Glioma – Rokowania, prognozy i postęp choroby

Glioma
Rokowania, prognozy i postęp choroby

Glejaki, najczęstsze nowotwory ośrodkowego układu nerwowego, charakteryzują się zróżnicowanym rokowaniem zależnym od stopnia złośliwości, lokalizacji guza, wieku pacjenta oraz obecności specyficznych mutacji molekularnych. Glejaki WHO stopnia 1 cechują się najlepszym pięcioletnim przeżyciem na poziomie około 95%, natomiast glejaki stopnia 4, takie jak glejak wielopostaciowy, mają najgorsze rokowanie z pięcioletnim wskaźnikiem przeżycia wynoszącym zaledwie 5-10% i medianą przeżycia około 15 miesięcy. Mutacje IDH stanowią kluczowy pozytywny marker prognostyczny, szczególnie w połączeniu z kodelecją 1p/19q, natomiast delecja CDKN2A wiąże się z gorszym przeżyciem zarówno w glejakach o niskim, jak i wysokim stopniu złośliwości. Metylacja promotora MGMT jest istotnym predyktorem odpowiedzi na temozolomid (TMZ) i dłuższego całkowitego przeżycia (OS), podczas gdy defekty naprawy niedopasowań wskazują na słabą odpowiedź na TMZ. Wiek pacjenta, wynik w skali Karnofsky’ego (KPS) oraz stopień złośliwości guza pozostają niezależnymi czynnikami prognostycznymi, z gorszym rokowaniem u pacjentów ≥45 lat i KPS ≤85 (HR=2,3; 95% CI 1,141-4,776; P=0,020).

Wprowadzenie do prognozy w glejaku

Glejaki stanowią najczęstsze nowotwory ośrodkowego układu nerwowego. Rokowanie w przypadku glejaków jest bardzo zróżnicowane i zależy od wielu czynników, w tym stopnia złośliwości guza, jego wielkości i lokalizacji. Wyniki leczenia są w dużej mierze uzależnione od stopnia złośliwości, przy czym glejaki WHO stopnia 1 mają najlepsze względne przeżycie, a glejaki WHO stopnia 4 najgorszy wskaźnik przeżycia całkowitego (OS), z zaledwie 6,8% pacjentów żyjących pięć lat po rozpoznaniu.¹ Mediana przeżycia w przypadku glejaków o wysokiej złośliwości (HGG) pozostaje niska i wynosi tylko 15 miesięcy, z około 40% przeżyciem w pierwszym roku po diagnozie i 17% w drugim roku.²

Rokowanie w przypadku glejaków zależy od kilku czynników, w tym konkretnego typu i stopnia złośliwości guza, jego lokalizacji, wieku i ogólnego stanu zdrowia pacjenta oraz odpowiedzi na leczenie. Niektóre typy glejaków, takie jak glejaki o niskim stopniu złośliwości (na przykład gwiaździak włosowatokomórkowy) lub niektóre rodzaje skąpodrzewiaków, mogą mieć względnie dobre rokowanie i mogą być skutecznie leczone za pomocą operacji chirurgicznej i/lub radioterapii.³

Czynniki prognostyczne w glejaku

Markery genetyczne

U dorosłych pacjentów mutacje IDH mają największe znaczenie prognostyczne i użyteczność kliniczną, dlatego powinny być oceniane w pierwszej kolejności. Mutacje IDH są pozytywnym markerem prognostycznym.⁴⁵ Najkorzystniejsze wyniki kliniczne zaobserwowano w przypadku glejaków o niższym stopniu złośliwości z mutacjami IDH i kodelecją 1p/19q.⁶

Delecja CDKN2A jest jednak markerem najwyższego stopnia złośliwości w grupie rozlanych glejaków gwiaździakopochodnych z mutacją IDH. Delecja CDKN2A jest związana ze znacząco krótszym czasem przeżycia wolnego od progresji (PFS) i całkowitego przeżycia (OS) zarówno w przypadku glejaków o niższym stopniu złośliwości (LGG), jak i glejaków o wysokim stopniu złośliwości (HGG).⁷⁸

Kodelecja 1p/19q jest korzystnym czynnikiem prognostycznym związanym z lepszym PFS i OS, niezależnie od zastosowanej metody wykrywania.⁹¹⁰

Obecność mutacji promotora TERT, zmian w EGFR lub kombinacji zysku chromosomu 7 i utraty chromosomu 10 powoduje, że gwiaździaki typu dzikiego IDH uzyskują status glejaka wielopostaciowego. Mutacja promotora TERT jest negatywnym czynnikiem prognostycznym, ale głównie w glejach typu dzikiego IDH.¹¹¹²

U pacjentów pediatrycznych zmiany w H3F3A są najważniejszymi markerami, które przewidują gorsze rokowanie.¹³¹⁴ Ogólnie u pacjentów pediatrycznych określenie defektów białka K27 i G34 ma największe znaczenie kliniczne.¹⁵

Kombinacja mutacji IDH1 i statusu metylacji MGMT jest bardziej predykcyjna dla przeżycia niż sam IDH1 lub MGMT. Metylacja promotora MGMT ma największe znaczenie kliniczne w przewidywaniu odpowiedzi na temozolomid (TMZ) i przewiduje dłuższe OS. Z kolei defekty naprawy niedopasowań powodują fenotyp hipermutacji przewidujący słabą odpowiedź na TMZ. Połączenie zarówno mutacji IDH, jak i metylacji promotora MGMT było związane z najlepszymi wskaźnikami odpowiedzi na TMZ.¹⁶¹⁷

Czynniki kliniczne

Analiza Kaplana-Maiera wykazała, że starsi pacjenci (≥45 lat) wykazują gorsze rokowanie niż pacjenci w wieku poniżej 45 lat (P=0,038). Złe rokowanie było również związane z parametrami klinicznymi, w tym wysokim stopniem złośliwości guza, mnogimi zmianami i wynikiem w skali sprawności Karnofsky’ego (KPS).¹⁸

Analiza wieloczynnikowa wykazała, że niski KPS (≤85) zwiększa ryzyko śmiertelności 2,3-krotnie z 95% CI od 1,141 do 4,776 (P=0,020). Niski stopień złośliwości guza (stopień 1-2) przeciwnie, zmniejszał ryzyko śmiertelności o 0,22 razy (95% CI, 0,065 do 0,763, P=0,0168). KPS i stopień złośliwości guza były niezależnymi czynnikami prognostycznymi u pacjentów z glejakami.¹⁹²⁰

Wiek jest ważnym czynnikiem, który należy wziąć pod uwagę przy próbie przewidzenia rokowania pacjenta i długoterminowego przeżycia glejaka. Ogólnie rzecz biorąc, grupa wiekowa z najlepszym rokowaniem w przypadku raka mózgu to młodzi dorośli (w wieku od 15 do 39 lat). Wskaźnik przeżycia glejaka u dzieci z guzami o niskim stopniu złośliwości jest stosunkowo wysoki, często przekraczający 90% w okresie 5 lat. Glejaki o wysokim stopniu złośliwości, takie jak glejak wielopostaciowy, mają gorsze rokowanie, a wskaźniki przeżycia wahają się od 20% do 30% w ciągu pięciu lat. W większości przypadków dorośli w wieku powyżej 40 lat mają gorsze rokowanie w porównaniu z osobami w wieku poniżej 40 lat.²¹

Stopień złośliwości guza a wskaźniki przeżycia

Im wyższy stopień złośliwości, tym bardziej inwazyjny i złośliwy jest dany glejak. Ogólnie rzecz biorąc, wolno rosnący i mniej inwazyjny guz zwykle wiąże się z lepszym rokowaniem niż szybko rosnący i inwazyjny guz.²²

Stopień I (gwiaździak włosowatokomórkowy): Te guzy mają ogólnie doskonałe rokowanie. Kilka badań podaje nawet do 95% 5-letniego wskaźnika przeżycia, co oznacza, że 95% pacjentów żyje po 5 latach od rozpoznania.²³
Stopień II (gwiaździak, skąpodrzewiak, mieszany skąpogwiaździak): Te guzy są bardziej nieprzewidywalne i mogą przekształcić się w guzy stopnia III i IV nawet przy leczeniu.²⁴
Stopień III (gwiaździak anaplastyczny, skąpodrzewiak anaplastyczny, mieszany skąpogwiaździak anaplastyczny): Te guzy są bardziej agresywne i istnieje uzasadnione ryzyko nawrotu.²⁵
Stopień IV (glejak wielopostaciowy): Te guzy są najbardziej agresywne, nowotworowe i generalnie mają gorsze wyniki. Przeżycie jest często ograniczone, większość pacjentów żyje do 1 lub 2 lat. Długoterminowe przeżycie jest bardzo rzadkie.²⁶

Zgodnie z danymi American Brain Tumor Association, pięcioletni wskaźnik przeżycia dla glejaka waha się szeroko, w zależności od stopnia i innych czynników, ale wynosi od 5% do 95%. W szczególności:²⁷

Glejaki stopnia 1 (takie jak gwiaździak włosowatokomórkowy) mają bardzo dobre rokowanie, z pięcioletnim wskaźnikiem przeżycia około 95%.
Glejaki stopnia 2 (takie jak gwiaździak rozlany) mają pięcioletni wskaźnik przeżycia około 40-50%.
Glejaki stopnia 3 (takie jak gwiaździak anaplastyczny) mają pięcioletni wskaźnik przeżycia około 25-30%.
Glejaki stopnia 4 (takie jak glejak wielopostaciowy) są najbardziej agresywne i mają pięcioletni wskaźnik przeżycia około 5-10%.

Średni czas przeżycia dla starszych pacjentów z glejakiem wielopostaciowym wynosi około 9-12 miesięcy. Wielu pacjentów z glejakiem wielopostaciowym nie przeżyje dłużej niż 1 rok. Niestety, szacuje się, że mniej niż 7% pacjentów z glejakiem wielopostaciowym przeżyje 5 lat po rozpoznaniu.²⁸²⁹

Zaawansowane modele predykcyjne w glejaku

Podejścia oparte na uczeniu maszynowym

W kontekście prognozy glejaka podejścia oparte na uczeniu maszynowym (ML) mogą ułatwić nawigację przez labirynt czynników wpływających na przeżycie, pomagając klinicystom w generowaniu bardziej precyzyjnych i spersonalizowanych prognoz przeżycia. Modele ML zapewniają zindywidualizowane prognozy przeżycia dla pacjentów z glejakami stopnia II i III WHO w wielu klinicznie istotnych punktach czasowych.³⁰

Wprowadzone modele ML wraz z odpowiednią aplikacją internetową zapewniają ilościowe, spersonalizowane projekcje prawdopodobieństwa przeżycia dla pacjentów z glejakami WHO stopnia II i III. Ogólnie badania podkreślają zdolność uczenia maszynowego do prognostyki opartej na danych w neuro-onkologii i demonstrują jego ogromny potencjał w zakresie poprawy opieki klinicznej.³¹

Przewidywanie KPS u pacjentów z guzami mózgu przed leczeniem może służyć jako podstawowe narzędzie do dostosowania indywidualnych planów leczenia. Badania wykorzystujące zaawansowane obrazowanie pokazują, jak uczenie maszynowe może dokładnie klasyfikować wyniki funkcjonalne u pacjentów z HGG przed zabiegami chirurgicznymi, chemicznymi lub radioterapeutycznymi. Wyniki osiągnięto przy użyciu tylko wieku, lokalizacji guza, pomiarów RS-fMRI i wielkości guza. Włączając te modele do praktyki klinicznej, można poprawić opiekę nad pacjentem, umożliwiając spersonalizowane plany leczenia, które równoważą jakość życia z przeżyciem.³²

Radiomika i obrazowanie funkcjonalne

Ostatnie badania wykazały, że cechy radiomiczne pochodzące z obrazów MRI mogą przewidywać przeżycie w sposób nieinwazyjny. W nowozdiagnozowanym gleju wielopostaciowym typu dzikiego cechy radiomiczne MRI pochodzące z różnych składników zmiany na mapach parametrycznych dyfuzji i perfuzji mogą przewidywać przeżycie w sposób nieinwazyjny.³³

Wyniki badań wskazują, że wskaźniki predykcyjne przeżycia u pacjentów z glejakiem wielopostaciowym obejmują zarówno wskaźniki perfuzji, jak i dyfuzji, podkreślając znaczącą rolę cech mikrostrukturalnych lub hemodynamicznych w określaniu wyników pacjentów. W badaniach kształt oraz radiomica pierwszego i drugiego rzędu przyczyniły się do modelu predykcyjnego z obrazów T1W, dyfuzji i map perfuzji.³⁴

Istnieje również potencjał wykorzystania obrazów syntetycznych do predykcji prognozy. Proponowana metoda wykorzystująca CycleGAN była w stanie syntezować obrazy z taką samą dokładnością jak obrazy rzeczywiste. Co więcej, proponowany model prognostyczny oparty na CycleGAN jest porównywalny z konwencjonalnym modelem prognostycznym z rzeczywistymi obrazami. Może to zmniejszyć koszty i czas skanowania obrazów, co prowadzi do promowania budowania prognoz wyników pacjentów z obrazami wielokontrastowymi.³⁵

Sygnatury molekularne

Sygnatury oparte na genach metabolizmu metioniny wykazały również wartość prognostyczną w glejach. Sygnatura prognostyczna oparta na siedmiu genach metabolizmu metioniny okazała się skuteczna w przewidywaniu glejaków. Wskaźnik C dla sygnatury ryzyka metabolizmu metioniny wynosił 0,83, co jest wyższe niż w przypadku rutynowych badań klinicznych dla glejaka.³⁶

Sygnatura ryzyka metabolizmu metioniny okazała się wysoce predykcyjna w podgrupach pacjentów z glejakami IDH wt, IDH mutant-codel i IDH mutant-non-codel. Model miał wysoką dokładność w przewidywaniu całkowitego przeżycia pacjentów z glejakami. Model był ściśle związany ze statusem wyniku zarówno w kohortach pochodnych, jak i walidacyjnych, zapewniając nowe spojrzenie na prognozowanie rokowania glejaków.³⁷

Funkcjonalna medycyna precyzyjna w prognozowaniu glejaka

Test 3D Predict Glioma zapewnia funkcjonalne wyniki w ciągu 7-10 dni od otrzymania tkanki, umożliwiając optymalizację leczenia pacjenta przed rozpoczęciem terapii. Silna korelacja wyników testu 3D Predict Glioma z wynikami klinicznymi pokazuje, że ten test funkcjonalny ma znaczenie prognostyczne u pacjentów leczonych RT/TMZ i wspiera dostosowanie leczenia klinicznego do odpowiedzi przewidywanej przez test w różnych podgrupach HGG.³⁸

Mediana przeżycia między osobami przewidywanymi jako reagujące na temozolomid i osobami przewidywanymi jako niereagujące na temozolomid wykazała statystycznie istotny wzrost przeżycia wolnego od progresji przy użyciu testu do przewidywania odpowiedzi w wielu podgrupach, w tym HGG (5,8 miesiąca), glejaka wielopostaciowego (4,7 miesiąca) i glejaka wielopostaciowego MGMT bez metylacji (4,7 miesiąca). Całkowite przeżycie również pozytywnie rozdzielało się między podgrupami odpowiednio o 7,6, 5,1 i 6,3 miesiąca.³⁹

Dane te, wraz z wcześniej opublikowanymi danymi, pokazują moc 3D Predict Glioma i funkcjonalnej medycyny precyzyjnej do zapewnienia przewidywań odpowiedzi na leki specyficznych dla pacjenta, wykraczających poza obecne ograniczenia tradycyjnych biomarkerów w HGG i glejakach wielopostaciowych.⁴⁰

Podsumowanie i perspektywy

Znaczniki prognostyczne i predykcyjne odgrywają ważną rolę w praktyce klinicznej do oceny rokowania i wyboru odpowiedniej terapii. Wiele biomarkerów zostało zgłoszonych i jest obecnie klinicznie stosowanych w zarządzaniu pacjentami z neuroonkologią. Obecnie odgrywają one kluczową rolę w poprawie dokładności diagnostycznej, określaniu rokowania i przewidywaniu odpowiedzi na leczenie.⁴¹

U dorosłych pacjentów mutacja IDH ma największe znaczenie prognostyczne i użyteczność kliniczną, dlatego powinna być oceniana w pierwszej kolejności. Metylacja promotora MGMT ma największy wpływ na praktykę kliniczną u pacjentów z glejakiem wielopostaciowym.⁴²⁴³

Nowe metody, takie jak modele uczenia maszynowego i radiomica, zapewniają obiecujące narzędzia do bardziej precyzyjnego i spersonalizowanego przewidywania rokowania. Funkcjonalna medycyna precyzyjna, taka jak test 3D Predict Glioma, oferuje również potencjał do optymalizacji leczenia i poprawy wyników pacjentów. Postępy te mogą prowadzić do bardziej precyzyjnych podejść terapeutycznych dostosowanych do indywidualnych pacjentów.⁴⁴⁴⁵

Należy pamiętać, że statystyki i średnie nie mogą powiedzieć, co stanie się konkretnie z danym pacjentem. Różni ludzie podchodzą do swojego rokowania w różny sposób, a rozmowa z zespołem medycznym o indywidualnym rokowaniu i opcjach leczenia pozostaje kluczowa.⁴⁶

Kolejne rozdziały

Zapraszamy do dalszego czytania naszego leksykonu.

Wybierz kolejny rozdział z menu poniżej, aby otworzyć nową podstronę kompedium wiedzy i uzyskać szczegółowe informację o leku, substancji lub chorobie.

Materiały źródłowe

#1 Prognostic and Predictive Biomarkers in Gliomas
https://www.mdpi.com/1422-0067/22/19/10373
Gliomas are the most common central nervous system tumors. […] Survival outcomes are largely dependent on grade, with CNS World Health Organization (WHO) grade 1 having the best relative survival, and CNS WHO grade 4 having the worst overall survival (OS) rate, with just 6.8% of patients living for five years after diagnosis. […] Prognostic and predictive markers play an important role in clinical practice for the assessment of prognosis and the selection of appropriate therapy. […] In adult patients, IDH mutation has the greatest prognostic significance and clinical utility. Therefore, it should be assessed first and foremost. […] In malignant gliomas, the combination of IDH1 mutations and MGMT methylation status is more predictive of survival than either IDH1 or MGMT alone. […] In pediatric patients, H3F3A alterations are the most important markers which predict the worse outcome.
#2 Survival Outcome Prediction in Glioblastoma: Insights from MRI Radiomics
https://www.mdpi.com/1718-7729/31/4/165
Survival Outcome Prediction in Glioblastoma: Insights from MRI Radiomics […] The median survival remains low at only 15 months, with approximately 40% survival in the first year post diagnosis and 17% in the second year. […] The final Cox proportional-hazards model had age and six radiomic features with nonzero coefficients. […] The C-Index of the model was 0.66 (95% C.I. 0.54â0.80). […] The results of the present study indicate that predictive indices of survival in patients with GBM include both perfusion and diffusion indices, highlighting the significant role of microstructural or hemodynamic characteristics in determining patient outcomes. […] In our study, shape and first and second order radiomic features contributed to the prediction model from T1W, diffusion, and perfusion maps. […] In newly diagnosed wild-type GBM, MRI radiomic features derived from various components of the lesion on diffusion and perfusion parametric maps can predict survival in a non-invasive manner.
#3
https://braintumourresearch.org/pages/types-of-brain-tumours-glioma?srsltid=AfmBOoo4uWSq1iOsvDku1pMaAmg3xAzkwY2IyTXxWFdXg_FabfKWe-bI
The prognosis for gliomas depends on several factors, including the specific type and grade of the tumour, its location, the age and overall health of the patient, and the response to treatment. Some types of gliomas, such as low-grade gliomas (for example pilocytic astrocytoma) or certain types of oligodendrogliomas, may have a relatively good prognosis and may be treated successfully with surgery and/or radiation therapy.
#4 Prognostic and Predictive Biomarkers in Gliomas
https://www.mdpi.com/1422-0067/22/19/10373
Gliomas are the most common central nervous system tumors. […] Survival outcomes are largely dependent on grade, with CNS World Health Organization (WHO) grade 1 having the best relative survival, and CNS WHO grade 4 having the worst overall survival (OS) rate, with just 6.8% of patients living for five years after diagnosis. […] Prognostic and predictive markers play an important role in clinical practice for the assessment of prognosis and the selection of appropriate therapy. […] In adult patients, IDH mutation has the greatest prognostic significance and clinical utility. Therefore, it should be assessed first and foremost. […] In malignant gliomas, the combination of IDH1 mutations and MGMT methylation status is more predictive of survival than either IDH1 or MGMT alone. […] In pediatric patients, H3F3A alterations are the most important markers which predict the worse outcome.
#5 Prognostic and Predictive Biomarkers in Gliomas
https://pmc.ncbi.nlm.nih.gov/articles/PMC8508830/
Gliomas are the most common central nervous system tumors. […] In adult patients, IDH mutations are positive prognostic markers and have the greatest prognostic significance. […] However, CDKN2A deletion, in IDH-mutant astrocytomas, is a marker of the highest malignancy grade. […] Moreover, the presence of TERT promoter mutations, EGFR alterations, or a combination of chromosome 7 gain and 10 loss upgrade IDH-wildtype astrocytoma to glioblastoma. […] In pediatric patients, H3F3A alterations are the most important markers which predict the worse outcome. […] MGMT promoter methylation has the greatest clinical significance in predicting responses to temozolomide (TMZ). […] Conversely, mismatch repair defects cause hypermutation phenotype predicting poor response to TMZ. […] Prognostic and predictive markers play an important role in clinical practice for the assessment of prognosis and the selection of appropriate therapy.
#6 Prognostic and Predictive Biomarkers in Gliomas
https://pmc.ncbi.nlm.nih.gov/articles/PMC8508830/
The combination of IDH1 mutations and MGMT methylation status is more predictive of survival than either IDH1 or MGMT alone. […] In adult patients, IDH mutation has the greatest prognostic significance and clinical utility. Therefore, it should be assessed first and foremost. […] The most favorable clinical outcomes were observed in lower-grade gliomas with IDH mutations and 1p/19q codeletion. […] CDKN2A homozygous deletion is a significant prognostic factor in IDH-mutant glioma patients across multiple histologic WHO grades. […] The presence of homozygous CDKN2A/B deletion is a marker of the highest malignancy grade in the group of diffuse, IDH-mutant astrocytomas. […] 1p/19q codeletion is a favorable prognostic factor associated with a better PFS and OS regardless of the detection method used.
#7 Prognostic and Predictive Biomarkers in Gliomas
https://www.mdpi.com/1422-0067/22/19/10373
MGMT promoter methylation has the greatest clinical significance in predicting responses to temozolomide (TMZ). […] Conversely, mismatch repair defects cause hypermutation phenotype predicting poor response to TMZ. […] CDKN2A deletion is associated with significantly shorter PFS and OS in both lower-grade glioma (LGG) and HGG. […] The presence of homozygous CDKN2A/B deletion is a marker of the highest malignancy grade in the group of diffuse, IDH-mutant astrocytomas. […] 1p/19q codeletion is a favorable prognostic factor associated with a better PFS and OS regardless of the detection method used. […] 7+/10â is a negative prognostic factor in gliomas. […] TERT promoter mutation is a negative prognostic factor, but mainly in IDH-wildtype gliomas. […] EGFR amplifications have been reported to indicate a much more aggressive tumor subpopulation. […] MGMT promoter methylation predicts longer OS. […] The combination of both IDH mutations and MGMT promoter methylation was associated with the best response rates to TMZ.
#8 Prognostic and Predictive Biomarkers in Gliomas
https://pmc.ncbi.nlm.nih.gov/articles/PMC8508830/
Gliomas are the most common central nervous system tumors. […] In adult patients, IDH mutations are positive prognostic markers and have the greatest prognostic significance. […] However, CDKN2A deletion, in IDH-mutant astrocytomas, is a marker of the highest malignancy grade. […] Moreover, the presence of TERT promoter mutations, EGFR alterations, or a combination of chromosome 7 gain and 10 loss upgrade IDH-wildtype astrocytoma to glioblastoma. […] In pediatric patients, H3F3A alterations are the most important markers which predict the worse outcome. […] MGMT promoter methylation has the greatest clinical significance in predicting responses to temozolomide (TMZ). […] Conversely, mismatch repair defects cause hypermutation phenotype predicting poor response to TMZ. […] Prognostic and predictive markers play an important role in clinical practice for the assessment of prognosis and the selection of appropriate therapy.
#9 Prognostic and Predictive Biomarkers in Gliomas
https://www.mdpi.com/1422-0067/22/19/10373
MGMT promoter methylation has the greatest clinical significance in predicting responses to temozolomide (TMZ). […] Conversely, mismatch repair defects cause hypermutation phenotype predicting poor response to TMZ. […] CDKN2A deletion is associated with significantly shorter PFS and OS in both lower-grade glioma (LGG) and HGG. […] The presence of homozygous CDKN2A/B deletion is a marker of the highest malignancy grade in the group of diffuse, IDH-mutant astrocytomas. […] 1p/19q codeletion is a favorable prognostic factor associated with a better PFS and OS regardless of the detection method used. […] 7+/10â is a negative prognostic factor in gliomas. […] TERT promoter mutation is a negative prognostic factor, but mainly in IDH-wildtype gliomas. […] EGFR amplifications have been reported to indicate a much more aggressive tumor subpopulation. […] MGMT promoter methylation predicts longer OS. […] The combination of both IDH mutations and MGMT promoter methylation was associated with the best response rates to TMZ.
#10 Prognostic and Predictive Biomarkers in Gliomas
https://pmc.ncbi.nlm.nih.gov/articles/PMC8508830/
The combination of IDH1 mutations and MGMT methylation status is more predictive of survival than either IDH1 or MGMT alone. […] In adult patients, IDH mutation has the greatest prognostic significance and clinical utility. Therefore, it should be assessed first and foremost. […] The most favorable clinical outcomes were observed in lower-grade gliomas with IDH mutations and 1p/19q codeletion. […] CDKN2A homozygous deletion is a significant prognostic factor in IDH-mutant glioma patients across multiple histologic WHO grades. […] The presence of homozygous CDKN2A/B deletion is a marker of the highest malignancy grade in the group of diffuse, IDH-mutant astrocytomas. […] 1p/19q codeletion is a favorable prognostic factor associated with a better PFS and OS regardless of the detection method used.
#11 Prognostic and Predictive Biomarkers in Gliomas
https://www.mdpi.com/1422-0067/22/19/10373
MGMT promoter methylation has the greatest clinical significance in predicting responses to temozolomide (TMZ). […] Conversely, mismatch repair defects cause hypermutation phenotype predicting poor response to TMZ. […] CDKN2A deletion is associated with significantly shorter PFS and OS in both lower-grade glioma (LGG) and HGG. […] The presence of homozygous CDKN2A/B deletion is a marker of the highest malignancy grade in the group of diffuse, IDH-mutant astrocytomas. […] 1p/19q codeletion is a favorable prognostic factor associated with a better PFS and OS regardless of the detection method used. […] 7+/10â is a negative prognostic factor in gliomas. […] TERT promoter mutation is a negative prognostic factor, but mainly in IDH-wildtype gliomas. […] EGFR amplifications have been reported to indicate a much more aggressive tumor subpopulation. […] MGMT promoter methylation predicts longer OS. […] The combination of both IDH mutations and MGMT promoter methylation was associated with the best response rates to TMZ.
#12 Prognostic and Predictive Biomarkers in Gliomas
https://pmc.ncbi.nlm.nih.gov/articles/PMC8508830/
Gliomas are the most common central nervous system tumors. […] In adult patients, IDH mutations are positive prognostic markers and have the greatest prognostic significance. […] However, CDKN2A deletion, in IDH-mutant astrocytomas, is a marker of the highest malignancy grade. […] Moreover, the presence of TERT promoter mutations, EGFR alterations, or a combination of chromosome 7 gain and 10 loss upgrade IDH-wildtype astrocytoma to glioblastoma. […] In pediatric patients, H3F3A alterations are the most important markers which predict the worse outcome. […] MGMT promoter methylation has the greatest clinical significance in predicting responses to temozolomide (TMZ). […] Conversely, mismatch repair defects cause hypermutation phenotype predicting poor response to TMZ. […] Prognostic and predictive markers play an important role in clinical practice for the assessment of prognosis and the selection of appropriate therapy.
#13 Prognostic and Predictive Biomarkers in Gliomas
https://www.mdpi.com/1422-0067/22/19/10373
Gliomas are the most common central nervous system tumors. […] Survival outcomes are largely dependent on grade, with CNS World Health Organization (WHO) grade 1 having the best relative survival, and CNS WHO grade 4 having the worst overall survival (OS) rate, with just 6.8% of patients living for five years after diagnosis. […] Prognostic and predictive markers play an important role in clinical practice for the assessment of prognosis and the selection of appropriate therapy. […] In adult patients, IDH mutation has the greatest prognostic significance and clinical utility. Therefore, it should be assessed first and foremost. […] In malignant gliomas, the combination of IDH1 mutations and MGMT methylation status is more predictive of survival than either IDH1 or MGMT alone. […] In pediatric patients, H3F3A alterations are the most important markers which predict the worse outcome.
#14 Prognostic and Predictive Biomarkers in Gliomas
https://pmc.ncbi.nlm.nih.gov/articles/PMC8508830/
Gliomas are the most common central nervous system tumors. […] In adult patients, IDH mutations are positive prognostic markers and have the greatest prognostic significance. […] However, CDKN2A deletion, in IDH-mutant astrocytomas, is a marker of the highest malignancy grade. […] Moreover, the presence of TERT promoter mutations, EGFR alterations, or a combination of chromosome 7 gain and 10 loss upgrade IDH-wildtype astrocytoma to glioblastoma. […] In pediatric patients, H3F3A alterations are the most important markers which predict the worse outcome. […] MGMT promoter methylation has the greatest clinical significance in predicting responses to temozolomide (TMZ). […] Conversely, mismatch repair defects cause hypermutation phenotype predicting poor response to TMZ. […] Prognostic and predictive markers play an important role in clinical practice for the assessment of prognosis and the selection of appropriate therapy.
#15 Prognostic and Predictive Biomarkers in Gliomas
https://pmc.ncbi.nlm.nih.gov/articles/PMC8508830/
7+/10 is a negative prognostic factor in gliomas. […] TERT promoter mutation is a negative prognostic factor, but mainly in IDH-wildtype gliomas. […] Overall, in pediatric patients, the determination of protein K27 and G34 defects is of the greatest clinical importance. […] In glioma patients with MYB and MYBL1 mutations, the clinical course is generally indolent. […] The MAPK pathway activation is a predictor of a favorable patient outcome. […] MGMT promoter methylation has the most impact on clinical practice for patients with glioblastoma. […] Many biomarkers have been reported and are now clinically used in the management of neuro-oncology patients. They now play a crucial role in improving diagnostic accuracy, determining prognosis, and predicting treatment responses.
#16 Prognostic and Predictive Biomarkers in Gliomas
https://www.mdpi.com/1422-0067/22/19/10373
MGMT promoter methylation has the greatest clinical significance in predicting responses to temozolomide (TMZ). […] Conversely, mismatch repair defects cause hypermutation phenotype predicting poor response to TMZ. […] CDKN2A deletion is associated with significantly shorter PFS and OS in both lower-grade glioma (LGG) and HGG. […] The presence of homozygous CDKN2A/B deletion is a marker of the highest malignancy grade in the group of diffuse, IDH-mutant astrocytomas. […] 1p/19q codeletion is a favorable prognostic factor associated with a better PFS and OS regardless of the detection method used. […] 7+/10â is a negative prognostic factor in gliomas. […] TERT promoter mutation is a negative prognostic factor, but mainly in IDH-wildtype gliomas. […] EGFR amplifications have been reported to indicate a much more aggressive tumor subpopulation. […] MGMT promoter methylation predicts longer OS. […] The combination of both IDH mutations and MGMT promoter methylation was associated with the best response rates to TMZ.
#17 Prognostic and Predictive Biomarkers in Gliomas
https://pmc.ncbi.nlm.nih.gov/articles/PMC8508830/
Gliomas are the most common central nervous system tumors. […] In adult patients, IDH mutations are positive prognostic markers and have the greatest prognostic significance. […] However, CDKN2A deletion, in IDH-mutant astrocytomas, is a marker of the highest malignancy grade. […] Moreover, the presence of TERT promoter mutations, EGFR alterations, or a combination of chromosome 7 gain and 10 loss upgrade IDH-wildtype astrocytoma to glioblastoma. […] In pediatric patients, H3F3A alterations are the most important markers which predict the worse outcome. […] MGMT promoter methylation has the greatest clinical significance in predicting responses to temozolomide (TMZ). […] Conversely, mismatch repair defects cause hypermutation phenotype predicting poor response to TMZ. […] Prognostic and predictive markers play an important role in clinical practice for the assessment of prognosis and the selection of appropriate therapy.
#18 Prognostic factors of patients with Gliomas â an analysis on 335 patients with Glioblastoma and other forms of Gliomas | BMC Cancer | Full Text
https://bmccancer.biomedcentral.com/articles/10.1186/s12885-019-6511-6
The prognosis of glioma is poor, despite recent advances in diagnosis and treatment of the disease. […] It is important to investigate the clinical characteristics and prognostic factors of glioma so as to provide basis for treatment and management of patients. […] Kaplan-Maier analysis revealed that older patients ( 45years) displayed worse prognosis than those aged under 45years (P=0.038). […] Dismal prognosis was also associated with clinical parameters, including high tumor grade, multiple lesions, and Karnofsky performance score (KPS). […] Multivariate analysis showed that low KPS (85) increased the risk of mortality by 2.3 folds with a 95% CI of 1.141 to 4.776 (P=0.020). […] Low tumor grade (grade 12) oppositely reduced the mortality risk by 0.22 folds (95% CI, 0.065 to 0.763, P=0.0168).
#19 Prognostic factors of patients with Gliomas â an analysis on 335 patients with Glioblastoma and other forms of Gliomas | BMC Cancer | Full Text
https://bmccancer.biomedcentral.com/articles/10.1186/s12885-019-6511-6
The prognosis of glioma is poor, despite recent advances in diagnosis and treatment of the disease. […] It is important to investigate the clinical characteristics and prognostic factors of glioma so as to provide basis for treatment and management of patients. […] Kaplan-Maier analysis revealed that older patients ( 45years) displayed worse prognosis than those aged under 45years (P=0.038). […] Dismal prognosis was also associated with clinical parameters, including high tumor grade, multiple lesions, and Karnofsky performance score (KPS). […] Multivariate analysis showed that low KPS (85) increased the risk of mortality by 2.3 folds with a 95% CI of 1.141 to 4.776 (P=0.020). […] Low tumor grade (grade 12) oppositely reduced the mortality risk by 0.22 folds (95% CI, 0.065 to 0.763, P=0.0168).
#20 Prognostic factors of patients with Gliomas â an analysis on 335 patients with Glioblastoma and other forms of Gliomas | BMC Cancer | Full Text
https://bmccancer.biomedcentral.com/articles/10.1186/s12885-019-6511-6
KPS and tumor grade were independent prognostic factors in patients with gliomas. […] Our analysis suggested that low KPS is an independent risk factor for mortality within the first year after treatment and in long-term survival of glioma patients. […] Multivariate analysis further indicated that low KPS and low tumor grade can significantly elevate and reduce, respectively, the risk of mortality of patients.
#21 Outlook for Glioma | Expert Surgeon | Aaron Cohen-Gadol, MD
https://www.aaroncohen-gadol.com/en/patients/glioma/survival/outlook
Many patients with glioblastoma will not survive longer than 1 year. Unfortunately, it is estimated that less than 7% of patients with glioblastoma will survive to 5 years after their diagnosis. […] Age is an important factor to consider when trying to predict a patients prognosis and long-term glioma survival. […] Generally speaking, the age group with the best prognosis with brain cancer is young adults (ages between 15 and 39). […] The glioma survival rate for children with low-grade tumors is relatively high, often exceeding 90% for a 5-year period. […] High-grade gliomas, such as glioblastomas, have a more guarded prognosis, with survival rates ranging from 20% to 30% over five years. […] In most cases, adults older than 40 have a worse prognosis when compared to individuals younger than 40.
#22 Outlook for Glioma | Expert Surgeon | Aaron Cohen-Gadol, MD
https://www.aaroncohen-gadol.com/en/patients/glioma/survival/outlook
Prognosis, or recovery outlook, for glioma is highly variable and depends on the tumor grade, size, and location. […] Factors such as age, extent of tumor removal during surgery, and overall mental and physical function of patients at the time of diagnosis are also useful indicators of prognosis. […] In short, the prognosis of a brain tumor estimates the length of time an average person lives after diagnosis. […] The higher the grade, the more invasive and malignant a particular glioma is. In general, a slow-growing and less invasive tumor usually carries a better prognosis than a fast-growing and invasive tumor. […] Grade I (pilocytic astrocytoma): These tumors generally have an excellent prognosis. Several studies have reported up to a 95% 5-year survival rate, which means that 95% of patients are living after 5 years of being diagnosed.
#23 Outlook for Glioma | Expert Surgeon | Aaron Cohen-Gadol, MD
https://www.aaroncohen-gadol.com/en/patients/glioma/survival/outlook
Prognosis, or recovery outlook, for glioma is highly variable and depends on the tumor grade, size, and location. […] Factors such as age, extent of tumor removal during surgery, and overall mental and physical function of patients at the time of diagnosis are also useful indicators of prognosis. […] In short, the prognosis of a brain tumor estimates the length of time an average person lives after diagnosis. […] The higher the grade, the more invasive and malignant a particular glioma is. In general, a slow-growing and less invasive tumor usually carries a better prognosis than a fast-growing and invasive tumor. […] Grade I (pilocytic astrocytoma): These tumors generally have an excellent prognosis. Several studies have reported up to a 95% 5-year survival rate, which means that 95% of patients are living after 5 years of being diagnosed.
#24 Outlook for Glioma | Expert Surgeon | Aaron Cohen-Gadol, MD
https://www.aaroncohen-gadol.com/en/patients/glioma/survival/outlook
Grade II (astrocytoma, oligodendroglioma, mixed oligoastrocytoma): These tumors are more unpredictable and can progress into Grade III and IV tumors even with treatment. […] Grade III (anaplastic astrocytoma, anaplastic oligodendroglioma, anaplastic mixed oligoastrocytoma): These tumors are more aggressive and have a reasonable risk of recurrence. […] Grade IV (glioblastoma): These tumors are the most aggressive, cancerous, and generally have worse outcomes. Survival is often limited, with most patients living up to 1 or 2 years. Long-term survival is very rare. […] It may be helpful to think of gliomas on a spectrum with low-grade gliomas being at one end of the spectrum with the best survival rates. […] Several types of low-grade glioma carry survival rates that can surpass 15 years.
#25 Outlook for Glioma | Expert Surgeon | Aaron Cohen-Gadol, MD
https://www.aaroncohen-gadol.com/en/patients/glioma/survival/outlook
Grade II (astrocytoma, oligodendroglioma, mixed oligoastrocytoma): These tumors are more unpredictable and can progress into Grade III and IV tumors even with treatment. […] Grade III (anaplastic astrocytoma, anaplastic oligodendroglioma, anaplastic mixed oligoastrocytoma): These tumors are more aggressive and have a reasonable risk of recurrence. […] Grade IV (glioblastoma): These tumors are the most aggressive, cancerous, and generally have worse outcomes. Survival is often limited, with most patients living up to 1 or 2 years. Long-term survival is very rare. […] It may be helpful to think of gliomas on a spectrum with low-grade gliomas being at one end of the spectrum with the best survival rates. […] Several types of low-grade glioma carry survival rates that can surpass 15 years.
#26 Outlook for Glioma | Expert Surgeon | Aaron Cohen-Gadol, MD
https://www.aaroncohen-gadol.com/en/patients/glioma/survival/outlook
Grade II (astrocytoma, oligodendroglioma, mixed oligoastrocytoma): These tumors are more unpredictable and can progress into Grade III and IV tumors even with treatment. […] Grade III (anaplastic astrocytoma, anaplastic oligodendroglioma, anaplastic mixed oligoastrocytoma): These tumors are more aggressive and have a reasonable risk of recurrence. […] Grade IV (glioblastoma): These tumors are the most aggressive, cancerous, and generally have worse outcomes. Survival is often limited, with most patients living up to 1 or 2 years. Long-term survival is very rare. […] It may be helpful to think of gliomas on a spectrum with low-grade gliomas being at one end of the spectrum with the best survival rates. […] Several types of low-grade glioma carry survival rates that can surpass 15 years.
#27
https://braintumourresearch.org/pages/types-of-brain-tumours-glioma?srsltid=AfmBOoo4uWSq1iOsvDku1pMaAmg3xAzkwY2IyTXxWFdXg_FabfKWe-bI
A glioma is a type of brain tumour that has developed from cells that should have become healthy glial cells in the brain. Glioma brain tumours vary across the spectrum of low-grade (slow-growing) to high-grade (faster-growing). The stage 4 glioma survival rate is lower than the survival rate for a stage 1 glioma, as higher grades have a poorer prognosis than lower grades. […] The survival rate for glioma can vary widely depending on the specific type and grade of the tumour, as well as the individual’s age, overall health and other factors. Glioma is a type of brain tumour that originates in the glial cells, which are the supportive cells in the brain. Gliomas are classified by grade, ranging from grade 1 (least aggressive) to grade 4 (most aggressive). According to the American Brain Tumor Association, the five-year survival rate for glioma varies widely, depending on the grade and other factors, but ranges from 5% to 95%. Specifically: Grade 1 gliomas (such as pilocytic astrocytoma) generally have a very good prognosis, with a five-year survival rate of around 95%. Grade 2 gliomas (such as diffuse astrocytoma) have a five-year survival rate of around 40-50%. Grade 3 gliomas (such as anaplastic astrocytoma) have a five-year survival rate of around 25-30%. Grade 4 gliomas (such as glioblastoma) are the most aggressive and have a five-year survival rate of around 5-10%.
#28 Outlook for Glioma | Expert Surgeon | Aaron Cohen-Gadol, MD
https://www.aaroncohen-gadol.com/en/patients/glioma/survival/outlook
Many patients with glioblastoma will not survive longer than 1 year. Unfortunately, it is estimated that less than 7% of patients with glioblastoma will survive to 5 years after their diagnosis. […] Age is an important factor to consider when trying to predict a patients prognosis and long-term glioma survival. […] Generally speaking, the age group with the best prognosis with brain cancer is young adults (ages between 15 and 39). […] The glioma survival rate for children with low-grade tumors is relatively high, often exceeding 90% for a 5-year period. […] High-grade gliomas, such as glioblastomas, have a more guarded prognosis, with survival rates ranging from 20% to 30% over five years. […] In most cases, adults older than 40 have a worse prognosis when compared to individuals younger than 40.
#29 Outlook for Glioma | Expert Surgeon | Aaron Cohen-Gadol, MD
https://www.aaroncohen-gadol.com/en/patients/glioma/survival/outlook
The median survival time for older patients with glioblastoma is approximately 9 to 12 months. […] People with gliomas with a genetic marker called MGMT methylation generally experience a better glioma tumor survival rate. […] MGMT methylation makes the tumor cells more responsive to certain chemotherapies, enhancing the effectiveness of the treatment and potentially improving glioma survival rate.
#30 Prognosis Individualized: Survival predictions for WHO grade II and III gliomas with a machine learning-based web application | npj Digital Medicine
https://www.nature.com/articles/s41746-023-00948-y
WHO grade II and III gliomas demonstrate diverse biological behaviors resulting in variable survival outcomes. […] In the context of glioma prognosis, machine learning (ML) approaches could facilitate the navigation through the maze of factors influencing survival, aiding clinicians in generating more precise and personalized survival predictions. […] ML models provide individualized survival forecasts for grade II and III glioma patients across multiple clinically relevant time points. […] This study introduces a suite of ML models adept at predicting survival prognoses for WHO grade II and III gliomas at 12, 24, 36, and 60 months subsequent to diagnosis. […] The predictions rendered by our models can be used to ascertain a patient’s prognosis at various intervals following their diagnosis, thereby enriching patient care.
#31 Prognosis Individualized: Survival predictions for WHO grade II and III gliomas with a machine learning-based web application | npj Digital Medicine
https://www.nature.com/articles/s41746-023-00948-y
The ML models, along with the corresponding web application, we introduce with this study, provide quantitative, personalized survival probability projections for WHO grade II and III glioma patients. […] Overall, this work underscores the aptitude of machine learning for data-driven prognostication in neuro-oncology and demonstrates its immense potential to augment clinical care.
#32
https://link.springer.com/article/10.1007/s11060-024-04715-1
Predicting KPS in brain tumor patients prior to treatment can serve as a foundational tool for tailoring individualized treatment plans. […] Ours is among the first to use RS-fMRI to predict functional outcomes in HGG directly. […] Our findings show a distinct dichotomy between the anatomical location of the tumor and functional connectivity (FC) changes, specifically concerning their predictive ability for KPS. […] Our results indicate tumor volume was only a moderate predictor of KPS, which might initially appear counterintuitive. However, this finding underscores the critical point that tumor location in relation to functional networks could have a more significant influence on functional outcomes than the size of the tumor alone. […] This research demonstrates how machine learning can accurately classify functional outcomes in HGG patients prior to surgical, chemical, or radiotherapy treatments. These results were achieved using only age, tumor location, RS-fMRI measures, and tumor size. By incorporating these models into clinical practice, we stand to enhance patient care, enabling personalized treatment plans that balance quality of life with survival.
#33 Survival Outcome Prediction in Glioblastoma: Insights from MRI Radiomics
https://www.mdpi.com/1718-7729/31/4/165
Survival Outcome Prediction in Glioblastoma: Insights from MRI Radiomics […] The median survival remains low at only 15 months, with approximately 40% survival in the first year post diagnosis and 17% in the second year. […] The final Cox proportional-hazards model had age and six radiomic features with nonzero coefficients. […] The C-Index of the model was 0.66 (95% C.I. 0.54â0.80). […] The results of the present study indicate that predictive indices of survival in patients with GBM include both perfusion and diffusion indices, highlighting the significant role of microstructural or hemodynamic characteristics in determining patient outcomes. […] In our study, shape and first and second order radiomic features contributed to the prediction model from T1W, diffusion, and perfusion maps. […] In newly diagnosed wild-type GBM, MRI radiomic features derived from various components of the lesion on diffusion and perfusion parametric maps can predict survival in a non-invasive manner.
#34 Survival Outcome Prediction in Glioblastoma: Insights from MRI Radiomics
https://www.mdpi.com/1718-7729/31/4/165
Survival Outcome Prediction in Glioblastoma: Insights from MRI Radiomics […] The median survival remains low at only 15 months, with approximately 40% survival in the first year post diagnosis and 17% in the second year. […] The final Cox proportional-hazards model had age and six radiomic features with nonzero coefficients. […] The C-Index of the model was 0.66 (95% C.I. 0.54â0.80). […] The results of the present study indicate that predictive indices of survival in patients with GBM include both perfusion and diffusion indices, highlighting the significant role of microstructural or hemodynamic characteristics in determining patient outcomes. […] In our study, shape and first and second order radiomic features contributed to the prediction model from T1W, diffusion, and perfusion maps. […] In newly diagnosed wild-type GBM, MRI radiomic features derived from various components of the lesion on diffusion and perfusion parametric maps can predict survival in a non-invasive manner.
#35
https://link.springer.com/article/10.1007/s13246-024-01443-8
There are several methods for predicting OS. […] In addition to clinical factors, MRI images have been used for prognosis prediction. […] Recently, quantitative imaging features derived from medical imaging were of added value in predicting outcome parameters in oncology in what is called Radiomics. […] The proposed method using CycleGAN was able to synthesize images with the same accuracy as the real images. Moreover, our proposed CycleGAN-based prognosis model is comparable to the conventional prognosis model with real images. It could reduce the cost and time for the image scan, which leads to promoting building the patients outcome prediction with multi-contrast images.
#36 Prognosis prediction based on methionine metabolism genes signature in gliomas | BMC Medical Genomics | Full Text
https://bmcmedgenomics.biomedcentral.com/articles/10.1186/s12920-023-01754-x
The prognostic signature developed based on seven Met metabolism genes in this study performed well in predicting gliomas. […] The C-index of our Met metabolism risk signature was 0.83, which is higher than routine clinical examination items for glioma. […] The Met metabolism risk signature was found to be highly predictive in IDH wt, IDH mutant-codel, and IDH mutant-non-codel subgroups of glioma patients. […] The model had a high accuracy in predicting overall survival of patients with gliomas. […] The model was closely associated with outcome status in both the derivation and validation cohorts, providing novel insights into the prediction of gliomas prognosis.
#37 Prognosis prediction based on methionine metabolism genes signature in gliomas | BMC Medical Genomics | Full Text
https://bmcmedgenomics.biomedcentral.com/articles/10.1186/s12920-023-01754-x
The prognostic signature developed based on seven Met metabolism genes in this study performed well in predicting gliomas. […] The C-index of our Met metabolism risk signature was 0.83, which is higher than routine clinical examination items for glioma. […] The Met metabolism risk signature was found to be highly predictive in IDH wt, IDH mutant-codel, and IDH mutant-non-codel subgroups of glioma patients. […] The model had a high accuracy in predicting overall survival of patients with gliomas. […] The model was closely associated with outcome status in both the derivation and validation cohorts, providing novel insights into the prediction of gliomas prognosis.
#38 Functional prediction of response to therapy prior to therapeutic intervention is associated with improved survival in patients with high-grade glioma | Scientific Reports
https://www.nature.com/articles/s41598-024-68801-0
The results presented here expand on this previous dataset and continue to demonstrate a progression-free survival (PFS) and an OS increase for test-predicted responders compared to non-responders across both HGG and GBM specifically. […] 3D Predict Glioma provides functional results within 710 days of tissue receipt, enabling optimization of patient management prior to therapy initiation. […] These results support the use of 3D Predict Glioma across the spectrum of newly diagnosed HGG patients. […] In all groups analyzed, test-predicted responders survived longer than test-predicted non-responders and historical median OS (14.6 months) and PFS (6.7 months). […] The data in this analysis, along with previously published data, demonstrates the power of 3D Predict Glioma and functional precision medicine to provide patient-specific drug response predictions beyond the current limitations of traditional biomarkers in HGG and GBM.
#39 Functional prediction of response to therapy prior to therapeutic intervention is associated with improved survival in patients with high-grade glioma | Scientific Reports
https://www.nature.com/articles/s41598-024-68801-0
Patients with high-grade glioma (HGG) have an extremely poor prognosis compounded by a lack of advancement in clinical care over the past few decades. […] Median survival between test-predicted temozolomide responders and test-predicted temozolomide non-responders revealed a statistically significant increase in progression-free survival when using the test to predict response across multiple subgroups including HGG (5.8 months), glioblastoma (4.7 months), and MGMT unmethylated glioblastoma (4.7 months). Overall survival was also positively separated across the subgroups at 7.6, 5.1, and 6.3 months respectively. […] The strong correlation of 3D Predict Glioma test results with clinical outcomes demonstrates that this functional test is prognostic in patients treated with RT/TMZ and supports aligning clinical treatment to test-predicted response across varying HGG subgroups.
#40 Functional prediction of response to therapy prior to therapeutic intervention is associated with improved survival in patients with high-grade glioma | Scientific Reports
https://www.nature.com/articles/s41598-024-68801-0
The results presented here expand on this previous dataset and continue to demonstrate a progression-free survival (PFS) and an OS increase for test-predicted responders compared to non-responders across both HGG and GBM specifically. […] 3D Predict Glioma provides functional results within 710 days of tissue receipt, enabling optimization of patient management prior to therapy initiation. […] These results support the use of 3D Predict Glioma across the spectrum of newly diagnosed HGG patients. […] In all groups analyzed, test-predicted responders survived longer than test-predicted non-responders and historical median OS (14.6 months) and PFS (6.7 months). […] The data in this analysis, along with previously published data, demonstrates the power of 3D Predict Glioma and functional precision medicine to provide patient-specific drug response predictions beyond the current limitations of traditional biomarkers in HGG and GBM.
#41 Prognostic and Predictive Biomarkers in Gliomas
https://pmc.ncbi.nlm.nih.gov/articles/PMC8508830/
7+/10 is a negative prognostic factor in gliomas. […] TERT promoter mutation is a negative prognostic factor, but mainly in IDH-wildtype gliomas. […] Overall, in pediatric patients, the determination of protein K27 and G34 defects is of the greatest clinical importance. […] In glioma patients with MYB and MYBL1 mutations, the clinical course is generally indolent. […] The MAPK pathway activation is a predictor of a favorable patient outcome. […] MGMT promoter methylation has the most impact on clinical practice for patients with glioblastoma. […] Many biomarkers have been reported and are now clinically used in the management of neuro-oncology patients. They now play a crucial role in improving diagnostic accuracy, determining prognosis, and predicting treatment responses.
#42 Prognostic and Predictive Biomarkers in Gliomas
https://www.mdpi.com/1422-0067/22/19/10373
Gliomas are the most common central nervous system tumors. […] Survival outcomes are largely dependent on grade, with CNS World Health Organization (WHO) grade 1 having the best relative survival, and CNS WHO grade 4 having the worst overall survival (OS) rate, with just 6.8% of patients living for five years after diagnosis. […] Prognostic and predictive markers play an important role in clinical practice for the assessment of prognosis and the selection of appropriate therapy. […] In adult patients, IDH mutation has the greatest prognostic significance and clinical utility. Therefore, it should be assessed first and foremost. […] In malignant gliomas, the combination of IDH1 mutations and MGMT methylation status is more predictive of survival than either IDH1 or MGMT alone. […] In pediatric patients, H3F3A alterations are the most important markers which predict the worse outcome.
#43 Prognostic and Predictive Biomarkers in Gliomas
https://pmc.ncbi.nlm.nih.gov/articles/PMC8508830/
7+/10 is a negative prognostic factor in gliomas. […] TERT promoter mutation is a negative prognostic factor, but mainly in IDH-wildtype gliomas. […] Overall, in pediatric patients, the determination of protein K27 and G34 defects is of the greatest clinical importance. […] In glioma patients with MYB and MYBL1 mutations, the clinical course is generally indolent. […] The MAPK pathway activation is a predictor of a favorable patient outcome. […] MGMT promoter methylation has the most impact on clinical practice for patients with glioblastoma. […] Many biomarkers have been reported and are now clinically used in the management of neuro-oncology patients. They now play a crucial role in improving diagnostic accuracy, determining prognosis, and predicting treatment responses.
#44
https://link.springer.com/article/10.1007/s11060-024-04715-1
High-grade glioma (HGG) is the most common and deadly malignant glioma of the central nervous system. The aim of this study is to develop models capable of predicting functional outcomes in HGG patients before surgery, facilitating improved disease management and informed patient care. […] The current work demonstrates the ability of machine learning to classify postoperative functional outcomes in HGG patients prior to surgery accurately. Our results suggest that both FC and the tumors location in relation to specific networks can serve as reliable predictors of functional outcomes, leading to personalized therapeutic approaches tailored to individual patients. […] The study highlights the potential of machine learning in accurately classifying postsurgical functional outcomes among HGG patients. These findings indicate the feasibility of achieving classification accuracy exceeding 90% before surgical intervention, using basic demographics, tumor volume, and RS-fMRI measures.
#45 Functional prediction of response to therapy prior to therapeutic intervention is associated with improved survival in patients with high-grade glioma | Scientific Reports
https://www.nature.com/articles/s41598-024-68801-0
The results presented here expand on this previous dataset and continue to demonstrate a progression-free survival (PFS) and an OS increase for test-predicted responders compared to non-responders across both HGG and GBM specifically. […] 3D Predict Glioma provides functional results within 710 days of tissue receipt, enabling optimization of patient management prior to therapy initiation. […] These results support the use of 3D Predict Glioma across the spectrum of newly diagnosed HGG patients. […] In all groups analyzed, test-predicted responders survived longer than test-predicted non-responders and historical median OS (14.6 months) and PFS (6.7 months). […] The data in this analysis, along with previously published data, demonstrates the power of 3D Predict Glioma and functional precision medicine to provide patient-specific drug response predictions beyond the current limitations of traditional biomarkers in HGG and GBM.
#46 Glioblastoma Prognosis | Survival Rates
https://www.thebraintumourcharity.org/brain-tumour-diagnosis-treatment/types-of-brain-tumour-adult/glioblastoma/glioblastoma-prognosis/
Glioblastoma prognosis is when your doctor or medical team explains what you might expect from your diagnosis. […] We know that glioblastoma prognosis is a sensitive topic and can be difficult to read about. […] Your doctor cant be absolutely certain about what will happen to you following a brain tumour diagnosis. But, they can give you an estimate, based on your tumour type and current situation. […] The average glioblastoma survival time is 12-18 months only 25% of patients survive more than one year, and only 5% of patients survive more than five years. […] Please remember that statistics and averages cant tell you what will happen to you specifically. […] Different people approach their prognosis in different ways. […] If you are feeling unsure or worried about a glioblastoma prognosis, contact our Support team on 0808 800 0004 or at [email protected].