | – | – | – | – | – | Operative time | CUSUMD: 23–110 | Local failure (CRM + , LR) Surgical failure (conversion, AL) | CUSUMD: - CUSUMD: - | 23–110 | |
Koedam (2018) [8] | TaTME | Per Institute | > 75 lap CRR resect annual > 30 TAMIS annual | – | – | Morbidity (CD 3b-5) | RA-CUSUMD: 40 | – | – | Operative time | CUSUMD: 80 | – | – | 40 | |
Lee (2018) [9] | TaTME | Per institute | Proficient in lap RR Proficient in TAMIS | - | - | Morbidity | RA-CUSUMD:29 RA-CUSUMS: 36 | - | Operative time | CUSUMD: 36 CUSUMS: 51 | Combination: R1, incomplete TME quality, | CUSUMD: 36 CUSUMS: 51 | 51 | ||
Caycedo-Marulanda (2020) [48] | TaTME | Per institute | Not mentioned | – | – | – | – | – | – | – | – | Anastomotic leakage | CUSUM: 50 | 45–51 | |
Mege (2018) [36] | TaTME | Per surgeon | Not mentioned | – | – | – | – | – | – | – | – | – | – | – | |
Rubinkiewicz (2020) [37] | TaTME | Per surgeon | Training in reference centers | Yes | CUSUMS: 40 | Morbidity | CUSUMS:30 | – | – | Operative time | CUSUMS: 40 | TME quality | CUSUMS: - | 40 | |
Persiani (2020) [38] | TaTME | Per Institute | Not mentioned | – | – | Morbidity | RA- CUSUMD:24 RA- CUSUMS:69 Bernoulli CUSUM: 21 Reference CUSUM:108 | Operative time | RA- CUSUMD:54 RA- CUSUMS:87 Bernoulli CUSUM: 71 | Reoperation rate | RA- CUSUMD:54 RA- CUSUMS:54 Bernoulli CUSUM: 31 Reference CUSUM: 69 | 71 | |||
Major Morbidity | RA- CUSUMD:54 RA- CUSUMS:54 Bernoulli CUSUM: 55 Reference CUSUM: 54 | Anastomotic leakage | RA- CUSUMD:78 RA- CUSUMS:78 Bernoulli CUSUM: 42 Reference CUSUM: 42 | ||||||||||||
Zeng (2021) [50] | TaTME | Per surgeon | Not mentioned | – | – | – | – | – | – | Operative time | CUSUMD: 42 CUSUMS: 95 | – | – | 42–95 | |
Oostendorp (2021) [49] | TaTME | Per Institute | Not mentioned | – | – | – | – | – | – | – | – | Local recurrence | SGA: - | – |
Author, year | Technique | Learning curve characteristics | Learning curve analysis | Conclusion according to article | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Analysis | Previous experience with surgical technique | Variable (IOC) | Analysis | Variable (POC) | Analysis | CRM rate | Analysis | Operative time | Analysis | Other variable | Analysis | Length | ||
Balik (2010) [39] | L-TME | Per institute | 305 open + lap CR | – | – | – | – | – | – | Operative time | SGA: - Sequence: - | – | – | – |
Tsai (2015) [40] | L-TME | Per surgeon | Fellowship completed Little experience in lap | – | – | – | – | – | – | Operative time | MAA: 22 | – | – | 22 |
Bege (2010) [11] | L-TME | Per Institute | Not mentioned | – | – | Morbidity | CUSUMD:45 | – | – | – | – | Combination (comb): POC, LR, Conversion, R1 | CUSUMD: 50 | 50 |
Lujan (2014) [41] | L-TME | Per institute | Ample experience in open CRR Skilled advanced lap | – | – | – | – | – | – | Operative time | Sequence: - SGA: - | – | – | – |
Kayano (2011) [58] | L-TME | Per surgeon | Not mentioned | – | Morbidity | SGA: 200 | – | – | Operative time | MAA: 50 | Conversion | SGA: 150 | – | |
Agha (2008) [42] | L-TME | Per institute | Experience with lap CR No experience with lap RR | – | – | SSI | SGA: 20 | – | – | Operative time | SGA: 40 | – | – | – |
Ito (2009) [59] | L-TME | Per institute | Not mentioned | – | – | Morbidity | SGA: - | – | – | Operative time | SGA: 40 | – | – | – |
Son (2010) [12] | L-TME | Per surgeon | Not mentioned | Yes | CUSUMD: 243 | Morbidity | CUSUMD: 79 | – | – | Operative time | MAA:61 | Conversion Transfusion volume | RA-CUSUMDl: 61 (Conv) SGA:75 (Transfusion volume) | 79 |
Fukunaga (2008) [26] | L-TME | Per surgeon | Not mentioned | – | – | – | – | – | Operative time | Sequence: - | – | – | – | |
Kim (2014) [10] | L-TME | Per surgeon | A: Fast experience B: Trained by A | – | – | – | – | CRM + | RA-CUSUMD:50 (A) RA-CUSUMD:70 (B) | Operative time | MAAA: 90 MAAB: 90 | LR | RA- CUSUMD:110 (A) RA- CUSUMD: 110 (B) | 110 |
Park (2009) [27] | L-TME | Per surgeon | Not mentioned | – | – | – | – | – | – | Operative time | MAA: 30 | LR Conversion | SGA: 69 (LR) CUSUMD: 13 (Conversion) | 69 |
Kuo (2013) [43] | L-TME | Per institute | Not mentioned | – | – | – | – | – | – | Operative time | SGA: 17 | – | – | 17 |
Wu (2017) [44] | L-TME | Unclear | Not mentioned | – | – | – | – | – | – | Operative time | CUSUMD: 36–42 MAA: 36–47 | – | – | 40 |
Melich (2015) [45] | R-TME vs L-TME | Per surgeon | 700 open CR, 50 open RR, 150 lap CR | – | – | AL, intra-abdominal abscess | CUSUM: - | CRM + | CUSUM: - | Operative time | MAA: - | – | – | – |
Morelli (2018) [46] | R-TMESi vs R-TME Xi | Per surgeon | > 100 RR > 100 lap surgery | – | – | – | – | – | – | Operative time | CUSUMD: 19 | – | – | 19 |
Park (2014) [47] | R-TME vs L-TME | Per surgeon | 2 year lap CRR fellowship | – | – | – | – | – | – | Operative time | CUSUMD: 44 (robot) MAA: 21 (robot) MAA: 69 (lap) CUSUMD: 41 (lap) | – | – | 44 (robot) 41 (lap) |
Wang (2021) [51] | R-TME vs L-TME | Per surgeon | > 300 open CRR > 150 lap CRR Robot training | – | – | – | – | – | – | Operative time | CUSUMD: 17 (rob) CUSUMD: 34 (lap) | – | – | 17 (rob) 34 (lap) |
Length of the learning curve
Before-after learning curve comparison
Author, year | Comparison | Technique | During learning curve | After learning curve | ||||||
---|---|---|---|---|---|---|---|---|---|---|
Intraop complications | Postop complications | CRM + | Operative time | Intraop complications | Postop compicationsl | CRM + | Operative time | |||
Kim (2014) [14] | 32 vs 135 | R-TME | 3 (9.4%) | 5 (15.6%) | 3 (9.4%) | 252 (42) * | 7 (5.2%) | 23 (17.0%) | 5 (3.7%) | 203 (46) * |
Foo (2015) [24] | 25 vs 14 | R-TME | – | 4 (16%) | 0 | 446 (102) * | – | 0 | 2 (14.3%) | 311 (165) * |
Sng (2013) [52] | 35 vs 162 | R-TME | – | 6 (17.1%) | 0 | 265 (190–470) * | – | 68 (42.0%) | 2 (1.2%) | 270 (145–515) * |
Jiménez-Rodriguez (2013) [13] | 23 vs 20 | R-TME | 3 (13.0%) | 5 (21.7%) | – | 189 (39) | 0 | 1 (5.0%) | – | 208 (44) |
Yamaguchi (2015) [53] | 25 vs 55 | R-TME | – | 3 (12.0%) | – | 415 (156–683) * | – | 5 (9.1%) | – | 240 (135–529) * |
Kawai (2018) [56] | 19 vs 111 | R-TME | – | 2 (11.8%) | – | 305 (111) * | – | 13 (11.7%) | – | 227 (112) * |
Park (2014) [15] | 78 vs 52 | R-TME | – | 8 (10.3%) | 6 (7.7%) | 212 (110–338) * | – | 15 (28.8%) | 3 (5.8%) | 182 (109–376) * |
Morelli, 2016[29] | 19 vs 31 | R-TME | – | 7 (35.0%) | – | – | – | 9 (29.0%) | – | – |
Kim (2012) [25] | 20 vs 42 | R-TME | – | 3 (15.0%) | – | 454 (112) | – | 5 (11.9%) | – | 359 (62) |
Kuo (2014) [30] | 19 vs 17 | R-TME | – | – | 1 (5.3%) | 520 (360–720) | – | – | 3 (17.6%) | 448 (315–585) |
Lee (2020) [35] | 177 vs 329 | R-TME | – | 48 (27.1%) | 10 (5.4%) | 361 (313–432) | – | 77 (23.5% | 19 (5.9%) | 337 (292–398) |
Aghayeva (2020) [33] | 52 vs 44 | R-TME | – | 15 (28.8%) | 2 (3.9%) | 380 (109)* | – | 7 (15.9%) | 1 (2.7%) | 323 (103)* |
Gachabayov (2020) [57] | 83 vs 152 | R-TME | – | 20 (24.1%) | – | 244 (123)* | – | 51 (33.5%) | – | 192 (100) * |
Koedam (2018) [8] | 40 vs 98 | TaTME | – | 23 (57.5%) | 1 (2.5%) | 199 (95–329) * | – | 53 (54.1%) | 1 (1.0%) | 153 (80–261) * |
Lee (2018) [9] | 51 vs 36 | TaTME | 6 (12%) | 23 (45%) | 2 (4%) | 278 (84) | 2 (6%) | 15 (42%) | 0 | 270 (73) |
Rubinkiewicz (2020) [37] | 40 vs 26 | TaTME | 5 (20%) * | 13 (33%) * | – | 270 (240–300) * | 1 (13%) * | 2 (8%) * | – | 210 (170–240) * |
Persiani (2020) [38] | 69 vs 52 87 vs 34 | TaTME | – | 31 (45%) | – | – 294 (59)* | – | 15 (25%) | – | – 259 (46)* |
Bege (2010) [11] | 50 vs 77 | L-TME | – | 26 (52%)* | 5 (10%) | 445 (117) | – | 27 (35.1%) * | 7 (9%) | 414 (97) |
Kayano (2011) [58] | 50 vs 200 | L-TME | – | 14 (28%) | 0 | – | – | 44 (22%) | 0 | – |
Kuo (2013) [43] | 17 vs 11 | L-TME | – | – | 3 (17.6%) | 402 (210–570) * | – | – | 1 (9.1%) | 331 (210–450) |
Morelli (2018) [46](Si) | 19 vs 21 | R-TME | – | 7 (36.8%) | – | 335 (64) * | – | 7 (33.3%) | – | 289 (42) * |
Morelli (2018) [46](Xi) | 19 vs 21 | R-TME | – | 4 (21.1%) | – | 305 (51) * | – | 6 (28.6%) | – | 264 (39) * |
Park (2014) [47] | 44 vs 45 | R-TME | – | 5 (11.4%) | 4 (9.1%) | 230 (49) * | – | 4 (8.9%) | 2 (4.4%) | 188 (53) * |
Park (2014) [47] | 41 vs 48 | L-TME | – | 8 (19.5%) | 2 (4.9%) | 242 (81) * | – | 15 (31.3%) | 4 (8.3%) | 169 (53) * |
Wang (2021) [51] | 17 vs 23 | R-TME | – | 1 (5.9%) | 1 (5.9%) | 361 (41)* | – | 2 (8.7%) | 1 (4.3%) | 324 (43) * |
Wang (2021) [51] | 34 vs 31 | L-TME | – | 2 (5.9%) | 0 (0.0%) | 338 (47) * | – | 2 (6.5%) | 0 (0.0%) | 302 (53) * |