In this task, you are given a passage which has a question and the context. You have to generate an answer to the question based on the information present in the context.

Example Input: Context: Glioblastomas treated with bevacizumab may develop low-signal apparent diffusion coefficient (low-ADC) lesions, which may reflect increased tumor cellularity or atypical necrosis. The purpose of this study was to examine the relationship between low-ADC lesions and overall survival (OS). We hypothesized that growing low-ADC lesions would be associated with shorter OS.', 'We retrospectively identified 52 patients treated with bevacizumab for the first (n = 42, 81%) or later recurrence of primary glioblastoma, who had low-ADC lesions and 2 post-bevacizumab scans ≤90 days apart. Low-ADC lesion volumes were measured, and normalized 5th percentile histogram low-ADC values were recorded. Using OS as the primary endpoint, semiparametric Cox models were fitted to ascertain univariate and multivariate hazard ratios (HRs) with significance at P = .05.', 'Median OS was 9.1 months (95% CI = 7.2-14.3). At the second post-bevacizumab scan, the volume of the low-ADC lesion (median: 12.94 cm(3)) was inversely associated with OS, with larger volumes predicting shorter OS (HR = 1.014 [95% CI = 1.003-1.025], P = .009). The percent change in low-ADC volume (median: 6.8%) trended toward increased risk of death with growing volumes (P = .08). Normalized 5th percentile low-ADC value and its percent change were not associated with OS (P > .51). Also correlated with shorter OS were the pre-bevacizumab nonenhancing volume (P = .025), the first post-bevacizumab enhancing volume (P = .040), and the second post-bevacizumab enhancing volume (P = .004).\Question: Do large-volume low apparent diffusion coefficient lesions predict poor survival in bevacizumab-treated glioblastoma patients?
Example Output: The volume of low-ADC lesions at the second post-bevacizumab scan predicted shorter OS. This suggests that low-ADC lesions may be considered important imaging markers and included in treatment decision algorithms.

Example Input: Context: The basis of the treatment of painful diabetic neuropathy is the use of drugs that block the transmission of pain (antineuritics) and a good metabolic control of underlying disease.', 'To describe the outcomes of 17 type-2 diabetics with painful neuropathy, treated between 1988 and 2005 with symptomatic therapy plus intensified insulin.', 'Review of medical records of 17 type-2 diabetic patients, aged 63+/-11 years and a duration of diabetes of 15+/-8 years. All patients received intensified insulin therapy with 0.35 units/kg of NPH insulin (2/3 before breakfast and 1/3 evening meal), plus capillary glucose measurements and regular insulin (with sliding-scale centered in approximately 0.1 units/kg) before the 3 main meals. All patients were also treated with gabapentin, nortriptyline or clomipramine. Pain was assessed using a visual analog score of 10 points.', 'After 1 year, glycosilated hemoglobin decreased from 10.0+/-1.4% to 7.7+/-1.2% (p approximately =0.003). Pain decreased from 10 to 5.1+/-3.3 at one month, 2.3+/-3.2 at six months, and 3.1+/-3.6 at 1 year (p <0.01). There was a direct statistical correlation between the reduction of HbA1C and pain decline (r =0.736; p =0.037). Pain scores were lower than those reported elsewhere for Pregabalin (n =76; p =0.05), Lamotrigine (n =27; p <0.0005), Topiramate (n =208; p <0.005), and Gabapentin (n =84; p <0.025). The lack of difference to Sodium Valproate (n =21; p =0.07) had borderline significance.\Question: Is [ Intensified insulin therapy plus antineuritic medication more effective than antineuritics alone in painful diabetic neuropathy ]?
Example Output: The addition of intensified insulin therapy to the symptomatic treatment of painful neuropathy in type-2 diabetics, significantly enhanced the reduction of pain. The lowering of glycosilated hemoglobin was a significant predictor of success in pain reduction.

Example Input: Context: To systematically review methodological articles which focus on nonpublication of studies and to describe methods of detecting and/or quantifying and/or adjusting for dissemination in meta-analyses. To evaluate whether the methods have been applied to an empirical data set for which one can be reasonably confident that all studies conducted have been included.', 'We systematically searched Medline, the Cochrane Library, and Web of Science, for methodological articles that describe at least one method of detecting and/or quantifying and/or adjusting for dissemination bias in meta-analyses.', 'The literature search retrieved 2,224 records, of which we finally included 150 full-text articles. A great variety of methods to detect, quantify, or adjust for dissemination bias were described. Methods included graphical methods mainly based on funnel plot approaches, statistical methods, such as regression tests, selection models, sensitivity analyses, and a great number of more recent statistical approaches. Only few methods have been validated in empirical evaluations using unpublished studies obtained from regulators (Food and Drug Administration, European Medicines Agency).\Question: Are methods for detecting , quantifying , and adjusting for dissemination bias in meta-analysis described?
Example Output:
We present an overview of existing methods to detect, quantify, or adjust for dissemination bias. It remains difficult to advise which method should be used as they are all limited and their validity has rarely been assessed. Therefore, a thorough literature search remains crucial in systematic reviews, and further steps to increase the availability of all research results need to be taken.