***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: Abstract  Variability  in patients ' response to interventions in pain and other clinical setting s is large . Many explanations such as trial methods , environment or culture have been proposed , but this paper sets out to show that the main cause of the variability may be r and om chance , and that if trials are small their estimate of magnitude of effect may be incorrect , simply because of the r and om play of chance . This is highly relevant to the questions of ‘ How large do trials have to be for statistical accuracy ? ’ and ‘ How large do trials have to be for their results to be clinical ly valid ? ’ The true underlying control event rate ( CER ) and experimental event rate ( EER ) were determined from single‐dose acute pain analgesic trials in over 5000 patients . Trial group size required to obtain statistically significant and clinical ly relevant ( 0.95 probability of number‐needed‐to‐treat within ±0.5 of its true value ) results were computed using these values . Ten thous and trials using these CER and EER values were simulated using varying group sizes to investigate the variation due to r and om chance alone . Most common analgesics have EERs in the range 0.4–0.6 and CER of about 0.19 . With such efficacy , to have a 90 % chance of obtaining a statistically significant result in the correct direction requires group sizes in the range 30–60 . For clinical relevance nearly 500 patients are required in each group . Only with an extremely effective drug ( EER>0.8 ) will we be reasonably sure of obtaining a clinical ly relevant NNT with commonly used group sizes of around 40 patients per treatment arm . The simulated trials showed substantial variation in CER and EER , with the probability of obtaining the correct values improving as group size increased . We contend that much of the variability in control and experimental event rates is due to r and om chance alone . Single small trials are unlikely to be correct . If we want to be sure of getting correct ( clinical ly relevant ) results in clinical trials we must study more patients . Credible estimates of clinical efficacy are only likely to come from large trials or from pooling multiple trials of conventional ( small ) size & NA ; There is uncertainty over whether the patient group in which acute pain studies are conducted ( pain model ) has any influence on the estimate of analgesic efficacy . Data from four recently up date d systematic review s of aspirin 600/650 mg , paracetamol 600/650 mg , paracetamol 1000 mg and ibuprofen 400 mg were used to investigate the influence of pain model . Area under the pain relief versus time curve equivalent to at least 50 % maximum pain relief over 6 h was used as the outcome measure . Event rates with treatment and placebo , and relative benefit ( RB ) and number needed to treat ( NNT ) were used as outputs from the meta‐analyses . The event rate with  placebo was systematic ally statistically lower for dental than postsurgical pain for all four treatments . Event rates with analgesics , RB and NNT were infrequently different between the pain models . Systematic difference in the estimate of analgesic efficacy between dental and postsurgical pain models remains unproven , and , on balance , no major difference is likely Background Previous analysis of a single data set in acute pain following third molar extraction demonstrated a strong relationship between the speed of reduction of pain intensity and overall pain relief , as well as need for additional analgesia . Methods Individual patient data analysis of a single r and omized , double-blind trial of placebo , paracetamol 1000 mg , ibuprofen sodium 400 mg and ibuprofen-poloxamer 400 mg following third molar extraction .  Visual analogue scale pain intensity ( VASPI ) and other measurements were made at baseline , every 5–45 min , and at 60 , 90 , 120 , 180 , 240 , 300 and 360 min . Results Most patients produced consistent VASPI results over time . For placebo and paracetamol , few patients achieved low VASPI scores and maintained them . For both ibuprofen formulations , VASPI scores fell rapidly during the first hour and were then typically maintained until later re-medication . Analysis of all patients showed that rapid VASPI reduction in the first hour was strongly correlated with good overall pain relief ( high total pain relief over 0–6 h ) , and with lesser need for additional analgesia within 6 h. Results for this analysis were in very good agreement with a previous analysis , validating the relationship between fast initial pain intensity reduction and overall good pain relief in this setting . Conclusions In acute pain following third molar extraction , faster acting analgesic formulations provide earlier onset of pain relief , better overall pain relief and a less frequent need for additional analgesia , indicating longer lasting pain relief Abstract A previously established relationship for deriving dichotomous from continuous information in r and omised controlled trials ( RCTs ) of analgesics has been tested using an independent data set . Individual patient information from 18 RCTs of parallel‐group design in acute postoperative pain ( after abdominal , gynaecological and oral surgery ) was used to calculate the percentage of the maximum possible pain relief score  ( % maxTOTPAR ) and the proportion of patients with > 50%maxTOTPAR for the different treatments . The relationship between the measures was investigated in 85 treatments with over 3400 patients . In 80 of 85 treatments ( 94 % ) agreement between calculated and actual number of patients with > 50%maxTOTPAR was within four patients per treatment and in 72 ( 85 % ) was within three ( average of 40 patients per treatment , range 21–58 patients ) . Summing the positive and negative differences between actual and calculated numbers of patients with > 50%maxTOTPAR gave an average difference of 0.30 patients per treatment arm . Reports of RCTs of analgesics frequently describe results of studies in the form of mean derived indices , rather than using discontinuous events , such as number or proportion of patients with 50 % pain relief . Because mean data inadequately describe information with a non‐normal distribution , combining mean data in systematic review s may compromise the results . Showing that dichotomous data can reliably be derived from mean data in acute pain studies enables data published as means to be used for quantitative systematic review s which require data in dichotomous form & NA ; Reports of RCTs of analgesics frequently describe results of studies in the form of mean derived indices , rather than using discontinuous events — such as number or proportion of patients with 50 % pain relief . Because mean data inadequately describe information with a non‐normal distribution , combining mean data in systematic review s may compromise the results . Showing that dichotomous data can reliably be derived from mean data , at least in acute pain models , indicates that more meaningful overviews or meta‐ analysis may be possible . This study investigated the relationship between continuous and dichotomous analgesic measures in a set of individual patient data , and then used that relationship to derive dichotomous from continuous information in r and omised controlled trials ( RCTs ) of analgesics .  Individual patient information from 13 RCTs of parallel‐group and crossover design in acute postoperative pain was used to calculate the percentage of the maximum possible pain relief score ( % maxTOTPAR ) and the proportion of patients with greater than 50 % pain relief ( > 50%maxTOTPAR ) for the different treatments . The relationship between the measures was investigated in 45 actual treatments and 10 000 treatments simulated using the underlying actual distribution ; 1283 patients had 45 separate treatments . Mean % maxTOTPAR correlated with the proportion of patients with > 50%maxTOTPAR ( r2 = 0.90 ) . The relationship calculated from all the 45 treatments predicted to within three patients the number of patients with more than 50 % pain relief in 42 of 45 treatments , and 98.8 % of 10 000 simulated treatments . For seven effective treatments , actual numbers‐needed‐to‐treat ( NNT ) to achieve > 50%maxTOTPAR compared with placebo were very similar to those derived from calculated data OBJECTIVES To survey the frequency of use of indirect comparisons in systematic review s and evaluate the methods used in their analysis and interpretation . Also to identify alternative statistical approaches for the analysis of indirect comparisons , to assess the properties of different statistical methods used for performing indirect comparisons and to compare direct and indirect estimates of the same effects within review s. DATA SOURCES Electronic data bases . REVIEW METHODS The Data base of Abstract s of Review s of Effects ( DARE ) was search ed for systematic review s involving meta- analysis of r and omised controlled trials ( RCTs ) that reported both direct and indirect comparisons , or indirect comparisons alone . A systematic review of MEDLINE and other data bases was carried out to identify published methods for analysing indirect comparisons . Study design s were created using data from the International Stroke Trial . R and om sample s of patients receiving aspirin , heparin or placebo in 16 centres were used to create meta-analyses , with half of the trials comparing aspirin and placebo and half heparin and placebo . Methods for indirect comparisons were used to estimate the contrast between aspirin  and  heparin . The whole process was repeated 1000 times and the results were compared with direct comparisons and also theoretical results . Further detailed case studies comparing the results from both direct and indirect comparisons of the same effects were undertaken . RESULTS Of the review s identified through DARE , 31/327 ( 9.5 % ) included indirect comparisons . A further five review s including indirect comparisons were identified through electronic search ing . Few review s carried out a formal analysis and some based analysis on the naive addition of data from the treatment arms of interest . Few method ological papers were identified . Some valid approaches for aggregate data that could be applied using st and ard software were found : the adjusted indirect comparison , meta-regression and , for binary data only , multiple logistic regression ( fixed effect models only ) . Simulation studies showed that the naive method is liable to bias and also produces over-precise answers . Several methods provide correct answers if strong but unverifiable assumptions are fulfilled . Four times as many similarly sized trials are needed for the indirect approach to have the same power as directly r and omised comparisons . Detailed case studies comparing direct and indirect comparisons of the same effect show considerable statistical discrepancies , but the direction of such discrepancy is unpredictable . CONCLUSIONS Direct evidence from good- quality RCTs should be used wherever possible . Without this evidence , it may be necessary to look for indirect comparisons from RCTs . However , the results may be susceptible to bias . When making indirect comparisons within a systematic review , an adjusted indirect comparison method should ideally be used employing the r and om effects model . If both direct and indirect comparisons are possible within a review , it is recommended that these be done separately before considering whether to pool data . There is a need to evaluate methods for the analysis of indirect comparisons for continuous data and for empirical research into how different methods of indirect comparison perform in cases where there is a large treatment effect . Further study is needed into when it is appropriate to look at indirect comparisons and when to combine both direct and indirect comparisons . Research into how evidence from indirect comparisons compares to that from non-r and omised studies may also be warranted . Investigations using individual patient data from a meta- analysis of several RCTs using different protocol s and an evaluation of the impact of choosing different binary effect measures for the inverse variance method would also be useful Abstract One way to ensure adequate sensitivity for analgesic trials is to test the intervention on patients who have established pain of moderate to severe intensity . The usual criterion is at least moderate pain on a categorical pain intensity scale . When visual analogue scales ( VAS ) are the only pain measure in trials we need to know what point on a VAS represents moderate pain , so that these trials can be included in meta‐ analysis when baseline pain of at least moderate intensity is an inclusion criterion . To investigate this we used individual patient data from 1080 patients from r and omised controlled trials of various analgesics .  Baseline pain was measured using a 4‐point categorical pain intensity scale and a pain intensity VAS under identical conditions . The distribution of the VAS scores was examined for 736 patients reporting moderate pain and for 344 reporting severe pain .  The VAS scores corresponding to moderate or severe pain were also examined by gender . Baseline VAS scores recorded by patients reporting moderate pain were significantly different from those of patients reporting severe pain . Of the patients reporting moderate pain 85 % scored over 30 mm on the corresponding VAS , with a mean score of 49 mm . For those reporting severe pain 85 % scored over 54 mm with a mean score of 75 mm . There was no difference between the corresponding VAS scores of men and women . Our results indicate that if a patient records a baseline VAS score in excess of 30 mm they would probably have recorded at least moderate pain on a 4‐point categorical scale 
    Output:
    
We found no information on many of the commonly available low dose codeine combinations .
For ibuprofen plus paracetamol , adverse event rates were lower than with placebo .
The proportion of people with acute pain who get good pain relief with any of them ranges from around 70 % at best to less than 20 % at worst ; low doses of some drugs in fast acting formulations were among the best .
Adverse events were generally no different from placebo .