Evaluating cancer screening programmes using survival analysis

Presejalni programi za odkrivanje raka omogočajo, da z rednimi presejalnimi testi odkrijemo raka pri na videz zdravih posameznikih v zgodnejši fazi bolezni, ko je zdravljenje bolj učinkovito. Evalvacija presejalnih programov je pomembna za laično javnost, saj pomaga pri razumevanju prednosti in slabosti presejanja, in za odločevalce, ki morajo zagotoviti, da so sredstva v zdravstvu optimalno porabljena. V doktorski nalogi smo uspešnost presejalnih programov ovrednotili z analizo preživetja. Dosedanje raziskave na tem področju so poskušale oceniti učinkovitost zgodnjega zdravljenja tako, da so primerjale preživetje bolnikov, pri katerih smo odkrili raka na presejalnem testu (presejalno odkriti raki), s preživetjem bolnikov, pri katerih smo raka odkrili na podlagi simptomov, ki so se pojavili v intervalu med zadnjim in naslednjim presejalnim testom (intervalni raki). Gre za preprosto, a pristrano primerjavo, ki jo poimenujemo "naivna primerjava". Dosedanje raziskave so poskušale pristranost pri naivni primerjavi zmanjšati s pomočjo statističnih modelov, vendar so bile pri tem zgolj deloma uspešne. Trenutni pristopi, ki temeljijo na analizi preživetja, zato niso primerni za vrednotenje uspešnosti presejalnih programov. V doktorski nalogi smo v primerjavi z dosedanjo literaturo ubrali drugačen pristop. Da bi lahko natančno definirali primerjavo, ki nas zanima, in upoštevali vso kompleksnost problema, smo razvili novo, celovito notacijo. Ta temelji na notaciji potencialnih izidov in nam omogoča, da lahko potencialno izkušnjo iste osebe opišemo v dveh svetovih: v svetu 0 in svetu 1. V svetu 0 oseba ni povabljena v presejalni program, v svetu 1 pa je. Izid, ki nas zanima, je čas preživetja, definiran kot čas od diagnoze do smrti. Tako čas diagnoze kot čas smrti sta lahko različna v svetu 0 in svetu 1, kar pomeni, da ima oseba lahko različno preživetje glede na to, v katerem svetu jo opazujemo. Če želimo oceniti uspešnost presejalnih programov, moramo primerjati preživetje istih pacientov v svetu 1 (kjer so lahko zdravljeni predčasno), z njihovim preživetjem v svetu 0 (kjer so zdravljeni ob nastopu simptomov). Osredotočili smo se na podskupino presejalno odkritih pacientov, saj zgolj te paciente zdravimo predčasno v svetu 1 in se na ta način izognili pristranosti zaradi dolžine časa. Pomembno je tudi, da v obeh svetovih začnemo meriti čas do smrti ob istem datumu (imenovan čas nič), saj na ta način zagotovimo, da je primerjava resnično nepristrana. V našem primeru smo čas nič nastavili na datum diagnoze v svetu 0. V doktorski nalogi smo formalno definirali nepristrano primerjavo in pokazali, kako se razlikuje od naivne. Dokazali smo tudi, da so različni viri pristranosti, ki se pojavijo pri naivni primerjavi, med seboj aditivni. V praksi želimo uspešnost presejalnih programov oceniti na podlagi empiričnih podatkov. Preživetje presejalno odkritih pacientov, ki so zdravljeni predčasno, lahko ocenimo neposredno iz podatkov. Če želimo pri oceni preživetja prestaviti čas nič na datum, ko bi pacientom diagnosticirali raka na podlagi simptomov, lahko v ta namen uporabimo obstoječe parametrične metode, ki ocenjujejo pretečeni čas med diagnozo na podlagi presejalnega testa in diagnozo na podlagi simptomov (imenovan čas prednosti). Izziv, ki še ni bil rešen, pa je oceniti, kako bi presejalno odkriti pacienti živeli, če bi z zdravljenjem pričeli kasneje, ob simptomih - v praksi namreč vse paciente začnemo zdraviti takoj, ko postavimo diagnozo raka. V doktorski nalogi smo zato v ta namen razvili novo metodo. Predlagana metoda zahteva podatke za dve skupini oseb - za tiste, ki so vključeni v program in za tiste, ki niso. Najprej predpostavimo, da sta obe skupini randomizirani. Ideja metode je naslednja: bolnike, ki niso bili vabljeni v program, lahko razdelimo glede na tiste, ki bi v primeru vabila bili odkriti na presejanju in tiste, ki bi bili odkriti ob simptomih. Ne moremo sicer vedeti, kaj bi se zgodilo z vsakim posameznim bolnikom, lahko pa ocenimo delež vsake podskupine na podlagi podatkov skupine, ki je bila vabljena v presejalni program. Preživetje bolnikov, ki niso bili vabljeni v program tako lahko zapišemo kot uteženo vsoto obeh skupin. Preživetje združenih podskupin lahko neposredno opazujemo, hkrati pa predpostavimo tudi, da bi bilo preživetje simptomatsko odkritih rakov enako kot je pri tistih, ki so bili vabljeni programu, saj jim s programom ne moremo pomagati. Ker lahko ocenimo vse preostale dele utežene vsote, lahko torej izračunamo tisti del, ki nas zanima: preživetje bolnikov, ki bi lahko bili presejalno odkriti, v situaciji, ko jih pričnemo zdraviti šele ob simptomih. Našo metodo je mogoče združiti z obstoječimi metodami, kar nam omogoča, da ocenimo uspešnost zgodnjega zdravljenja brez pristranosti. V doktorskem delu smo izvedli različne simulacije, s katerimi smo želeli ponazoriti, kako različne nastavitve simulacije vplivajo na velikost pristranosti pri naivni primerjavi in s katerimi smo evalvirali predlagano metodo. Za ilustracijo naše metodologije smo evalvirali slovenski presejalni program za odkrivanje raka dojke (DORA) in pokazali, kako analizirati podatke v primeru, ko skupini vabljenih in nevabljenih nista primerljivi. Naši ilustrativni rezultati so podprli hipotezo, da zgodnje zdravljenje izboljša preživetje bolnic z rakom dojke. Vsebinski zaključki naše študije so omejeni, saj smo za oceno časa prednosti uporabili parametre iz predhodnih študij.Cancer screening programmes (CSPs) routinely screen asymptomatic individuals in populations at risk of developing cancer using cost-effective tests. If a screening test yields positive results, a formal diagnostic test, such as a biopsy, is used to confirm the presence of cancer, ideally followed by early treatment. The underlying rationale is that treating patients who are detected on a screening test earlier than if they had presented with symptoms improves their probability of survival and, in some cases, prevents the development of an invasive malignancy altogether. Evaluation of CSPs is vital as it allows for balanced assessment of the benefits and harms associated with CSPs, and aids in optimizing public health resource allocation. Many different outcomes can be used for this purposein this thesis we focus on survival. To assess the effectiveness of early treatment, previous studies in this field relied on the naive comparison between interval (cancers detected based on symptoms after a negative test and prior to the next scheduled screening) and screen-detected cases (cancers detected based on a screening test). Realizing that the direct comparison between these two groups is subject to several biases, specifically lead time bias, length time bias and bias due to overdetection, several methods have been developed with the aim to reduce the bias. However, no existing approach has yet been able to fully account for these biases. Since the naive comparison is biased, we start this thesis by first defining the contrast of interest and subsequently search for suitable estimators. To this end, we develop a novel notation. The proposed notation is based on the notation of potential outcomes where we allow for each subject to be observed in two worlds: in world 1, we assume that the subject is invited to CSP and in world 0 we assume that the subject is not invited to CSP. Since the survival time is defined as the duration of time from diagnosis to death, both events are treated as potential outcomes and may therefore take different values in world 1 compared to world 0. In this thesis, the contrast of interest is defined as the comparison of survival for screen-detected cases in world 1, where cancer is detected earlier and treatment is initiated sooner (referred to as \u27early treatment\u27), against their survival in world 0, where diagnosis occurs at symptom presentation and subsequent treatment is delayed compared to world 1 (referred to as \u27delayed treatment\u27). To ensure a fair comparison, time zero is set at the same time in both worlds. In our case it was set at symptomatic detection, i.e. at cancer diagnosis in world 0. In this work, we formally define the contrast of interest and show how it is different from the naive comparison between interval and screen-detected cases. Lastly, we also provide the proof that the total bias that arises with the naive comparison is equal to the sum of lead time bias, length time bias and bias due to overdetection. With respect to the estimation, we show that the survival of screen-detected cases who received early treatment with time zero shifted to symptomatic detection, can be effectively estimated using existing parametric methods. However, we are missing an estimator that would allow us to estimate the second part of the contrast: the survival of screen-detected cases who received delayed treatment, as all screen-detected cases are invited for early treatment. To this end, we develop a new estimator that draws upon data from both cancer cases invited to the programme and those who were notto simplify, we initially assume that the two groups are randomized. Our estimator is based on the idea that among cancer cases not invited to the programme, some would have been detected through screening if they had been invited, while others would in any case receive diagnoses based on symptoms, either due to non-attendance or as interval cases. While we cannot determine which patient among those not invited to the programme belongs to which subgroup, we can estimate the proportion of each hypothetical subgroup (screen-detected or detected based on symptoms) using data from cancer cases invited to the programme. This enables us to express the survival of cancer cases not invited to the programme as a weighted sum of the two hypothetical subgroups. The survival of screen-detected cases that would receive delayed treatment can therefore be expressed as a weighted difference between the overall survival of cancer cases not invited to the programme and the survival of cases not invited to the programme that would have been detected based on symptoms (assumed to be equal to the survival of symptomatic cases invited to the programme). By integrating the proposed estimator with existing methods, we show that it is possible to estimate the effectiveness of early treatment provided to screen-detected cases without any bias. Our work is supplemented by simulations and illustrated using empirical data. Simulations are performed to demonstrate how the size of each bias depends on the simulation parameters and to evaluate the proposed estimator. Data from Slovenian breast CSP are analysed to demonstrate our methodology and to show how the data can be matched if the two groups, invited vs. not invited, are not randomized. The illustrative results provided support for the hypothesis that early treatment improves probability of survival for screen-detected cases and revealed that length time bias is a major source of bias that should not be neglected. The conclusions should be interpreted in the light of the study’s limitations

Structural relationships between interpersonal competencies, dispositions towards laughter and ridicule, and positive relations

Namen raziskave je bil preveriti mediatorsko vlogo odnosov do posmeha in šaljenja med medosebnimi kompetencami in pozitivnimi medosebnimi odnosi. Na priložnostnem vzorcu 476 udeležencev sem uporabil vprašalnik o odnosih do posmeha in šaljenja PhoPhiKat-45, vprašalnik empatije IRI (lestvici zavzemanje perspektive in empatična skrb), vprašalnik socialne inteligentnosti TSIS in vprašalnik psihološkega blagostanja RPWB (lestvica pozitivni medosebni odnosi). Prileganje modela sem preveril s strukturnim modeliranjem in na podlagi rezultatov obdržal model delne mediacije. V raziskavi sem zavrnil hipotezo, da lahko z odnosi do posemeha in šaljenja mediiramo povezanost med medosebnimi kompetencami in pozitivnimi medosebnimi odnosi. Model delne mediacije ima zato bolj šibko empirično podporo, čeprav lahko z njim relativno dobro pojasnimo vhodne podatke. Ugotovil sem, da je socialna inteligentnost ključen napovednik odnosov do posmeha in šaljenja. Rezultati nudijo podporo hipotezi, da je socialna inteligentnost orodje, ki ga lahko posameznik uporablja v prosocialne (adaptivni humor) ali antisocialne namene (neadaptivni oz. agresivni humor). V nasprotju s pričakovanji sem ugotovil, da se gelotofobija (strah pred posmehom) pozitivno povezuje s procesiranjem socialnih informacij, kar bi lahko pomenilo, da gelotofobisti ločijo posmeh od smeha. Bistveno vlogo pri napovedovanju pozitivnih medosebnih odnosov imajo socialne veščine, medtem ko je vpliv odnosov do posmeha in šaljenja zanemarljiv, kar postavlja humor v novo perspektivo. Zaradi nizke veljavnosti notranje strukture vprašalnika TSIS je potrebno vprašalnik revidirati in zaključke študije validirati na drugem vzorcu.The purpose of this study was to examine the mediator effects of dispositions towards laughter and ridicule between interpersonal competencies and positive relations. The study included a convenience sample of 476 participants who completed the following questionnaires: Dispositions towards laughter and ridicule PhoPhiKat-45, Interpersonal Reactivity Index IRI (perspective taking and empathy scales), Tromso Social Intelligence Scale TSIS and Ryff’s Psychological Well-Being Scales RPWB (positive relations scale). Results of the structural equation modelling showed that the partially mediated model fits the data better than the fully mediated model. In addition, I discovered no support for the mediation role of dispositions towards laughter and ridicule in the partially mediated model. The partially mediated model therefore lacked empirical support. Results supported the hypothesis that social intelligence is a tool, which may be used for both prosocial (adaptive humour) and antisocial purposes (maladaptive humor). Contrary to my expectations, the relationship between social information processing and gelotophobia is positive, which could indicate that people with excessive fear of being laughed at can perhaps distinguish between laughter and ridicule. Furthermore, social skills were the only statistically significant predictor of positive relations in the model. Dispositions towards laugther and ridicule had negligible role in predicting positive relations. To sum up, previous studies may have overstated the effect humor has on the quality of interpersonal relationships. However, my conclusions are limited because of the poor internal structure validity of the TSIS. Further studies are needed to validate my findings

Evaluating cancer screening programs using survival analysis

The main purpose of cancer screening programs is to provide early treatment to patients that are diagnosed with cancer on a screening test, thus increasing their chances of survival. To test this hypothesis directly, one should compare the survival of screen-detected cases to the survival of their counterparts not included to the program. In this study, we develop a general notation and use it to formally define the comparison of interest. We explain why the naive comparison between screen-detected and interval cases is biased and show that the total bias that arises in this case can be decomposed as a sum of lead time bias, length time bias, and bias due to overdetection. With respect to the estimation, we show what can be estimated using existing methods. To fill in the missing gap, we develop a new nonparametric estimator that allows us to estimate the survival of the control group, that is, the survival of cancer cases that would be screen-detected among those not included to the program. By joining the proposed estimator with existing methods, we show that the contrast of interest can be estimated without neglecting any of the biases. Our approach is illustrated using simulations and empirical data

COVID-19 in Slovenia, from a success story to disaster

During the first wave of the COVID-19 pandemic in spring 2020, Slovenia was among the least affected countries, but the situation became drastically worse during the second wave in autumn 2020 with high numbers of deaths per number of inhabitants, ranking Slovenia among the most affected countries. This was true even though strict non-pharmaceutical interventions (NPIs) to control the progression of the epidemic were being enforced. Using a semi-parametric Bayesian model developed for the purpose of this study, we explore if and how the changes in mobility, their timing and the activation of contact tracing can explain the differences in the epidemic progression of the two waves. To fit the model, we use data on daily numbers of deaths, patients in hospitals, intensive care units, etc., and allow transmission intensity to be affected by contact tracing and mobility (data obtained from Google Mobility Reports). Our results imply that though there is some heterogeneity not explained by mobility levels and contact tracing, implementing interventions at a similar stage as in the first wave would keep the death toll and the health system burden low in the second wave as well. On the other hand, sticking to the same timeline of interventions as observed in the second wave and focusing on enforcing a higher decrease in mobility would not be as beneficial. According to our model, the ‘dance’ strategy, i.e., first allowing the numbers to rise and then implementing strict interventions to make them drop again, has been played at too-late stages of the epidemic. In contrast, a 15–20% reduction of mobility compared to pre-COVID level, if started at the beginning and maintained for the entire duration of the second wave and coupled with contact tracing, could suffice to control the epidemic. A very important factor in this result is the presence of contact tracingwithout it, the reduction in mobility needs to be substantially larger. The flexibility of our proposed model allows similar analyses to be conducted for other regions even with slightly different data sources for the progression of the epidemicthe extension to more than two waves is straightforward. The model could help policymakers worldwide to make better decisions in terms of the timing and severity of the adopted NPIs

Estimation of life years gained in population-based cancer screening programs

Zaradi možnih negativnih zdravstvenih posledic presejalnih programov in velikih sredstev, vloženih vanje, je pomembno spremljati njihovo učinkovitost. Umrljivost v ciljni populaciji je eden od kazalnikov, ki služi za prikaz dolgoročne učinkovitosti organiziranih populacijskih presejalnih programov – po 10 do 20 letih se pričakuje padec umrljivosti v ciljni populaciji za 20 % do 30 %. Ena od glavnih omejitev kazalnika umrljivosti je, predvsem pri rakih z dobrim preživetjem, da pokaže učinkovitost presejanja šele v daljšem časovnem obdobju. Mnogokrat se zato za oceno učinkovitosti populacijskih presejalnih programov za raka uporablja analiza preživetja, pri kateri so rezultati dostopni prej. Tudi analiza preživetja ima svoje omejitve, saj se lahko v rezultate prikradejo številne pristranosti (npr. pristranost časa trajanja, prednosti in prediagnosticiranja). Nedavno smo slovenski raziskovalci predlagali nov analitični pristop, ki omogoča primerjavo preživetja pri rakih, ki so oz. niso odkriti v presejalnem programu, z upoštevanjem vseh pomembnih pristranosti. Izračunana preživetja so osnova za izračun pridobljenih let življenja, to je mere, ki izraža dodatno število let življenja, ki bi jih osebe preživele zaradi vključitve v presejalni program.V testnem primeru smo ocenili učinke uvedbe Državnega prese-jalnega program za raka dojk DOR A, ki smo ga prvim prebival-kam ponudili leta 2008, na celotno populacijo pa je bil razširjen leta 2018. Ženske, ki so bile povabljene v program DOR A v obdobju 2008–2018, so do leta 2022 pridobile skupaj 90,6 leta življenja, če bi bile v program DOR A že od leta 2008 vključene vse ženske, pa bi pridobile 552,7 leta življenja. Z vsakim dodatnim letom opazovanja, ko posamezne ženske od vključitve v program DOR A preživijo, se seštevek pridobljenih let življenja poveča.Nova metoda bo v pomoč pri upravljanju obstoječih presejalnih programov za raka, njihovi promociji in vrednotenju učinkov pri spremembah presejalnih politik.Due to the potential negative consequences of cancer screening programmes and the substantial resources invested in them, it is important to monitor their effectiveness. Mortality in the target population is one indicator that can be used to demonstrate the long-term effectiveness of organized, population-based screening programmes—after 10 to 20 years, mortality in the target population is expected to decrease by 20–30%. One of the main limitations of the mortality indicator is that, particularly for cancers with good survival rates, it only shows the effectiveness of screening over a long period of time. Therefore, survival analysis, where results are available earlier, is often used to evaluate the effectiveness of population-based cancer screening programmes. It is recognized that a number of biases can creep into the results of survival analysis (e.g. lead, length and overdiagnosis bias).Recently, Slovenian researchers have proposed a new analytical approach that allows a comparison of survival rates for cancers detected and undetected in the screening programme, taking into account all relevant biases. The calculated survival rates form the basis for the calculation of life years gained, a measure that expresses the additional number of years of life that people live as a result of participating in the screening programme.In the test case, we assessed the impact of the introduction of the National Breast Cancer Screening Programme DORA, which was first offered to residents in 2008 and expanded to the entire population in 2018. Women invited to the DORA programme in the period 2008–2022 gained a total of 90.6 life years. If all women had been included in the DORA programme since 2008, they would have gained 552.7 years of life. The total number of life years gained increases with each additional year of observation that individual women survive after enrolment in the DORA programme.The new method will help in the management of existing cancer screening programmes, their promotion and the evaluation of the impact of changes in screening policy

Estimation of life years gained in population-based cancer screening programs

Due to the potential negative consequences of cancer screening programmes and the substantial resources invested in them, it is important to monitor their effectiveness. Mortality in the target population is one indicator that can be used to demonstrate the long-term effectiveness of organized, population-based screening programmes—after 10 to 20 years, mortality in the target population is expected to decrease by 20–30%. One of the main limitations of the mortality indicator is that, particularly for cancers with good survival rates, it only shows the effectiveness of screening over a long period of time. Therefore, survival analysis, where results are available earlier, is often used to evaluate the effectiveness of population- based cancer screening programmes. It is recognized that a number of biases can creep into the results of survival analysis (e.g. lead, length and overdiagnosis bias). Recently, Slovenian researchers have proposed a new analytical approach that allows a comparison of survival rates for cancers detected and undetected in the screening programme, taking into account all relevant biases. The calculated survival rates form the basis for the calculation of life years gained, a measure that expresses the additional number of years of life that people live as a result of participating in the screening programme. In the test case, we assessed the impact of the introduction of the National Breast Cancer Screening Programme DORA, which was first offered to residents in 2008 and expanded to the entire population in 2018. Women invited to the DORA programme in the period 2008–2022 gained a total of 90.6 life years. If all women had been included in the DORA programme since 2008, they would have gained 552.7 years of life. The total number of life years gained increases with each additional year of observation that individual women survive after enrolment in the DORA programme. The new method will help in the management of existing cancer screening programmes, their promotion and the evaluation of the impact of changes in screening policy

Is it possible to predict clonal thrombocytosis in triple-negative patients with isolated thrombocytosis based only on clinical or blood findings?

JAK2, MPL, and CALR mutations define clonal thrombocytosis in about 90% of patients with sustained isolated thrombocytosis. In the remainder of patients (triple-negative patients) diagnosing clonal thrombocytosis is especially difficult due to the different underlying conditions and possible inconclusive bone marrow biopsy results. The ability to predict patients with sustained isolated thrombocytosis with a potential clonal origin has a prognostic value and warrants further examination. The aim of our study was to define a non-invasive clinical or blood parameter that could help predict clonal thrombocytosis in triple-negative patients. We studied 237 JAK2 V617-negative patients who were diagnosed with isolated thrombocytosis and referred to the haematology service. Sixteen routine clinical and blood parameters were included in the logistic regression model which was used to predict the type of thrombocytosis (reactive/clonal). Platelet count and lactate dehydrogenase (LDH) were the only statistically significant predictors of clonal thrombocytosis. The platelet count threshold for the most accurate prediction of clonal or reactive thrombocytosis was 449 × 10$^9$/L. Other tested clinical and blood parameters were not statistically significant predictors of clonal thrombocytosis. The level of LDH was significantly higher in CALR-positive patients compared to CALR-negative patients. We did not identify any new clinical or blood parameters that could distinguish clonal from reactive thrombocytosis. When diagnosing clonal thrombocytosis triple-negative patients are most likely to be misdiagnosed. Treatment in patients with suspected triple-negative clonal thrombocytosis should not be delayed if cardiovascular risk factors or pregnancy coexist, even in the absence of firm diagnostic criteria. In those cases the approach “better treat more than less” should be followed

Prognostic factor analysis of visual outcome after vitrectomy for rhegmatogenous retinal detachment

Pars plana vitrectomy (PPV) is a surgical approach mainly chosen for complex rhegmatogenous retinal detachment (RRD) repair with highly variable functional results. The aim of this analysis was to evaluate the impact of preoperative factors and postoperative optical coherence tomography (OCT) macular findings on the functional outcome of patients undergoing primary PPV for RRD. A retrospective analysis was performed on 88 eyes of 88 patients with complex RRD managed by PPV. A swept source OCT was used to obtain images at the postoperative visit at least 6 months after PPV. Hierarchical linear regression model was used to evaluate the influence of preoperative factors related to patient, ocular clinical and postoperative OCT macular findings on functional outcomes of PPV for RRD. Duration of symptoms (p = 0.031) and discontinuity of the ellipsoid zone (EZ) on OCT (p = 0.024) showed statistically significant negative correlation, while preoperative best-corrected visual acuity (BCVAp < 0.001) showed statistically significant positive correlation to postoperative BCVA. Preoperative BCVA and duration of symptoms can be used as prognostic factors for visual outcome in patients undergoing PPV for RRD. Discontinuity of the EZ was the only postoperative OCT variable related to worse postoperative visual outcome

The Relative Preservation of the Central Retinal Layers in Leber Hereditary Optic Neuropathy

(1) Background: The purpose of this study was to evaluate the thickness of retinal layers in Leber hereditary optic neuropathy (LHON) in the atrophic stage compared with presumably inherited bilateral optic neuropathy of unknown cause with the aim of seeing if any LHON-specific patterns exist. (2) Methods: 14 patients (24 eyes) with genetically confirmed LHON (LHON group) were compared with 13 patients (23 eyes) with negative genetic testing results (mtDNA + WES) and without identified etiology of bilateral optic atrophy (nonLHON group). Segmentation analysis of retinal layers in the macula and peripapillary RNFL (pRNFL) measurements was performed using Heidelberg Engineering Spectralis SD-OCT. (3) Results: In the LHON group, the thickness of ganglion cell complex (GCC) (retinal nerve fiber layer (RNFL)&mdash;ganglion cell layer (GCL)&mdash;inner plexiform layer (IPL)) in the central ETDRS (Early Treatment Diabetic Retinopathy Study) circle was significantly higher than in the nonLHON group (p &lt; 0.001). In all other ETDRS fields, GCC was thinner in the LHON group. The peripapillary RNFL (pRNFL) was significantly thinner in the LHON group in the temporal superior region (p = 0.001). Longitudinal analysis of our cohort during the follow-up time showed a tendency of thickening of the RNFL, GCL, and IPL in the LHON group in the central circle, as well as a small recovery of the pRNFL in the temporal region, which corresponds to the observed central macular thickening. (4) Conclusions: In LHON, the retinal ganglion cell complex thickness (RNFL-GCL-IPL) appears to be relatively preserved in the central ETDRS circle compared to nonLHON optic neuropathies in the chronic phase. Our findings may represent novel biomarkers as well as a structural basis for possible recovery in some patients with LHON