scieee Science in your language
[en] (orig)

Treatment and intention-to-treat propensity score analysis to evaluate the impact of video-assisted thoracic surgery on 90-day mortality after anatomical resection for lung cancer

Author: Recuero, José Luis,Royo, Iñigo,Gómez de Antonio, David,Call, Sergi,Aguinagalde Valiente, Borja,Gómez Hernández, María Teresa,Hernández Ferrández, Jorge,Sánchez Lorente, David,Sesma Romero, Julio,Rivo, Eduardo,Moreno Mata, Nicolás,Embún, Raúl
Publisher: Oxford University Press
Year: 2022
DOI: 10.1093/ejcts/ezac122
Source: https://addi.ehu.eus/bitstream/10810/75360/7/Treatment%20and%20intention%20accepts%20version.pdf
T ea men and in enon‐ o‐ ea p opensi y sco e analysis o e alua e he impac o ideo‐
assis ed ho acic su ge y on 90‐day mo ali y ae ana omical esecon o lung cance
Au ho s
JoseLuisRecue o‐Díaz¹†,IñigoRoyo‐C espo¹,Da idGómezde‐An onio²,Se giCall³,Bo ja
Aguinagalde⁴,Ma íaTe esaGómez‐He nández⁵,Jo geHe nández‐Fe ández⁶,Da idSánchez‐
Lo en e⁷,JulioSesma‐Rome o⁸,Edua doRi o⁹,NicolásMo eno‐Ma a¹⁰,andRaulEmbun¹,¹¹*†
onbehal o  heSpanishG oupo Video‐assis edTho acicSu ge y(GEVATS)
†Theseau ho scon ibu edequally o hiswo k.
Affiliaons
1. Depa men o Tho acicSu ge y,Hospi alUni e si a ioMiguelSe e ,Hospi alClínico
Uni e si a ioLozanoBlesa,IISA agón,Za agoza,Spain
2. Depa men o Tho acicSu ge y,Hospi alUni e si a ioPue adeHie oMajadahonda,
Mad id,Spain
3. Depa men o Tho acicSu ge y,Hospi alUni e si a iMú uaTe asa,Uni e si a de
Ba celona,Te asa,Ba celona,Spain
4. Depa men o Tho acicSu ge y,Hospi alUni e si a iodeDonosa,SanSebasán‐
Donosa,Spain
5. Depa men o Tho acicSu ge y,Hospi alUni e si a iodeSalamanca,IBSAL,
Uni e sidaddeSalamanca,Salamanca,Spain
6. Depa men o Tho acicSu ge y,Hospi alUni e si a ioSag a Co ,Ba celona,Spain
7. Depa men o Tho acicSu ge y,Hospi alClínicdeBa celona,Ins u oRespi a o io,
Uni e si yo Ba celona,Ba celona,Spain
8. Depa men o Tho acicSu ge y,Hospi alGene alUni e si a ioAlican e,Alican e,
Spain
9. Depa men o Tho acicSu ge y,Hospi alUni e si a ioSanagodeCompos ela,
SanagodeCompos ela,Spain
10. Depa men o Tho acicSu ge y,Hospi alRamónyCajal,Mad id,Spain
11. Depa men o Su ge y,Facul yo Medicine,Uni e si yo Za agoza,Za agoza,Spain
*Co esponding au ho
This is a p e-copyedi ed, au ho -p oduced e sion o an a icle accep ed o publica ion in Eu opean Jou nal o Ca dio ho acic
Su ge y ollowing pee e iew. The e sion o eco dJose Luis Recue o-Díaz, Iñigo Royo-C espo, Da id Gómez de-An onio, Se gi Call,
Bo ja Aguinagalde, Ma ía Te esa Gómez-He nández, Jo ge He nández-Fe ández, Da id Sánchez-Lo en e, Julio Sesma-Rome o,
Edua do Ri o, Nicolás Mo eno-Ma a, Raul Embun, on behal o he Spanish G oup o Video-assis ed Tho acic Su ge y (GEVATS),
T ea men and in en ion- o- ea p opensi y sco e analysis o e alua e he impac o ideo-assis ed ho acic su ge y on 90-day
mo ali y a e ana omical esec ion o lung cance , Eu opean Jou nal o Ca dio-Tho acic Su ge y, Volume 62, Issue 3, Sep embe
2022, ezac122 is a ailable online a : h ps://doi.o g/10.1093/ejc s/ezac122.
RaulEmbun
Depa men o Tho acicSu ge y
Hospi alUni e si a ioMiguelSe e 
PaseoIsabellaCa ólica1,Za agoza50009,Spain
Tel:+34‐635492179
Email: aulem[email p o ec ed]

Abs ac
OBJECTIVES:Theaimo  hiss udywas oknow he ea men effec o  ideo‐assis ed ho acic
su ge y(VATS)on90‐daymo ali yae ana omicallung eseconbasedonanaonwide
coho .
METHODS:Thisisamulcen ep ospec ecoho o 2721ana omical esecons o lung
cance  omDecembe 2016 oMa ch2018.T ea men andin enon‐ o‐ ea (ITT)analyses
we epe o medae in e sep obabili ysco eweighnganddiffe en p opensi ysco e
ma chingalgo i hms.Co a ia ebalancewasassessedbys anda dizedmeandiffe ences.The
esma o s epo edwe e hea e age ea men effec , hea e age ea men effec on he
ea edandodds aosae condionallogiscmodelswi h95%con idencein e als.The
uncon oundednessassumponwase alua edbysensi i yanalysis o a e age ea men 
effec (c‐dependence)anda e age ea men effec on he ea ed(Γ).
RESULTS:VATSwas heinialapp oachin1911paen s(70.2%), hough273cases(14.3%)had
obecon e ed o ho aco omy.Nine y‐daymo ali y a eswe e: ea men analysis(VATS
1.16% sopen3.9%,P<0.001),ITTanalysis(VATS1.78% sopen3.36%,P=0.012).Ae 
in e sep obabili ysco eweighngandp opensi ysco ema ching,in he ea men analysis,
VATSmean absolu e isk educonsbe ween2.25%and2.96%and ela e isk educons
be ween65%and70%(OR=0.34,95%con idencein e al0.15–0.79,allP‐ alues<0.004).
Howe e ,all heesma o s u nedou  obenon‐signi ican in heITTanalyses.Ahigh
sensi i y ounobse ablecon ounde swasp o ed(c‐dependence0.135,Γ=1.5).
CONCLUSIONS:VATScan educe he isko 90‐daymo ali yae ana omicallung esecon.
Howe e , heimplicaonso con e sion o ho aco omy,compa ingITT e sus ea men 
analysis,and hepo enalimpac o hiddenbiasshoulddese e u he aenonin he u u e.
Keywo ds:Video‐assis ed ho acicsu ge y,90‐Daymo ali y,In enon‐ o‐ ea analysis,
Tho acicsu ge y,Ana omicallung esecon,Lungcance 

Abb e iaons
ATE‐A e age ea men effec 
ATT‐A e age ea men effec on he ea ed
CIs‐Con idencein e als
GEVATS‐SpanishG oupo Video‐assis edTho acicSu ge y
ITT‐In enon‐ o‐ ea 
IPSW‐In e sep obabili ysco eweighng
PSM‐P opensi ysco ema ching
SMD‐S anda dizedmeandiffe ences
VATS‐Video‐assis ed ho acicsu ge y

In oducon
Al hough he ea emulple e ospec ese ies ha ha eshownalowe  a eo complicaons
andpos ope a es ayinpaen sope a edonby ideo‐assis ed ho acicsu ge y(VATS), he e
a emo edisc epancieson heimpac  ha  hesu gicalapp oachcouldha eonpos ope a e
mo ali y.In his ega d,a ecen  andomizedclinical ial,designed oe alua esho ‐ e mand
oncologicefficacyo VATS, ailed odemons a ediffe encesinpos ope a emo ali y
be weenVATSand ho aco omy[1].
Rega dingpos ope a emo ali y, ecen se iesha eshown ha 90‐daymo ali ycould
double30‐dayo in‐hospi almo ali yae lung esecon[2–4].Al houghmos se ies
compa ingVATSwi h ho aco omydono menon90‐daymo ali y,someimpo an s udies
ha eno shownsigni ican diffe encesinei he in‐hospi al,30‐dayo 90‐daymo ali y[5–7].A
ecen publicaon om heESTSda abasedidshowsigni ican diffe encesinmo ali ya 
discha ge(VATS1% s ho aco omy1.9%,P=0.020),no menoningmo ali ya 90days[8].
Fews udiesha epe o medanin enon‐ o‐ ea (ITT)analysiscompa ingVATSand
ho aco omy o lung esecon,ande enlessha ecompa ed he esul sob aineddepending
on hes a egyo analysispe o med[9,10].Howe e ,sinceanon‐negligiblep opo ono 
paen sunde goingVATSmus be inallycon e ed o ho aco omy,ITTanalysisseems obe
hemos app op ia es a egy oe alua e ea men effec s ela ed oVATSina ealscena io
[11].
In iewo  hecon licng esul sand heunde epo edITTanalysisin heli e a u e, he
objec eo ou s udywas ode e mine heimpac o  hesu gicalapp oachon90‐day
mo ali y,compa ing ea men andITTanalysisinpaen swhounde wen andana omical
lung esecon o lungcance in henaonalcoho by heSpanishG oupo Video‐assis ed
Tho acicSu ge y(GEVATS)[12].

Ma e ials and Me hods
E hical s a emen
Thisp ojec wasapp o edbyall helocale hicscommieesandin o medconsen was
ob ained om he ec ui edpaen s ouse hei clinicalda a o scien icpu poses(App o al
byE hicsCommieeo A agonHeal hResea chIns u eon20May2015PI15/0072).
Da a sou ce
TheGEVATSo  heSpanishSocie yo Tho acicSu ge yisap ospec e olun a ymulcen e
obse aonals udywi ha o alo 33Tho acicSu ge yDepa men pa cipang.TheCen es
we eno selec edbasedon hei expe ienceinVATSo anyo he c i e ion.Thecoho 
includedpaen swhounde wen anana omicallung esecon om20Decembe 2016 o20
Ma ch2018.TheGEVATSobjec eswe e oknow heimpac o su gicalapp oachonsho ‐
andlong‐ e mou comes.Theme hodo  heGEVATS,includingsamplesizejus icaonand
heaudi p ocesspe o med,was ecen lypublished[12].
Paen allocaonin oVATSo  ho aco omydependedonclinicalp acce,expe ienceand
belie so eacho  hepa cipangsu geonsanddepa men s.
In hisp ospec eobse aonalcoho s udy,we ied ospeci icallyelucida e heimpac o 
hesu gicalapp oachon90‐daymo ali yae ana omicallung esecon o lungcance .Fo 
hispu pose, hosepaen swi hadiagnosiso he  hanlungca cinomaand hosewho
unde wen pneumonec omyo ex endedlung eseconwe eexcluded.Ex ended esecon
wasconside edincaseo ches wall,diaph agmo slee e esecon.Ou manusc ip is
epo edacco ding o heSTROBE ecommendaonsandESTSS ascalP ime  o p opensi y
sco eanalysis.
S ascal analysis
Adouble ypeo analysiswasca iedou , ea men andITT,dependingon heneedo 
con e sion omVATS oopen h oughou  hep ocedu e.Theassociaono  hesu gical
app oach(open e susVATS)as he ea men  a iable,wi hbaselineoncologicandsu gical
a iables ha couldin luenceon heou come a iable(90‐daymo ali y)and heapp oach o
bechosen,wasanalysedby wo‐ aileds ascalhypo hesis esng,usingMann–Whi neyand
Chi‐squa e es sands anda dizedmeandiffe ences(SMD).Those a iableswi haP‐ alueo 
less han0.2and/o s anda dizeddiffe encesg ea e  han0.1we e heco a ia esused o
build hep opensi ysco e oco ec  o seleconbias.
Missingda awe edeal bycasewisedeleonanalysiswhenless han5%o paen shad
incomple e egis ies.
Thep opensi ysco ewasesma edbyalogi modeland heo e lapassumponwasassessed
ondensi yplo s o  ea men andITTanalysis.The ea men effec swe ee alua edbasedon
hein e sep obabili ysco eweighng(IPSW)and hep opensi ysco ema ching(PSM)
h ough henea es ‐neighbo me hodwi handwi hou  eplacemen ,usingdiffe en callipe 
wid hs(0.035,0.05and0.1)andma ching aos(1:1,1:2and1:3).
Co a ia ebalancedwasassessedbySMD,be o eandae weighngo ma ching.SMDless
han0.1o 0.05we econside edgoodo excellen , espec ely, oexclude esidualimbalance
[14].Balanceo co a ia eswasdisplayedondo plo s o IPSWandPSM,sepa a ely.
The ea men effec swe eesma edbyweigh edmeanandma chingou comemodels
epo ng hea e age ea men effec (ATE),basedon hediffe enceinpo enalou come
means,and hea e age ea men effec on he ea ed(ATT).ATEandATTwe e epo edas
absolu e isk educons(IPSWandPSM)and ela e isk educons(IPSW).Inaddion,in
caseo PSM1:1wi hou  eplacemen andcallipe 0.035,acondionallogisc ixed‐effec s
eg essionmodelwasconduc ed.In hiscase, ea men effec swe e epo edasodds aos.
Theimpac o su geonexpe ienceinVATSp ocedu es(≤50 e sus>50cases),su geonsenio i y
( esiden  e sus acul y<10yea s e sus acul y10–20yea s e sus acul y>20yea s),su gical
olumeandVATS a ebydepa men (disc e e a iables)we eused oadjus  heodds aos
epo edby hecondionallogiscmodelsp e iouslydesc ibed.Tocompu esu gical olume
andVATS a ebyins uon h oughou  he15‐mon h ec ui men pe iod,weconside ed he
epo ssubmiedby heHeadso  heAdminis a eDepa men s omeachIns uon.
These epo swe eusedin heaudi p ocesswep e iouslypublished[12].95%con idence
in e als(CIs)we ecalcula ed om obus s anda de o sandP‐ aluesless han0.05we e
conside eds ascallysigni ican .
Thecondionalpa aldependenceme hodp oposedbyMas ene al.wasused oe alua e
hesensi i yo conclusionsabou  heATE.Boundson heATEgi enase o c‐dependence
alues(be ween0and1)and heb eakdownpoin (maximum alueo  hec‐dependence
pa ame e unde which heconclusionsllholds)we e epo ed.Inaddion, heimpac o 
hiddenbiason heATTesma o ae PSM(1:1,callipe 0.035,no eplacemen )wasassessed
wi h heboundingapp oachp oposedbyRosenbaum.TheΓpa ame e andco espondingP‐
alueswe eused omeasu e hesensi i yo ATT ounobse ablecon ounde s.
TheT ea men Effec sSui einS a a/MP16.0and heS a apackagesS ddiff,Psma ch2,
Calipma ch,Tesensi i yandMhboundswe eused o  hes ascalanalysis.TablauDesk op
2020.3.1wasused o plo  ep esen aono  heco a ia ebalance.

Resul s
A o alo 3533paen swe e ec ui ed,including1917VATScases(54.3%).Ae exclusiono 
paen swi hadiagnosisdiffe en  olungcance (448paen s,12.7%),pneumonec omy(236
paen s,6.7%)andex ended esecon(165,4.7%),2721paen s(77%o  heen eGEVATS
coho )me  heinclusionc i e ia.The ypeso  eseconsincludedwe e:2444lobec omies
(90%),111bilobec omies(4%)and166ana omicalsegmen ec omies(6%).
VATSwas heinialapp oachin1911paen s(70.2%), ep esenng he ea men g oupin
heITTanalysis.Howe e ,273cases(14.3%)had obecon e ed o ho aco omyand,
he e o e, heVATSa min he ea men analysisconsis edo 1638paen s(60.2%).The
unadjus edanalysisshowedanimpo an associaonbe weenin‐hospi almo ali yand90‐day
mo ali ywi h hesu gicalapp oachpe o med(Table1).Theou come a iable(90‐day
mo ali y)wasmissingin11cases(0.4%) ha we eno conside edin heanalysiso  ea men 
effec s.Thepe cen ageso missing alueswe enegligible o all hecon ounde sexcep  o 
DLCO.ThemainanalysisexcludedDLCOascon ounde ,so14 a iableswe eused obuild he
p opensi ysco einacomple e‐caseanalysissinceonly1.8%o  hepaen shadmissing alues
insomeo  heco a ia esincluded(Table2).Thep opensi ysco edis ibuon op o e he
o e lapassumponisshowninadensi yplo (Figu e1).Only9paen sin heVATSg oup
(0.6%)hadap opensi ysco ehighe  han hemaximump opensi ysco e aluein heopen
g oup,whileonly2paen sin heopeng oup(0.2%)hadap opensi ysco elowe  han he
minimum aluein heVATSg oup.
Ae IPSW, he aoso VATS o ho aco omywe e1339:1324paen sin he ea men 
analysisand1347:1317paen sin heITTanalysis.Co a ia ebalancewasp o ed(Figu e2).
PSM1:1wi hou  eplacemen andacallipe wid ho 0.035yielded872ma chedpai sin he
ea men analysisand705ma chedpai sin heITTanalysis.Mos o  heco a ia es eached
anexcellen balanceae ma ching(Table3).Thep opo onso casesma ched o1con ol
we e54.2%( ea men analysis)and37.6%(ITTanalysis).
Ae PSMwi h eplacemen ,2664paen s(1608VATSand1056open)in he ea men 
analysisand2663paen s(1877VATSand786open)in heITTanalysiswe ema ched o1,2
o 3coun e pa s.Independen lyo  hema ching aosandcallipe wid hs,mos o  he
co a ia es eachedanexcellen balance(Figu e3).
Basedon he ea men analysis,VATSwasconsis en lyassocia ed oalowe 90‐daymo ali y
a eacco ding o heATEandATTesma o s,wha e e  hep opensi ysco e echniqueo 

algo i hmused.Howe e ,in hecaseo ITTanalysis, heslllowe mo ali yae VATSwas
associa ed onon‐signi ican ATEandATT,in e mso absolu eand ela e isk educons,in
all hecases(Table4).
In hecondionallogiscmodelae PSM1:1(no eplacemen andcallipe wid h0.035), he
esul sob ainedae  ea men analysis(OR=0.38;95%CI0.20–0.73;P=0.004)andITT
analysis(OR=0.71;95%CI0.38–1.33;P=0.283)we econsis en wi h heATEandATT
esma o s.Ae adjusng he ixed‐effec modelsbysu geonexpe ience(numbe o VATS
p ocedu esandsenio i y)anddepa men expe ience(su gical olumeandVATS a e) heodds
aoswe esimila  o hosein henon‐adjus edma ched ea men analysis(OR=0.34;95%CI
0.15–0.79;P=0.012)andlowe , houghsllnon‐signi ican ,in heITTanalysis(OR=0.41;95%
CI0.13–1.25;P=0.117).
In hesensi i yanalysis, heclose oze oc‐dependence aluesunde which heconclusions
sllheld( ea men analysis0.135andITTanalysis0.09)mean ahighsensi i yo  heATE
esma o  ohiddenbias(Figu e4).Inaddion, hemaximumΓ aluea whichsigni ican P‐
alueswe eob ained(Γ=1.5)showed ha  heATTesmaono  hiss udyissensi e obias
(unobse ed a iables)able oinc ease heoddso  ecei ingVATSinmo e han50%.
In hemainanalysis,wedidno conside DLCObecauseo  hehigh a eo missing alues
(15.2%).Howe e ,inaseconda yanalysisincludingDLCOasaco a ia e obuild hep opensi y
sco e, heATEandATTesma o sae IPSWwe eequi alen  o hoseob ainedin hemain
analysis.Mo eo e , hesensi i yanalysisshowedane enhighe po enalimpac o 
unmeasu edo unobse ablecon ounde s(Γ=1.15).

Discussion
Ou main indingwas ha VATScan educe90‐daymo ali yae anana omicallung esecon
o lungcance .Howe e , hisbene icialeffec dec easedand u nedou  obenon‐signi ican 
whenanITTanalysiswaspe o med.No ewo hy, hese indingswe econsis en alongall he
p opensi ysco ealgo i hmsca iedou .Finally, hehighsensi i yo ou analysis ohidden
biashighligh s ha  hepo enalimpac o unmeasu edandunobse ablecon ounde sin
obse aonals udiescompa ingVATSandopensu ge ycouldbede e minan .
The esul so  he ews udiescompa ing heimpac o  hesu gicalapp oachon90‐day
mo ali ylead ocon adic o yconclusions.Limi eds ascalpowe seconda y osmall
samplesizesandsu p isinglylowmo ali y a escouldpa lyexplainnon‐conclusi e indings
[1,6,7].Howe e ,whenanalysing he esul sob ainedbyla geins uonalcoho s,signi ican 
s ascaldiffe encescouldonlyco espond oclinically i ial ea men effec [15].
In he ho acicsu ge yli e a u e,use ul ecommendaonsha ebeenmade oimp o e
epo ngbasedon hep opensi ysco eanalysis,since hisanalycapp oachisno as
s aigho wa das eg essionanalysis[16].Conside ing he ecommendaonsby heEu opean
Socie yo Tho acicSu geonsini ss ascalp ime  epo ,weca iedou  he2ad ised
me hods,IPSWandPSMwi hcallipe [13].Inaddion, oassess heconsis encyo ou  esul s,
wepu in op accediffe en ma chingalgo i hms( ea ed ocon ol aos,callipe wid hs
and eplacemen  e susno eplacemen ma ching).
Theuseo 2p opensi ysco es echniquescompa ingou comesae VATSo openlung
eseconisanexcepon[10].Pagèse al.published he esul sbyaF enchnaonwides udy
e aluang heimpac o su gicalapp oachonsho ‐andlong‐ e mou comesae lobec omy
o lungcance .In hisla gecoho (n=24,811) ec ui ed h oughou an8‐yea pe iod,only
4.9%o  hecaseswe eope a edonbyVATS.I isno ewo hy ha  hesigni icancele el
ob ainedina ewou comesdiffe edbe ween hep opensi ysco es a egiesused(IPSW
e susPSM).Howe e , ega ding30‐daymo ali y,bo hIPSWandPSM ailed odemons a ea
signi ican  educonae VATS(PSMOR=0.89,95%CI0.45–1.81;IPSWOR=0.74,95%CI
0.37–1.45).
Theimpo anceo anITTs a egywhene aluang heimpac o  hesu gicalapp oachwas
highligh edinoneo  he i s me a‐analysespublishedcompa ingVATSand ho aco omy[17].
Howe e , hein o maonabou con e sion omVATS oopensu ge yisno always egis e ed,
e enincaseo naonalandin e naonal egis ies[6,8,10,18,19].Consequen ly,ITTanalysis
isno awidep accein he ho acicsu ge yli e a u eand, he e o e, hebene i con e ed o
VATSwhene aluang ea men effec scouldbemisleading.In ac , hehighe  he a eo 
con e sion omVATS oopen hehighe  hepo enaldisc epancybe ween ea men andITT
analyses.In his ega d,despi eahighe  a eo VATSinou coho (60.2%) han heone
epo edbymanynaonwideandmulcen e egis ies, hep opo ono con e sionwea e
epo ng(14.3%)isno ablysupe io compa ed osome ecognizedse ies anging om2% o
9%[11,20,21].Risko con e sionina ecen me analysiswas9.6%(95%CI:6.6–13.9%)[22].
Wecanno concludeabou  he easons o ou highe con e sion a e.Howe e ,naonwide
ep esen a eness,da aaudi  ha in ol edall hepa cipangcen es,o jus amae o 
disposiono su geons,mo ep one os a ng hep ocedu ebyVATSinou coun y,couldbe
someo  hehypo heses.Inaddion,al houghanyonecouldexpec  ha highe VATS a esa e
pa allel olowe con e sion a esbecauseo expe ienceacquision, his easoningcouldbe
con licngdependingon hescena ioand he ypeo coho inqueson, o examplesingle
cen e e susmulcen e.In his ega d,ou  ela elyhighcon e sion a ecouldsimply
ep esen aconsequenceo ou di ec lyp opo onalhighVATS a e.
Al houghsomes udiesa gue ha con e sion omVATS oopendoesno en ailasu gical
ailu e,o he se iesha eassocia edcon e sion owo seou comesin e mso pos ope a e
mo bidi y[20,23].Ou s udywouldsuppo ade imen aleffec associa ed ocon e sion.
Howe e ,mo ede ailedandspeci icanalysescompa ingcon e edVATS os aigh 
ho aco omycouldgene a einsighulknowledgeabou  heimplicaonso con e sioni sel 
and hemos app op ia edisposion owa dss a ng hep ocedu ebyVATS.
ITTanalysisisclaimedas hegolds anda din andomizedcon ol ials o e lec ap agmac
clinicalscena io, omain ainp ognoscbalancegene a ed om heo iginal andomizaonand
ogi eanunbiasedesma eo  ea men effec .Howe e ,weconside edimpo an a  his
s agewhenmos o  hes udiesdealingwi hVATSa esll epo ng hei  esul sbasedona
ea men analysis, oinclude hislessconse a es a egyo analysisso ha wecouldsll
compa eou  indingswi h hecoe aneousli e a u e.Toou knowledge, hisis he i s 
manusc ip  ha e alua e heimpac o  hesu gicalapp oachonsho ‐ e mmo ali yae 
lung esecon,compa inga ea men andITTanalysis.
Limi aons
Themaind awbackinmulcen e olun a y egis iesis ela ed oseleconbiasandda a
quali y.Al hough hede ailso ou audi we ep e iously epo ed,wecanno  ejec  esidual
biasa  hiss age[12].
Asp e iouslypublished, ocalcula eou samplesize,weconside ed2%absolu e isk
diffe encein90‐daymo ali yas ele an inp acce(4% s2%),andanexpec ed25%o cases
byVATS[12].Becauseo  heunde esma ed90‐daymo ali y a ediffe encebe weenVATS
andOpen(1.16% s3.9%)and hehighe ‐ han‐expec edVATS a e(60%), hes ascalpowe 
o ou 'posi e'conclusionin he ea men analysis(99%)ishighe  han hecon enonal
80%.Howe e ,in heITTanalysis, helowe diffe enceinmo ali ybe weenbo happ oaches
(1.78% s3.36%)and helowe p opo ono con olpaen s(29%)couldbe he easons o a
limi edpowe (69%)o ou 'nega e' esul s.
Missing aluesa eano he co ne s oneinobse aonals udies.Al houghDLCOwas heonly
co a ia ewi hamissing a eo highe  han2%(415/2721paen s15%), his espi a o y
pa ame e hasbeenp o edasoneo  hemos de e minan  isk ac o sae lung esecon,
e eninou owncoho [24–26].Despi eequi alen  esul sinapos hocanalysisbasedon he
subg oupo paen swi h his aluep esen ,con oundingbiascanno beexcluded.
Despi e henaonal ep esen a enesso  heGEVATScoho ,sincei wouldha eincluded
50%o  heana omicallung eseconspe o medinSpaino e  he15‐mon h ec ui men 
pe iod, hehighaudi ed a eo VATS egis e ed(60%)couldcomp omise heexpo aono 
ou  esul s oo he naonalo localscena ioswi hanimpo an disc epancyinVATS
implemen aon[12].Howe e , heequipoiseinou s udyin e mso  hep opo ono 
paen sineachg oupcompa ed oo he se iesmakesi lesslikely ha ei he ou openg oup
ep esen sas onglyselec edcollecono challengingcaseso ou VATSg oupas ongly
selec edcollecono  a ou ablecases[6,10,27].
PSMisconside ed ojeopa dize hegene alizaono i sconclusionswhenma chedsample
sizeislowe  han50%o  heo iginalsample.Inou s udybyca yingou PSM1:1wi hou 
eplacemen andcallipe wid h0.035, hep opo ono ma chedsamplewas64%and52%
ae  ea men andITTanalysis, espec ely.Ne e heless, he esul sob ainedae such
PSMalgo i hmswe eequi alen  o hose eachedae makinguseo all hesamplewi h
o he p opensi ysco e echniques,whichseems op ese eou conclusiona amo egene al
seng.
Finally,hiddenbiasisaubiqui ousp oblemine e yobse aonals udy,e enincaseo a
igo ousp opensi ysco eanalysis,andsensi i y es  ies oge abee unde s andingo  his
obs acle oob ain eliableesma o s.Howe e , his ypeo analysisisexceponalin ho acic
su ge y[10].Thes udypublishedbyPagèse al. om heEpi ho da abase epo edahigh
sensi i y ounobse ablecon ounde swhenesmangpos ope a edea h(Γ=1.6).Ou 
esul swe e e ysimila (Γ=1.5),e enae includingDLCOasaco a ia ein hep opensi y
sco eanalysis(Γ=1.2, heclose  o1 hemo esensi eou esmaons ohiddenbias).
Consequen ly, he eliabili yo ou esmaonsshouldbecauouslyadmiedunlmo e
obus e idence.

Conclusion
Ha inginmind heexclusionc i e iap e iously e e ed(pneumonec omyandex ended
esecon),VATSwasconsis en lyshown o educe90‐daymo ali yby65–70%ae an
ana omicallung esecon o lungcance in heGEVATScoho .Howe e ,d awnon heITT
analysisincludingpaen scon e ed oopensu ge yin o heVATSg oup, hisbene i 
dec eased o heex en o ob ainings ascallynon‐signi ican , houghpo enally
unde powe ed,diffe ences.Unlupcominge idencecompa ingcon e edVATS os aigh 
ho aco omy,aneffo shouldbemade oopmize hebene icialeffec o VATSonsho ‐ e m
mo ali yae anana omical esecon o lungcance .In heanalysiso hiddenbias,we
demons a ed ha  he ea men effec esma o swe ehighlysensi e ounobse able
con ounde s,whichcouldonlybeo e comeinasufficien lyla gemulcen e andomized ial.

Acknowledgemen s
We hankall helocal esea che swhocon ibu edwi hpaen  ec ui men andda aen y.
Coo dina o :RaulEmbun(Uni e si yHospi alMiguelSe e ).
Scien ic commiee:Da idGómezdeAn onio(Uni e si yHospi alPue adeHie o
Majadahonda,Mad id);Se giCall(Mú uaTe asaUni e si yHospi al,Uni e si yo Ba celona,
Te asa,Ba celona);NicolásMo eno‐Ma a(RamónyCajalUni e si yHospi al,Mad id);
Ma celoF.Jiménez(SalamancaUni e si yHospi al,Uni e si yo Salamanca,IBSAL,
Salamanca);MiguelCong egado(Vi genMaca enaUni e si yHospi al,Se ille);andSe gio
Bolu e ‐Nadal(Gene alUni e si yHospi alo Alican e).
Local esea che s:JoseLuisRecue oandIñigoRoyoC espo(Uni e si yHospi alMiguelSe e 
andLozanoBlesa);Bo jaAguinagaldeandIke LópezSanz(DonosaUni e si yHospi al,San
Sebasán‐Donosa);Se gioAmo ‐AlonsoandF anciscoJa ie Mo adiellos‐Díez(Qui onsalud
Mad idUni e si yHospi al,Mad id);MiguelJesúsA a ás(ValencianOncologyIns u e
Foundaon,Valencia);AnaIsabelBlancoO ozco(Uni e si yHospi alVi gendelRocío,Se illa);
Ma cBoadaandDa idSánchez(Hospi alClinico Ba celona,Respi a o yIns u e,Uni e si yo 
Ba celona,Ba celona);Albe oCabañe oSánchez(RamónyCajalUni e si yHospi al,Mad id);
IsabelCalVázquezandRamónMo eno‐Balsalob e(Uni e si yHospi alLaP incesa,Mad id);
ÁngelCille ueloRamos(Uni e si yClinicalHospi al,Valladolid);Sil anaC owleyCa asco
(Uni e si yHospi alPue adeHie oMajadahonda,Mad id);ElenaFe nández‐Ma nand
Flo ennoHe nandoT ancho(Hospi alClínicoSanCa los,Mad id);SanagoGa cía‐Ba ajasand
Cip ianoLópezGa cía(Uni e si yHospi alo Badajoz,Badajoz);Ma iaDolo esGa cía‐Jiménez
(Uni e si yHospi alo Albace e,Albace e);JoseMa íaGa cía‐P imandEdua doRi o(Sanago
deCompos elaUni e si yHospi al,SanagodeCompos ela);JoseAlbe oGa cia‐Salcedo(12
deOc ub eUni e si yHospi al,Mad id);JuanJoséGelbenzu‐ZazpeandMa íaElenaRamí ez‐
Gil(ComplejoHospi ala ioo Na a e,Pamplona);Ca losFe nandoGi aldo‐OspinaandRobe o
MongilPoce(Hospi alRegionalUni e si a io,Málaga);Ma íaTe esaGómezHe nández
(SalamancaUni e si yHospi al,Uni e si yo Salamanca,IBSAL,Salamanca);Jo geHenández
andJuanJoséFiblaAl a a(Sag a Co Uni e si yHospi al,Ba celona);Jenni e D.IllanaWol 
(Pue adelMa Hospi al,Cádiz);Albe oJau eguiAbula ach(Valld'Heb onUni e si yHospi al,
Ba celona);UnaiJiménezandRa aelRojo‐Ma cos(Uni e si yHospi alC uces,Bilbao);Nés o J.
Ma nez‐He nández(LaRibe aUni e si yHospi al,Alci a,Valencia);Elisabe hMa nez‐Téllez
andJuanCa losT ujilloReyes(San aC euandSan PauHospi al,Au onomousUni e si yo 
Ba celona,Ba celona);LucíaMillaCollado(Hospi alA naudeVilano a,Lleida);Se gioB.
Mo enoMe ino(Vi genMaca enaUni e si yHospi al,Se ille);Ca meObiols(Mú uaTe asa
Uni e si yHospi al,Uni e si yo Ba celona,Te asa,Ba celona);Flo encioQue o‐Valenzuela
(Vi gendelasNie esHospi al,G anada);Rica dRamos‐Izquie do(Uni e si yHospi alo 
Bell i ge,Hospi ale deLlob ega ,Ba celona);Albe oRod íguez‐Fus e (Hospi aldelMa ,
Hospi aldelMa MedicalResea chIns u e,Ba celona);Lau aSanchezMo eno(Uni e si y
11. DecaluweH,Pe e senRH,HansenH,PiwkowskiC,AugusnF,B unelliAe al.;ESTS
MinimallyIn asi eTho acicSu ge yIn e es G oup(MITIG).Majo in aope a e
complicaonsdu ing ideo‐assis ed ho acoscopicana omicallung esecons:an
in enon‐ o‐ ea analysis.Eu JCa dio ho acSu g2015;48:588–99.
12. EmbunR,Royo‐C espoI,Recue oDíazJL,Bolu e S,CallS,Cong egadoMe al.Spanish
Video‐Assis edTho acicSu ge yG oup:me hod,auding,andinial esul s oma
naonalp ospec ecoho o paen s ecei ingana omicallung esecons.A ch
B onconeumol2020;56:718–24.
13. BenedeoU,HeadSJ,AngeliniGD,Blacks oneEH.S ascalp ime :p opensi ysco e
ma chingandi sal e na es.Eu JCa dio ho acSu g2018;53:1112–7.
14. AusnPC.Balancediagnoscs o compa ing hedis ibuono baselineco a ia es
be ween ea men g oupsinp opensi y‐sco ema chedsamples.S a Med2009
10;28:3083–107.
15. Abdelsaa ZM,AllenMS,ShenKR,Cassi iSD,NicholsFC,WigleDAe al.Va iaonin
hospi aladopon a eso  ideo‐assis ed ho acoscopiclobec omy o lungcance and
heeffec onou comes.AnnTho acSu g2017;103:454–60.
16. AusnPC.P opensi y‐sco ema chingin heca dio ascula su ge yli e a u e om
2004 o2006:asys emac e iewandsuggesons o imp o emen .JTho ac
Ca dio ascSu g2007;134:1128–35.
17. YanTD,BlackD,BannonPG,McCaughanBC.Sys emac e iewandme a‐analysiso 
andomizedandnon andomized ialsonsa e yandefficacyo  ideo‐assis ed ho acic
su ge ylobec omy o ea ly‐s agenon‐small‐celllungcance .JClinOncol
2009;27:2553–62.
18. Pu iV,Gaisse HA,Wo mu hDW,G oganEL,Bu eindWR,ChangACe al.Tho acic
su geonspa cipan spe o ming ho acoscopiclobec omy.AnnTho acSu g
2019;107:202–8.
19. PaulS,Al o kiNK,ShengS,LeePC,Ha poleDH,OnaisMWe al.Tho acoscopic
lobec omyisassocia edwi hlowe mo bidi y hanopenlobec omy:ap opensi y‐
ma chedanalysis om heSTSda abase.JTho acCa dio ascSu g2010;139:366–78.
20. BongiolaS,Gon ioA,ViggianoD,Bo gianniS,PoliL,C isciRe al.;I alianVATS
G oup.Risk ac o sandimpac o con e sion omVATS oopenlobec omy:analysis
omanaonalda abase.Su gEndosc20191;33:3953–62.
21. Lau senLØ,Pe e senRH,HansenHJ,JensenTK,Ra nJ,KongeL.Video‐assis ed
ho acoscopicsu ge ylobec omy o lungcance isassocia edwi halowe 30‐day
mo bidi ycompa edwi hlobec omyby ho aco omy.Eu JCa dio ho acSu g
2016;49:870–5.
22. Powe AD,Me iRE,Abdel‐RasoulM,Moffa‐B uceSD,D'SouzaDM,Kneue zPJ.
Esmang he isko con e sion om ideo‐assis ed ho acoscopiclungsu ge y o
ho aco omy—asys emac e iewandme a‐analysis.JTho acDis2021;13:812–23.

23. Fou d ainA,DeDominicisF,IquilleJ,La ieS,Me luscaG,Wie‐P is e Ae al.
In aope a econ e siondu ing ideo‐assis ed ho acoscopydoesno cons u ea
ea men  ailu e.Eu JCa dio ho acSu g2019;55:660–5.
24. B unelliA,DineshP,Woodcock‐ShawJ,LilechildD,PompiliC.Nine y‐daymo ali y
ae  ideo‐assis ed ho acoscopiclobec omy:incidenceand isk ac o s.AnnTho ac
Su g2017;104:1020–6.
25. GómezdeAn onioD,C owleyCa ascoS,Rome oRománA,RoyuelaA,SánchezCalle
Á,ObiolsFo nellCe al.Su gical isk ollowingana omiclung eseconin ho acic
su ge y:ap ediconmodelde i ed omaSpanishMulcen e Da abase.A ch
B onconeumol2021Feb24:S0300‐2896(21)00070‐3.
26. AguinagaldeB,InsausA,LopezI,SanchezL,Bolu e S,EmbunR.VATSlobec omy
mo bidi yandmo ali yislowe inpaen swi h hesameppoDLCO:analysiso  he
da abaseo  heSpanishVideo‐Assis edTho acicSu ge yG oup.A chB onconeumol
2021;57:750–6.
27. XuJ,NiH,WuY,CaoJ,HanX,LiuLe al.Pe iope a ecompa isono  ideo‐assis ed
ho acicsu ge yandopenlobec omy o pT1‐s agenon‐smallcelllungcance paen s
inChina:amul‐cen e p opensi ysco e‐ma chedanalysis.T anslLungCance Res
2021;10:402–14.
No e:Thisis heau ho 'saccep edmanusc ip  e sion.The inalpublisheda clemaycon ain
addionaledi sand o mangchangesmadedu ing hep oduconp ocess.Pleaseci e he
published e sionwhen e e encing hiswo k.
Figu e_1
Figu e_2
Figu e_3
Figu e_4