Kalafi ya kankere ya makgwafo e ikaegile ka dilo di le mmalwa, go akaretsa le gore kankere e mo kgatong efe, mofuta wa kankere ya makgwafo le gore molwetse o itekanetse go le kana kang.
Dingwe tsa ditsela tse di tlwaelegileng tsa go alafa di akaretsa:
1. Karo: Gantsi eno ke yone kalafi e e dirisiwang thata mo go alafeng kankere ya makgwafo e e sa tswang go simolola.
Ngaka e e arang e ntsha tlhagala le karolwana e nnye ya dithishu tse di itekanetseng tse di e dikologileng.
2. Kalafi ya marang: Go dirisiwa marang a a maatla thata go bolaya disele tsa kankere le go fokotsa ditlhagala.
E ka dirisiwa e le nosi kgotsa e dirisiwa mmogo le mefuta e mengwe ya kalafi.
3. Kalafi ya dikhemikale: Kalafi eno e dirisa diokobatsi go bolaya disele tsa kankere.
E ka nowa ka go tsenngwa mo mothapong kana ka molomo, mme gantsi e dirisiwa mmogo le dikalafi tse dingwe.
Kalafi e e diretsweng go bolaya disele tsa kankere: Kalafi eno e tlhasela dijini kgotsa diporoteine tse di rileng tse di thusang disele tsa kankere go gola le go tshela.
Gantsi e dirisiwa mo kankere ya makgwafo e e setseng e etegetse kgotsa e e anameng.
5. Kalafi ya go lwantsha malwetse: Kalafi eno e thusa thulaganyo ya mmele ya go lwantsha malwetse go lemoga disele tsa kankere le go di tlhasela.
Gantsi e dirisiwa mo kankere ya makgwafo e e setseng e etegetse kgotsa e e anameng.
6. Photodynamic therapy: Kalafi eno e dirisa seokobatsi se se ntshang lesedi go bolaya disele tsa kankere.
Gantsi e dirisiwa mo kankere ya makgwafo e e sa ntseng e simologa.
7. Kalafi ya proton: Eno ke mofuta wa kalafi ya marang e e dirisang diprotone go na le marang a x-ray go isa marang kwa tlhagaleng.
Gantsi e dirisiwa mo kankere ya makgwafo e e sa ntseng e simologa.
8. Diteko tsa kalafi: Balwetse ba ka nna ba tshwanelega go nna le seabe mo ditekong tsa kalafi tse di lekang kalafi e ntšha kana go kopanya mefuta e mesha ya kalafi.
Go botlhokwa gore o tlotle le setlhopha sa kalafi ka kalafi e e molemo go gaisa, ka gonne thulaganyo e e molemo go gaisa ya kalafi e tla ikaega ka boemo jwa motho yoo.
Chen JH, Wu J, Xu Q: The emerging treatment landscape of targeted therapy in non-small-cell lung cancer. Signal Transduct Target Ther. , 4 (): 61.
Furuse K: [Photodynamic therapy of centrally located early-stage lung cancer]. Gan To Kagaku Ryoho. 1996, 23 (1): 27-30.
Gálffy G: [From rare mutations to classical ones, inhibition of signaling pathways in non-small cell lung cancer]. Magy Onkol. 2020, 64 (3): 196-204.
Magalhães M, Alvarez-Lorenzo C, Concheiro A, Figueiras A, Santos AC, Veiga F: RNAi-based therapeutics for lung cancer: biomarkers, microRNAs, and nanocarriers. Expert Opin Drug Deliv. 2018, 15 (10): 965-982.
Kataoka M, Fujiwara T, Tanaka N: [Gene therapy for lung cancer]. Nihon Geka Gakkai Zasshi. 2002, 103 (2): 244-9.
Jin C, Yang B: A Case of Delayed Diagnostic Pulmonary Tuberculosis during Targeted Therapy in an EGFR Mutant Non-Small Cell Lung Cancer Patient. Case Rep Oncol. , 14 (1): 659-663.
Wang Y, Liu Q, Chen H, You J, Peng B, Cao F, Zhang X, Chen Q, Uzan G, Xu L, Zhang D: Celastrol improves the therapeutic efficacy of EGFR-TKIs for non-small-cell lung cancer by overcoming EGFR T790M drug resistance. Anticancer Drugs. 2018, 29 (8): 748-755.
['Go se ikarabele: kalafi']
['Web site eno e diretswe go ruta le go naya tshedimosetso fela mme ga e neye kgakololo ya kalafi kgotsa ditirelo tsa seporofešenale.']
['Tshedimosetso e e neelwang ga e a tshwanela go dirisiwa go bona bolwetse kana go alafa bothata jwa botsogo, mme batho ba ba batlang kgakololo ya kalafi ba tshwanetse go ikgolaganya le ngaka e e nang le laesense.']
['Tsweetswee ela tlhoko gore thulaganyo ya methapo e e dirang dikarabo tsa dipotso tseno, ga e a tlhomama fa go tla mo dilong tsa dipalo. Ka sekai, palo ya batho ba ba nang le bolwetse bongwe jo bo rileng.']
['Ka metlha batla kgakololo ya ngaka ya gago kgotsa moabi yo mongwe wa kalafi yo o tshwanelegang malebana le boemo jwa kalafi. Le ka motlha o se ka wa itlhokomolosa kgakololo ya kalafi ya porofeshenale kgotsa wa diega go e batla ka ntlha ya sengwe se o se badileng mo website eno. Fa o akanya gore o ka tswa o na le boemo jwa tshoganyetso jwa kalafi, leletsa 911 kgotsa o ye kwa kamoreng ya tshoganyetso e e gaufi le wena ka bonako. Ga go na kamano epe ya ngaka le molwetse e e tlisiwang ke website eno kgotsa go e dirisa. BioMedLib kgotsa badiri ba yone, kgotsa ope fela yo o tsentseng letsogo mo website eno, ga ba dire ditshupetso dipe, tse di tlhamaletseng kgotsa tse di sa tlhamalalang, malebana le tshedimosetso e e mo go yone kgotsa go e dirisa.']
['Go ikgatholosa: ditshwanelo tsa bokwadi']
['Molao wa Digital Millennium Copyright wa 1998, 17 U.S.C. § 512 (the DMCA) o tlamela ka kgetse ya beng ba ditshwanelo ba ba dumelang gore matheriale o o tlhagelelang mo inthaneteng o gataka ditshwanelo tsa bona go ya ka molao wa ditshwanelo wa U.S.']
['Fa o dumela ka pelo yotlhe gore tshedimosetso kgotsa matheriale o o mo website ya rona kgotsa ditirelo tsa rona o gataka ditshwanelo tsa gago tsa semolao, wena (kgotsa moemedi wa gago) o ka re romelela kitsiso o kopa gore tshedimosetso eo kgotsa matheriale oo o tlosiwe kgotsa o thibelwe go o fitlhelela.']
['Dikitsiso di tshwanetse go romelwa ka go kwala ka imeili (leba karolo ya "Contact" go bona aterese ya imeili).']
['DMCA e batla gore kitsiso ya gago ya go tlolwa ga ditshwanelo tsa gago e akaretse tshedimosetso e e latelang: (1) tlhaloso ya tiro e e sireleditsweng ka ditshwanelo e go tweng e tlotswe; (2) tlhaloso ya diteng tse go tweng di tlotswe le tshedimosetso e e lekaneng go re letla go bona diteng; (3) tshedimosetso ya go ikgolaganya le wena, go akaretsa aterese ya gago, nomoro ya mogala le aterese ya imeile; (4) polelo ya gago ya gore o dumela ka pelo yotlhe gore diteng tse di tlotsweng ga di a letlelelwa ke mong wa ditshwanelo tsa gago, kgotsa moemedi wa gagwe, kgotsa ka molao ope; ']
['(5) polelo e e saenilweng ke wena, e e supang gore tshedimosetso e e mo kitsisong e boammaaruri le gore o na le thata ya go diragatsa ditshwanelo tsa botaki tse go tweng di gatakilwe;']
['le (6) saena ya mmatota kgotsa ya eleketeroniki ya mong wa tshwanelo ya go gatisa kgotsa motho yo o filweng tetla ya go dira mo boemong jwa mong wa tshwanelo ya go gatisa. ']
['Fa o sa akaretse tshedimosetso yotlhe e e fa godimo e ka nna ya diegisa go sekasekwa ga ngongorego ya gago.']
['Go Ikgolaganya']
['Tsweetswee re romelele imeile ka potso/kgakololo epe fela.']
How to treat lung cancer?
The treatment for lung cancer depends on several factors, including the stage of the cancer, the type of lung cancer, and the patient's overall health.
Some common treatment options include:
1. Surgery: This is often the preferred treatment for early-stage lung cancer.
The surgeon removes the tumor and a small portion of healthy tissue around it.
2. Radiation therapy: High-energy radiation is used to kill cancer cells and shrink tumors.
It can be used alone or in combination with other treatments.
3. Chemotherapy: This treatment uses drugs to kill cancer cells.
It can be given intravenously or or orally, and is often used in combination with other treatments.
4. Targeted therapy: This treatment targets specific genes or proteins that contribute to the growth and survival of cancer cells.
It is often used for advanced or metastatic lung cancer.
5. Immunotherapy: This treatment helps the immune system recognize and attack cancer cells.
It is often used for advanced or metastatic lung cancer.
6. Photodynamic therapy: This treatment uses a light-activated drug to kill cancer cells.
It is often used for early-stage lung cancer.
7. Proton therapy: This is a type of radiation therapy that uses protons instead of x-rays to deliver radiation to the tumor.
It is often used for early-stage lung cancer.
8. Clinical trials: Patients may be eligible to participate in clinical trials testing new treatments or combinations of treatments.
It is important to discuss the best treatment options with a healthcare team, as the most effective treatment plan will depend on the individual's specific situation.
Disclaimer: medical
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Please note the neural net that generates answers to the questions, is specially inaccurate when it comes to numeric content. For example, the number of people diagnosed with a specific disease.
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Disclaimer: copyright
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['Mo e ka nnang']
['BioMedLib e dirisa dikhomputara tse di itirisang (machine-learning algorithms) go dira dipotso le dikarabo.']
['Re simolola ka dikgatiso di le dimilione di le 35 tsa tsa kalafi ya ditshedi tsa PubMed/Medline. Gape, ditsebe tsa Web tsa RefinedWeb.']
