Robot-Assisted vs. Conventional Laparoscopic Surgery for Endometrial Cancer: What an Updated Review of 10,673 Patients Shows

Table of Contents

• Key Points
• Background: Why Compare These Two Surgeries?
• How the Researchers Conducted the Review
• The Studies and Patients Included
• Study Quality and Publication Bias
• Key Finding: Intraoperative Visceral Injuries
• Key Finding: Blood Transfusion
• Key Finding: Conversion to Open Surgery
• Key Finding: Cancer Recurrence
• Key Finding: Estimated Blood Loss
• Key Finding: Lymph Nodes Harvested
• Key Finding: Length of Hospital Stay
• Key Finding: Operative Time
• Key Finding: 3-Year and 5-Year Survival
• What These Findings Mean for Patients
• Limitations: What the Review Could Not Prove
• Practical Recommendations
• Frequently Asked Questions
• Source Information

Key Points

• In pooled data from 20 studies of 2,989 patients, robot-assisted surgery was linked to about 78 mL less estimated blood loss than conventional laparoscopy, though variation between studies was high.
• Across 17 studies of 2,791 patients, the risk of converting to open abdominal surgery was about one-third as high with robot-assisted surgery as with conventional laparoscopy.
• Operative time, blood transfusion, lymph nodes removed, hospital stay, recurrence, and 3-year and 5-year survival did not differ significantly between the two approaches in the pooled analyses.
• Only 2 of the 30 included studies were randomized trials; the other 28 were observational, and variation between studies was substantial for several outcomes.
• The paper's introduction notes that drawbacks of robotic surgery reported in other literature include longer operative times, higher costs, technical limitations, and the need for specialized staff and training; in this review's own pooled analysis, operative time did not differ significantly, and cost-effectiveness was not assessed.

Background: Why Compare These Two Surgeries?

Endometrial cancer is the most common gynecologic malignancy (cancer of the female reproductive organs) in high-income countries, and its incidence is increasing. The rise is driven by obesity, aging, and hormonal factors, which makes endometrial cancer a growing public health concern. The disease most often presents with postmenopausal bleeding.

Surgical staging is essential for assessing how far the disease has spread and for guiding treatment. Traditionally, surgeons performed this staging through open laparotomy (a large abdominal incision). Today, minimally invasive approaches such as laparoscopy and robotic surgery are preferred. These approaches offer lower morbidity (fewer complications) without compromising oncologic outcomes (cancer control results).

Conventional laparoscopic surgery (CLS) is a minimally invasive technique. The surgeon inserts a laparoscope (a thin camera) into the abdomen to guide a hysterectomy (removal of the uterus) and bilateral salpingo-oophorectomy (removal of both ovaries and fallopian tubes). Because laparoscopy is less invasive, it is associated with less pain, faster recovery, and a shorter hospital stay.

Despite these advantages over open surgery, laparoscopy can still cause major complications. These include injury to major blood vessels or nerves, lymphedema (swelling caused by lymph fluid buildup), and associated cellulitis (skin infection). The risk of these complications means that an experienced surgeon should perform the procedure, with skill in laparoscopic hysterectomy and lymph node sampling.

Robot-assisted laparoscopic surgery (RALS), also called robotic surgery, has emerged as an advanced alternative. Gynecologic oncologists have adopted RALS rapidly since 2005, when the US Food and Drug Administration (FDA) approved it. Compared with conventional laparoscopy, RALS may offer greater dexterity, tremor filtration (filtering out hand shaking), reduced reliance on an assistant, and a shorter learning curve.

Several studies comparing robotic-assisted hysterectomy with lymphadenectomy (lymph node removal) to traditional laparoscopy suggest advantages for the robotic approach. These advantages include reduced blood loss and a shorter operative time. However, one study by Cardenas-Goicoechea and colleagues reported that the mean number of lymph nodes retrieved was similar between the groups. That study also found no significant differences in time to discharge, readmission, or reoperation rates.

Robotic surgery has also been shown to be a feasible, safe, and reproducible alternative to laparoscopic surgery, even in obese or elderly patients with endometrial cancer. Evidence in patients with severe obesity remains particularly relevant, because this group presents unique surgical challenges. A retrospective study compared robotic-assisted, laparoscopic, and vaginal hysterectomy in morbidly obese women with endometrial cancer. That study found that minimally invasive approaches, particularly robotic-assisted surgery, were feasible and safe in this high-risk group, with acceptable perioperative outcomes.

Nevertheless, robotic surgery has drawbacks. These include longer operative times, higher costs, technical limitations of the robotic system, and the need for specialized staff and training. Findings from studies comparing conventional and robot-assisted laparoscopy for endometrial cancer have been inconsistent. This inconsistency underscores the need for clearer evidence through comprehensive analysis.

The authors limited this review to clinical effectiveness, including operative, perioperative, and oncologic adequacy outcomes. Economic evaluations, such as cost-effectiveness, were outside the scope of this analysis. This updated meta-analysis adds recent studies comparing the two approaches. It evaluates perioperative and oncologic outcomes, including recurrence and overall survival, and it incorporates newly published randomized controlled trials. The authors also performed subgroup analyses and meta-regression to explore sources of heterogeneity (variation between studies).

How the Researchers Conducted the Review

The authors reported this meta-analysis according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. They registered the review prospectively with PROSPERO, an international registry of systematic reviews, under the registration number CRD420251120306.

The researchers searched PubMed, the Cochrane Library, and Google Scholar from database inception to April 15, 2025. They used predefined terms for robotic surgery, laparoscopy, and endometrial cancer to find studies comparing robot-assisted and conventional laparoscopic surgery for endometrial cancer. Boolean operators combined synonyms (OR) and different concepts (AND). The search included MeSH terms (standardized medical subject headings used in PubMed) and free-text keywords for every concept. The researchers applied filters for human and English-language publications.

Google Scholar was searched for supplementary or gray literature, including trial registries and conference abstracts. The authors acknowledge limitations regarding the reproducibility of Google Scholar searches. The search strategy followed Cochrane Handbook recommendations to ensure comprehensive and reproducible results. The full search strategies for each database are provided in Supplementary Table S1 of the original article.

Two reviewers screened titles and abstracts and assessed full texts. Disagreements were resolved by consensus with a third reviewer. The study selection process followed PRISMA guidelines and is illustrated in a PRISMA flow diagram (Figure S1 in the original article).

Studies were included if they were randomized controlled trials or observational studies. Each study had to compare robot-assisted laparoscopic surgery with conventional laparoscopic surgery in patients with endometrial cancer and report at least one predefined outcome measure. For multiple publications from the same cohort, only the most comprehensive or most recent report was included.

The exclusion criteria were:

• Conference abstracts, reviews, editorials, letters, and case reports
• Non-English publications
• Studies on recurrent endometrial cancer
• Studies without direct comparisons between RALS and CLS

Two reviewers independently extracted data using a standardized collection form. The extracted information included study characteristics (first author, year, country), study design, and sample size. It also included patient characteristics (age, body mass index, disease stage, tumor grade) and surgical characteristics (uterine weight and adjuvant therapy).

The primary outcome was intraoperative visceral injury, meaning injury during surgery to the ureters, bladder, bowel, or blood vessels. The secondary outcomes were operative time, estimated blood loss, blood transfusion rate, and total number of lymph nodes harvested. The secondary outcomes also included conversion to laparotomy, length of hospital stay, and recurrence rate. The remaining secondary outcomes were overall survival, 3-year survival, and 5-year survival.

Two reviewers independently assessed methodological quality. They evaluated randomized controlled trials with the Cochrane risk of bias tool (RoB 2.0) and observational studies with the Newcastle–Ottawa Scale (NOS). Disagreements were resolved by consensus with a third reviewer's input. The authors did not formally assess the certainty of evidence using GRADE, so conclusions about comparative effectiveness should be interpreted with caution.

The authors performed a random effects meta-analysis using Review Manager (RevMan) version 5.4.1. They analyzed survival outcomes (3-year and 5-year survival) using risk ratios (RRs), because the included studies reported data mainly as total events and total patients per group. Hazard ratios (HRs) were not consistently available and could not be derived because of the lack of time-to-event data. Kaplan–Meier curves were not uniformly reported in a form suitable for reliable digitization, so the authors did not reconstruct hazard ratios from survival curves. For continuous outcomes such as operative time and estimated blood loss, the authors used mean differences (MDs) with 95% confidence intervals (CIs).

The authors measured heterogeneity with the Higgins I² statistic. They classified I² values of 25–50%, 50–75%, and greater than 75% as mild, moderate, and severe heterogeneity, respectively. Statistical significance was set at p < 0.05 for all analyses. The authors used a random-effects model to account for anticipated clinical and methodological variability across studies.

The authors evaluated publication bias for outcomes that included 10 or more studies. They did this through visual inspection of funnel plots, in accordance with Cochrane Handbook recommendations. When funnel plots showed asymmetry, they performed Egger's regression test using Comprehensive Meta-Analysis software to further assess small-study effects. Outcomes with fewer than 10 studies were not formally assessed for publication bias because such analyses would be unreliable.

The authors conducted a series of prespecified subgroup analyses to explore potential sources of between-study heterogeneity. They stratified studies by:

1. Study design (randomized controlled trials versus observational studies)
2. Disease stage (early stage versus mixed or advanced-stage disease)
3. Body mass index (obese, defined as ≥ 30 kg/m², versus nonobese, defined as < 30 kg/m²)
4. Data reporting format (mean ± standard deviation versus values requiring statistical conversion from median and dispersion measures)
5. Geographic region (United States, Europe, and Asia)
6. Study size (large studies with ≥ 200 patients versus small studies with < 200 patients)

The authors performed subgroup analyses for all continuous outcomes, including estimated blood loss, length of hospital stay, operative time, and total lymph node harvest. They assessed differences between subgroups with the chi-square test for subgroup differences in RevMan, with a P value < 0.05 indicating statistical significance. For studies reporting continuous data as medians, the authors converted values to means and standard deviations using established statistical methods (for example, the method of Wan and colleagues). They also conducted additional subgroup analyses to evaluate the potential impact of these transformations on pooled estimates.

The authors performed meta-regression analyses to explore potential sources of heterogeneity. They evaluated two prespecified moderators, age and body mass index, across four continuous outcomes that showed substantial heterogeneity. The meta-regression models used the maximum likelihood estimator with random effects.

The Studies and Patients Included

The systematic literature search yielded 5,524 articles. After screening, the researchers excluded duplicates and ineligible articles. A total of 30 studies were included in the meta-analysis.

Two of the included studies were randomized controlled trials, and 28 were cohort studies. Together, the studies included 10,673 patients: 3,553 in the RALS group and 7,120 in the CLS group. The mean age was 56.34 years in the RALS group and 56.94 years in the CLS group.

Most included studies were observational in design (28 of 30), with only two randomized controlled trials. Baseline oncologic characteristics, including disease stage, tumor grade, uterine weight, and adjuvant therapy, were inconsistently reported across studies. Several of these variables were not reported in a substantial proportion of studies.

The included studies came from many countries and varied widely in size. The table below summarizes the study design, country, and group sizes for each included study.

• Argenta et al., 2022 — retrospective, USA — 566 RALS, 461 CLS (total 1,027)
• Bell et al., 2008 — retrospective, USA — 40 RALS, 30 CLS (total 70)
• Boggess et al., 2008 — retrospective, USA — 103 RALS, 81 CLS (total 184)
• Cardenas Goicoechea et al., 2014 — retrospective, USA — 187 RALS, 245 CLS (total 432)
• Chiou et al., 2015 — retrospective, Taiwan — 86 RALS, 150 CLS (total 236)
• Coronado et al., 2012 — retrospective, Spain — 71 RALS, 84 CLS (total 155)
• Corrado et al., 2015 — retrospective, Italy — 72 RALS, 277 CLS (total 349)
• Escobar et al., 2012 — retrospective, Korea — 30 RALS, 30 CLS (total 60)
• Eoh et al., 2021 — retrospective, Korea — 315 RALS, 3,248 CLS (total 3,563)
• Eoh et al., 2023 — retrospective, Korea — 551 RALS, 452 CLS (total 1,003)
• Gehrig et al., 2008 — retrospective, USA — 49 RALS, 32 CLS (total 81)
• Hiratsuka et al., 2023 — retrospective, Japan — 34 RALS, 31 CLS (total 65)
• Hoekstra et al., 2009 — prospective, USA — 32 RALS, 7 CLS (total 39)
• Johanssons et al., 2023 — retrospective, Australia — 39 RALS, 41 CLS (total 80)
• Jung et al., 2010 — prospective, Korea — 28 RALS, 25 CLS (total 53)
• Kivekas et al., 2025 — randomized controlled trial, Finland — 49 RALS, 48 CLS (total 97)
• Lim et al., 2011 — retrospective, USA — 122 RALS, 122 CLS (total 244)
• Maenpaa et al., 2016 — randomized controlled trial, Finland — 50 RALS, 49 CLS (total 99)
• Magrina et al., 2011 — retrospective, USA — 67 RALS, 37 CLS (total 104)
• Manchana et al., 2015 — retrospective, Thailand — 28 RALS, 47 CLS (total 75)
• Martino et al., 2011 — retrospective, USA — 101 RALS, 114 CLS (total 215)
• Nezhat et al., 2019 — retrospective, USA — 57 RALS, 48 CLS (total 105)
• Perroni et al., 2021 — retrospective, Italy — 455 RALS, 766 CLS (total 1,221)
• Seamon et al., 2009 — retrospective, USA — 105 RALS, 76 CLS (total 181)
• Seror et al., 2014 — retrospective, France — 40 RALS, 106 CLS (total 146)
• Shah et al., 2011 — retrospective, USA — 43 RALS, 118 CLS (total 161)
• Silva et al., 2018 — retrospective, Brazil — 44 RALS, 45 CLS (total 89)
• Turunen et al., 2013 — retrospective, Finland — 67 RALS, 150 CLS (total 217)
• Venkat et al., 2012 — retrospective, USA — 27 RALS, 27 CLS (total 54)
• Yoon et al., 2024 — retrospective, Korea — 95 RALS, 173 CLS (total 268)

Study Quality and Publication Bias

The authors assessed the quality of the 28 cohort studies and 2 randomized controlled trials using the Newcastle–Ottawa quality assessment scale and the RoB-2 tool, respectively. All included randomized controlled trials had a low risk of bias.

The authors assessed outcomes consisting of 10 or more studies for publication bias using funnel plots. Funnel plots that revealed asymmetry were further assessed for confirmation using Begg's and Egger's tests. The p values for Begg's and Egger's tests are provided in Table S4 of the original article.

Key Finding: Intraoperative Visceral Injuries

Robot-assisted surgery did not significantly reduce the risk of intraoperative visceral injury compared with conventional laparoscopy. Fourteen studies were included in this analysis, encompassing 5,774 patients: 1,274 in the RALS group and 4,500 in the CLS group.

The pooled analysis found a similar risk of intraoperative visceral injury between the RALS and CLS groups. The risk ratio was 0.72 (95% CI: 0.43–1.19; p = 0.20). Heterogeneity among the studies was minimal (I² = 0%), which indicates consistent findings across the included studies.

Overall, these results suggest that RALS does not significantly reduce the risk of intraoperative visceral injury compared with CLS. In plain terms, the chance of injury to the ureters, bladder, bowel, or blood vessels during surgery was statistically comparable between the two approaches.

Key Finding: Blood Transfusion

Blood transfusion rates were similar between the two surgical groups. Ten studies reported blood transfusion rates, including 1,805 patients: 768 in the RALS group and 1,037 in the CLS group.

The pooled analysis found no appreciable difference in blood transfusion rates between the two groups. The risk ratio was 0.73 (95% CI: 0.40–1.33; p = 0.30), with moderate heterogeneity (I² = 27%).

This means that patients who had robot-assisted surgery were not significantly more or less likely to need a blood transfusion than patients who had conventional laparoscopy.

Key Finding: Conversion to Open Surgery

Patients in the robot-assisted group had significantly fewer conversions to laparotomy (open abdominal surgery) than patients in the conventional laparoscopy group. This was one of the clearest differences between the two approaches.

The conversion rate was examined in 17 studies encompassing 2,791 patients: 1,247 in the RALS group and 1,544 in the CLS group. The risk ratio was 0.35 (95% CI: 0.23–0.53; p < 0.00001), with no heterogeneity (I² = 0%).

A risk ratio of 0.35 means that the risk of conversion to open surgery in the RALS group was about one-third of the risk in the CLS group. The very low p value (p < 0.00001) indicates that this finding is statistically highly significant, meaning there is less than a 0.001% probability that the difference is due to chance. The absence of heterogeneity (I² = 0%) means the studies agreed closely on this result.

Key Finding: Cancer Recurrence

There was no conclusive evidence that robot-assisted surgery reduced the risk of cancer recurrence compared with conventional laparoscopy. Six studies reported recurrence rates among 2,921 patients: 1,265 in the RALS group and 1,656 in the CLS group.

The pooled risk ratio was 0.85 (95% CI: 0.59–1.23; p = 0.39), with moderate heterogeneity (I² = 34%). Because the confidence interval crosses 1.0 and the p value is above 0.05, the difference was not statistically significant.

In practical terms, the data do not show that one surgical approach is better than the other at preventing the cancer from coming back.

Key Finding: Estimated Blood Loss

Robot-assisted surgery was associated with significantly less estimated blood loss than conventional laparoscopy. This was the other major difference between the two approaches.

Estimated blood loss was analyzed in 20 studies involving 2,989 patients: 1,302 in the RALS group and 1,687 in the CLS group. The pooled mean difference was −78.36 mL (95% CI: −99.07 to −57.65; p = 0.0001).

This means that, on average, patients having robot-assisted surgery lost about 78 mL less blood than patients having conventional laparoscopy. The p value of 0.0001 indicates that this finding is statistically significant.

However, heterogeneity was high (I² = 81%). Sensitivity and subgroup analyses did not fully explain this high heterogeneity. Therefore, the authors state that these results should be interpreted as indicative of a trend rather than definitive.

Key Finding: Lymph Nodes Harvested

The total number of lymph nodes harvested (removed and examined) was similar between the two groups. This measure matters because the number of lymph nodes removed is one indicator of surgical quality in cancer staging.

Twelve studies involving 1,980 patients (908 in the RALS group and 1,072 in the CLS group) reported total lymph node harvest. The pooled mean difference was 0.98 (95% CI: −2.36 to 4.31; p = 0.57).

This result was not statistically significant. However, heterogeneity was very high (I² = 90%), and sensitivity and subgroup analyses did not fully explain this variability. Therefore, the authors state that these results should be interpreted as indicative of a directional trend rather than a definitive effect.

Key Finding: Length of Hospital Stay

The length of hospital stay was similar between the two groups. Twenty-one studies involving 6,444 patients (1,555 in the RALS group and 4,889 in the CLS group) reported this outcome.

The pooled mean difference was −0.35 days (95% CI: −0.72 to 0.02; p = 0.07). This means that patients in the robot-assisted group stayed in the hospital about one-third of a day less, on average. However, the result did not reach statistical significance.

Heterogeneity was very high (I² = 94%), and sensitivity and subgroup analyses did not fully explain this variability. Therefore, the authors state that these results should be interpreted as indicative of a directional trend rather than a definitive effect.

Key Finding: Operative Time

Operative time did not differ significantly between robot-assisted and conventional laparoscopic surgery. Twenty-two studies involving 4,295 patients (1,799 in the RALS group and 2,496 in the CLS group) reported operative time.

The pooled mean difference was 11.49 minutes (95% CI: −7.12 to 30.10; p = 0.23). This means that robot-assisted surgery took about 11 minutes longer on average, but this difference was not statistically significant.

Heterogeneity was very high (I² = 97%), and sensitivity and subgroup analyses did not fully explain this variability. Therefore, the authors state that these results should be interpreted as indicative of a directional trend rather than a definitive effect.

Key Finding: 3-Year and 5-Year Survival

Overall survival at 3 years and at 5 years was not significantly different between the two surgical approaches. Four studies reported 3-year survival (n = 1,796 patients), and four studies reported 5-year survival (n = 6,028 patients).

For 3-year survival, the risk ratio was 1.01 (95% CI: 0.96–1.06; p = 0.82), with heterogeneity of I² = 67%. For 5-year survival, the risk ratio was 1.01 (95% CI: 0.98–1.05; p = 0.38), also with heterogeneity of I² = 67%.

These findings are based on a limited number of studies. The authors also derived them using pooled risk ratios at fixed time points rather than time-to-event analyses, which may limit their robustness. The authors therefore advise that these survival estimates should be interpreted cautiously.

What These Findings Mean for Patients

For patients deciding between robot-assisted and conventional laparoscopic surgery for endometrial cancer, this review suggests that the two approaches are broadly comparable for most outcomes. The clearest advantages of robot-assisted surgery were less blood loss and a lower chance of needing to switch to open abdominal surgery during the operation.

The review found no significant differences between the two approaches for several important outcomes:

• Intraoperative visceral injuries (risk ratio 0.72; p = 0.20)
• Blood transfusion (risk ratio 0.73; p = 0.30)
• Total lymph nodes harvested (mean difference 0.98; p = 0.57)
• Length of hospital stay (mean difference −0.35 days; p = 0.07)
• Operative time (mean difference 11.49 minutes; p = 0.23)
• Recurrence (risk ratio 0.85; p = 0.39)
• 3-year survival (risk ratio 1.01; p = 0.82)
• 5-year survival (risk ratio 1.01; p = 0.38)

The authors note that robotic surgery has drawbacks, including longer operative times, higher costs, technical limitations of the robotic system, and the need for specialized staff and training. These factors may matter to patients and hospitals when choosing between approaches.

The paper's introduction cites a separate retrospective study in morbidly obese women with endometrial cancer, which found minimally invasive approaches, particularly robotic-assisted surgery, feasible and safe with acceptable perioperative outcomes; this was not a finding of the review's own analyses. This is relevant because obesity is a major driver of the rising incidence of endometrial cancer.

Limitations: What the Review Could Not Prove

The authors emphasize several limitations that affect how strongly the conclusions can be stated. The most important limitation is that most of the evidence comes from observational studies rather than randomized controlled trials. Only 2 of the 30 included studies were randomized controlled trials; the other 28 were observational.

Substantial heterogeneity was observed across several outcomes. For estimated blood loss, heterogeneity was 81%. For lymph node harvest, heterogeneity was 90%. For length of hospital stay, heterogeneity was 94%. For operative time, heterogeneity was 97%. Sensitivity and subgroup analyses did not fully explain this variability for several of these outcomes.

Survival data were limited. The 3-year and 5-year survival estimates were based on only four studies each. The authors also derived these estimates using pooled risk ratios at fixed time points rather than time-to-event analyses, which may limit their robustness.

The authors did not formally assess the certainty of evidence using GRADE. Therefore, conclusions regarding comparative effectiveness should be interpreted with caution.

Baseline oncologic characteristics, including disease stage, tumor grade, uterine weight, and adjuvant therapy, were inconsistently reported across studies. Several of these variables were not reported in a substantial proportion of studies, which limits adjustment for differences between patient groups.

Economic evaluations, such as cost-effectiveness, were outside the scope of this analysis. The review therefore does not answer questions about the relative value or affordability of the two approaches.

Given the predominance of observational evidence, persistent heterogeneity, and limited survival data, the authors state that these findings should be interpreted with caution. High-quality randomized trials are needed to better define the comparative effectiveness of these approaches.

Practical Recommendations

Based on this review, patients and clinicians can consider the following points when discussing surgical options for endometrial cancer:

1. The review found no significant differences in lymph nodes harvested, recurrence, or 3-year and 5-year survival between robot-assisted and conventional laparoscopic surgery, but the authors say these findings are based on few studies and the evidence for long-term cancer-control equivalence is limited. The review found no significant differences in lymph nodes harvested, recurrence, or 3-year and 5-year survival between robot-assisted and conventional laparoscopic surgery.
2. Weigh the blood loss and conversion advantages of robotic surgery. Robot-assisted surgery was associated with about 78 mL less blood loss and roughly one-third the risk of conversion to open surgery. The reduction in blood loss was similar in obese and nonobese patients, with no significant difference between these subgroups.
3. Ask about hospital and surgeon experience. Robotic surgery requires specialized staff and training. The paper says robotic surgery may offer a shorter learning curve, but the review did not test this, and hospital resources and surgeon familiarity vary.
4. Discuss costs and access. Robotic surgery has higher costs, and this review did not evaluate cost-effectiveness. Patients should ask how costs and insurance coverage may differ between the two approaches.
5. Recognize the limits of the evidence. Most evidence comes from observational studies with substantial heterogeneity. Patients should ask their care team how these findings apply to their individual case, including disease stage, tumor grade, body mass index, and other health conditions.
6. Ask about clinical trials. The authors call for high-quality randomized trials to better define the comparative effectiveness of these approaches. Patients interested in contributing to stronger evidence can ask whether relevant trials are available.

Frequently Asked Questions

What is the difference between robot-assisted and conventional laparoscopic surgery for endometrial cancer?

Both are minimally invasive operations to remove the uterus and both ovaries and fallopian tubes, and to sample lymph nodes for staging. In conventional laparoscopy the surgeon guides a camera and instruments directly. In robot-assisted surgery a robotic system translates the surgeon's hand movements, filtering out tremor. Both aim to stage the cancer with fewer complications than a large abdominal incision.

Which operation had less blood loss in the pooled analysis?

Across 20 studies involving 2,989 patients, robot-assisted surgery was linked to about 78 mL less estimated blood loss on average than conventional laparoscopy. The authors note high variation between studies and describe this as a trend rather than a definitive effect. Blood transfusion rates did not differ significantly between the two groups.

How likely is it that surgery switches to an open abdominal operation?

Across 17 studies of 2,791 patients, the chance of converting to open surgery during robot-assisted surgery was about one-third of the chance with conventional laparoscopy. This was one of the clearest differences between the approaches, and the studies agreed closely on it. Your own risk depends on your individual circumstances, which your care team can discuss.

Does robot-assisted surgery remove as many lymph nodes as conventional laparoscopy?

The number of lymph nodes removed and examined was similar between the two approaches across 12 studies of 1,980 patients. This matters because lymph node count is one indicator of surgical quality in cancer staging. Variation between studies was very high, so the authors describe this as a directional trend rather than a definitive effect.

Will survival or the chance of the cancer returning differ between the two operations?

The review found no significant difference in cancer recurrence, or in 3-year and 5-year overall survival, between robot-assisted and conventional laparoscopy. These survival estimates came from only four studies each and were calculated at fixed time points, so the authors advise interpreting them cautiously. Cancer control appeared broadly comparable with either approach.

How long is the hospital stay and operation with each approach?

Hospital stay was similar, about one-third of a day shorter on average with robot-assisted surgery, but this was not statistically significant. Operative time was about 11 minutes longer on average with robot-assisted surgery, also not statistically significant. Variation between studies was very high for both outcomes, so the authors describe these as directional trends.

What are the drawbacks of robot-assisted surgery and how strong is the evidence?

Robot-assisted surgery has drawbacks, including longer operative times, higher costs, technical limitations of the robotic system, and the need for specialized staff and training. Most evidence comes from 28 observational studies and only 2 randomized trials, with substantial variation between studies. The authors call for high-quality randomized trials and advise interpreting the findings with caution.

Should I get a second opinion before choosing robot-assisted or conventional laparoscopic surgery for endometrial cancer?

A second opinion can be useful when weighing these two minimally invasive approaches. The evidence shows they are broadly comparable for most outcomes, including lymph nodes harvested, recurrence, and 3-year and 5-year survival. Robot-assisted surgery was associated with about 78 mL less blood loss and roughly one-third the risk of conversion to open surgery, though most evidence comes from observational studies with substantial heterogeneity. A second opinion can help clarify how these trade-offs, along with surgeon and hospital experience and costs, apply to your stage, tumor grade, and body mass index. Diagnostic Detectives Network provides independent expert second opinions.

Source Information

Original article title: Robot-assisted versus conventional laparoscopic surgery for endometrial cancer: an updated systematic review and meta-analysis.

Authors: Majeed K, Ahmed M, Ali H, Kashif A, Murtaza M, Hanif ZM, Sidra F, Batool A, Onesime J, Akilimali A.

Publication details: BMC Surgery (2026) 26:475. DOI: https://doi.org/10.1186/s12893-026-03802-6. Open Access under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Review registration: PROSPERO CRD420251120306.

Note: This patient-friendly article is based on peer-reviewed research. It restructures the findings of one systematic review and meta-analysis for a general audience. It does not replace advice from a qualified healthcare professional. Patients should discuss their individual treatment options with their care team.